Exploring Torus Universes in Causal Dynamical Triangulations
Budd, T G
2013-01-01
Motivated by the search for new observables in nonperturbative quantum gravity, we consider Causal Dynamical Triangulations (CDT) in 2+1 dimensions with the spatial topology of a torus. This system is of particular interest, because one can study not only the global scale factor, but also global shape variables in the presence of arbitrary quantum fluctuations of the geometry. Our initial investigation focusses on the dynamics of the scale factor and uncovers a qualitatively new behaviour, which leads us to investigate a novel type of boundary conditions for the path integral. Comparing large-scale features of the emergent quantum geometry in numerical simulations with a classical minisuperspace formulation, we find partial agreement. By measuring the correlation matrix of volume fluctuations we succeed in reconstructing the effective action for the scale factor directly from the simulation data. Apart from setting the stage for the analysis of shape dynamics on the torus, the new set-up highlights the role o...
On a renormalization group scheme for causal dynamical triangulations
Cooperman, Joshua H.
2016-03-01
The causal dynamical triangulations approach aims to construct a quantum theory of gravity as the continuum limit of a lattice-regularized model of dynamical geometry. A renormalization group scheme—in concert with finite size scaling analysis—is essential to this aim. Formulating and implementing such a scheme in the present context raises novel and notable conceptual and technical problems. I explored these problems, and, building on standard techniques, suggested potential solutions in a previous paper (Cooperman, arXiv:gr-qc/1410.0026). As an application of these solutions, I now propose a renormalization group scheme for causal dynamical triangulations. This scheme differs significantly from that studied recently by Ambjørn, Görlich, Jurkiewicz, Kreienbuehl, and Loll.
Impact of topology in causal dynamical triangulations quantum gravity
Ambjorn, Jan; Drogosz, Zbigniew; Gizbert-Studnicki, Jakub; Goerlich, Andrzej; Jurkiewicz, Jerzy; Nemeth, Daniel
2016-01-01
We investigate the impact of spatial topology in 3+1 dimensional causal dynamical triangulations (CDT) by performing numerical simulations with toroidal spatial topology instead of the previously used spherical topology. In the case of spherical spatial topology we observed in the so-called phase C an average spatial volume distribution n(t) which after a suitable time redefinition could be identified as the spatial volume distribution of the four-sphere. Imposing toroidal spatial topology we...
The transfer matrix in four dimensional causal dynamical triangulations
Ambjo̸rn, J.; Gizbert-Studnicki, J.(Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 11, Krakow, PL 30-348, Poland); Görlich, A.T.; Jurkiewicz, J.; Loll, R.
2013-01-01
The Causal Dynamical Triangulation model of quantum gravity (CDT) is a proposition to evaluate the path integral over space-time geometries using a lattice regularization with a discrete proper time and geometries realized as simplicial manifolds. The model admits a Wick rotation to imaginary time for each space-time configuration. Using computer simulations we determined the phase structure of the model and discovered that it predicts a de Sitter phase with a four-dimensional spherical semi-...
Scale-dependent homogeneity measures for causal dynamical triangulations
Cooperman, Joshua H
2014-01-01
I propose two scale-dependent measures of the homogeneity of the quantum geometry determined by an ensemble of causal triangulations. The first measure is volumetric, probing the growth of volume with graph geodesic distance. The second measure is spectral, probing the return probability of a random walk with diffusion time. Both of these measures, particularly the first, are closely related to those used to assess the homogeneity of our own universe on the basis of galaxy redshift surveys. I employ these measures to quantify the quantum spacetime homogeneity as well as the temporal evolution of quantum spatial homogeneity of ensembles of causal triangulations in the well-known physical phase. According to these measures, the quantum spacetime geometry exhibits some degree of inhomogeneity on sufficiently small scales and a high degree of homogeneity on sufficiently large scales. This inhomogeneity appears unrelated to the phenomenon of dynamical dimensional reduction. I also uncover evidence for power-law sc...
Extrinsic curvature in 2-dimensional Causal Dynamical Triangulation
Glaser, Lisa; Weinfurtner, Silke
2016-01-01
Causal Dynamical Triangulations (CDT) is a non-perturbative quantisation of general relativity. Ho\\v{r}ava-Lifshitz gravity on the other hand modifies general relativity to allow for perturbative quan- tisation. Past work has given rise to the speculation that Ho\\v{r}ava-Lifshitz gravity might correspond to the continuum limit of CDT. In this paper we add another piece to this puzzle by applying the CDT quantisation prescription directly to Ho\\v{r}ava-Lifshitz gravity in 2 dimensions. We derive the continuum Hamiltonian and we show that it matches exactly the Hamiltonian one derives from canonically quantising the Ho\\v{r}ava-Lifshitz action. Unlike the standard CDT case, here the intro- duction of a foliated lattice does not impose further restriction on the configuration space and, as a result, lattice quantisation does not leave any imprint on continuum physics as expected.
Causal Dynamical Triangulation of 3D Tensor Model
Kawabe, Hiroshi
2016-01-01
We extend the string field theory of the two dimensional (2D) generalized causal dynamical triangulation (GCDT) with the Ishibashi-Kawai (IK-) type interaction formulated by the matrix model, to the three dimensional (3D) model of the surface field theory. Based on the loop gas model, we construct a tensor model for the discretized surface field and then apply it the stochastic quantization method. In the double scaling limit, the model is characterized by two scaling dimensions $D$ and $D_N$, the power indices of the minimal length as the scaling parameter. The continuum GCDT model with the IK-type interaction is realized with the similar restriction in the $D_N$-$D$ space, to the 2D model. The distinct property in the 3D model is that the quantum effect contains the IK-type interaction only, while the ordinary splitting interaction is excluded.
Can causal dynamical triangulations probe factor-ordering issues?
Maitra, R L
2009-01-01
The causal dynamical triangulations (CDT) program has for the first time allowed for path-integral computation of correlation functions in full general relativity without symmetry reductions and taking into account Lorentzian signature. One of the most exciting recent results in CDT is the strong agreement of these computations with (minisuperspace) path integral calculations in quantum cosmology. Herein I will describe my current project to compute minisuperspace (Friedman-Robertson-Walker) path integrals with a range of different measures corresponding to various factor orderings of the Friedman-Robertson-Walker Hamiltonian. The aim is to compare with CDT results and ask whether CDT can shed light on factor-ordering ambiguities in quantum cosmology models.
Searching for a continuum limit in causal dynamical triangulation quantum gravity
Ambjorn, J.; Coumbe, D. N.; Gizbert-Studnicki, J.; Jurkiewicz, J.
2016-05-01
We search for a continuum limit in the causal dynamical triangulation approach to quantum gravity by determining the change in lattice spacing using two independent methods. The two methods yield similar results that may indicate how to tune the relevant couplings in the theory in order to take a continuum limit.
Searching for a continuum limit in causal dynamical triangulation quantum gravity
Ambjorn, J.; Coumbe, D. N.; Gizbert-Studnicki, J.(Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 11, Krakow, PL 30-348, Poland); Jurkiewicz, J.
2016-01-01
We search for a continuum limit in the causal dynamical triangulation (CDT) approach to quantum gravity by determining the change in lattice spacing using two independent methods. The two methods yield similar results that may indicate how to tune the relevant couplings in the theory in order to take a continuum limit.
A first look at transition amplitudes in (2 + 1)-dimensional causal dynamical triangulations
We study a lattice regularization of the gravitational path integral—causal dynamical triangulations—for (2 + 1)-dimensional Einstein gravity with positive cosmological constant in the presence of past and future spacelike boundaries of fixed intrinsic geometries. For spatial topology of a 2-sphere, we determine the form of the Einstein–Hilbert action supplemented by the Gibbons–Hawking–York boundary terms within the Regge calculus of causal triangulations. Employing this action we numerically simulate a variety of transition amplitudes from the past boundary to the future boundary. To the extent that we have so far investigated them, these transition amplitudes appear consistent with the gravitational effective action previously found to characterize the ground state of quantum spacetime geometry within the Euclidean de Sitter-like phase. Certain of these transition amplitudes convincingly demonstrate that the so-called stalks present in this phase are numerical artifacts of the lattice regularization, seemingly indicate that the quantization technique of causal dynamical triangulations differs in detail from that of the no-boundary proposal of Hartle and Hawking, and possibly represent the first numerical simulations of portions of temporally unbounded quantum spacetime geometry within the causal dynamical triangulations approach. We also uncover tantalizing evidence suggesting that Lorentzian not Euclidean de Sitter spacetime dominates the ground state on sufficiently large scales. (paper)
Causal dynamical triangulation for non-critical open-closed string field theory
We extend the 2 dimensional Causal Dynamical Triangulation (CDT) model from the usual model of closed string to the one of open-closed string. The matrix-vector model describing the loop gas model is modified so as to possess the nature of the CDT, i.e. the time foliation structure. Stochastic quantization method produces interactions of loop and line variables similar to those in the non-critical open-closed string field theories. By taking an appropriate scaling, we realize an extended model of the generalized CDT (GCDT), which keeps the causality in a broad sense
Five Dimensional Dynamical Triangulations
George, A
1999-01-01
The dynamical triangulations approach to quantum gravity is investigated in detail for the first time in five dimensions. In this case, the most general action that is linear in components of the f-vector has three terms. It was suspected that the corresponding space of couplings would yield a rich phase structure. This work is primarily motivated by the hope that this new viewpoint will lead to a deeper understanding of dynamical triangulations in general. Ultimately, this research programme may give a better insight into the potential application of dynamical triangulations to quantum gravity. This thesis serves as an exploratory study of this uncharted territory. The five dimensional (k,l) moves used in the Monte Carlo algorithm are proven to be ergodic in the space of combinatorially equivalent simplicial 5-manifolds. A statement is reached regarding the possible existence of an exponential upper bound on the number of combinatorially equivalent triangulations of the 5-sphere. Monte Carlo simulations reve...
3d Lorentzian, dynamically triangulated quantum gravity
Ambjørn, J.; Jurkiewicz, J.(Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 11, Krakow, PL 30-348, Poland); Loll, R
2006-01-01
The model of Lorentzian three-dimensional dynamical triangulations provides a non-perturbative definition of three-dimensional quantum gravity. The theory has two phases: a weak-coupling phase with quantum fluctuations around a ``semiclassical'' background geometry which is generated dynamically despite the fact that the formulation is explicitly background-independent, and a strong-coupling phase where ``classical'' space disintegrates into a foam of baby universes.
Roaming moduli space using dynamical triangulations
Ambjorn, J., E-mail: ambjorn@nbi.dk [Niels Bohr Institute, Copenhagen University, Blegdamsvej 17, DK-2100 Copenhagen O (Denmark); Barkley, J., E-mail: barkley@nbi.dk [Niels Bohr Institute, Copenhagen University, Blegdamsvej 17, DK-2100 Copenhagen O (Denmark); Budd, T.G., E-mail: t.g.budd@uu.nl [Institute for Theoretical Physics, Utrecht University, Leuvenlaan 4, NL-3584 CE Utrecht (Netherlands)
2012-05-11
In critical as well as in non-critical string theory the partition function reduces to an integral over moduli space after integration over matter fields. For non-critical string theory this moduli integrand is known for genus one surfaces. The formalism of dynamical triangulations provides us with a regularization of non-critical string theory. We show how to assign in a simple and geometrical way a moduli parameter to each triangulation. After integrating over possible matter fields we can thus construct the moduli integrand. We show numerically for c=0 and c=-2 non-critical strings that the moduli integrand converges to the known continuum expression when the number of triangles goes to infinity.
Roaming moduli space using dynamical triangulations
Ambjorn, J; Budd, T
2011-01-01
In critical as well as in non-critical string theory the partition function reduces to an integral over moduli space after integration over matter fields. For non-critical string theory this moduli integrand is known for genus one surfaces. The formalism of dynamical triangulations provides us with a regularization of non-critical string theory. We show how to assign in a simple and geometrical way a moduli parameter to each triangulation. After integrating over possible matter fields we can thus construct the moduli integrand. We show numerically for $c=0$ and $c=-2$ non-critical strings that the moduli integrand converges to the known continuum expression when the number of triangles goes to infinity.
Roaming moduli space using dynamical triangulations
Ambjørn, J.; Barkley, J.; Budd, T. G.
2012-05-01
In critical as well as in non-critical string theory the partition function reduces to an integral over moduli space after integration over matter fields. For non-critical string theory this moduli integrand is known for genus one surfaces. The formalism of dynamical triangulations provides us with a regularization of non-critical string theory. We show how to assign in a simple and geometrical way a moduli parameter to each triangulation. After integrating over possible matter fields we can thus construct the moduli integrand. We show numerically for c=0 and c=-2 non-critical strings that the moduli integrand converges to the known continuum expression when the number of triangles goes to infinity.
Dynamics and causality constraints
The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Causality in field theory are kinematical constraints dynamically implemented via solutions of the field equation, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away with deep implications to the nature of physicals interactions. (author)
Dynamics and causality constraints
De Souza, M M
2000-01-01
The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Local causality are kinematical constraints dynamically implemented via solutions of the field equations, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away and implies on deep implications to the nature of physical interactions.
Arrighi, Pablo
2012-01-01
We generalize the theory of Cellular Automata to arbitrary, time-varying graphs. In other words we formalize, and prove theorems about, the intuitive idea of a labelled graph which evolves in time - but under the natural constraint that information can only ever be transmitted at a bounded speed, with respect to the distance given by the graph. The notion of translation-invariance is also generalized. The definition we provide for these `causal graph dynamics' is simple and axiomatic. The theorems we provide also show that it is robust. For instance, causal graph dynamics are stable under composition and under restriction to radius one. In the finite case some fundamental facts of Cellular Automata theory carry through: causal graph dynamics admit a characterization as continuous functions and they are stable under inversion. The provided examples suggest a wide range of applications of this mathematical object, from complex systems science to theoretical physics. Keywords: Dynamical networks, Boolean network...
Rideout, D
2002-01-01
The Causal Set approach to quantum gravity asserts that spacetime, at its smallest length scale, has a discrete structure. This discrete structure takes the form of a locally finite order relation, where the order, corresponding with the macroscopic notion of spacetime causality, is taken to be a fundamental aspect of nature. After an introduction to the Causal Set approach, this thesis considers a simple toy dynamics for causal sets. Numerical simulations of the model provide evidence for the existence of a continuum limit. While studying this toy dynamics, a picture arises of how the dynamics can be generalized in such a way that the theory could hope to produce more physically realistic causal sets. By thinking in terms of a stochastic growth process, and positing some fundamental principles, we are led almost uniquely to a family of dynamical laws (stochastic processes) parameterized by a countable sequence of coupling constants. This result is quite promising in that we now know how to speak of dynamics ...
Rideout, D P
2001-01-01
The Causal Set approach to quantum gravity asserts that spacetime, at its smallest length scale, has a discrete structure. This discrete structure takes the form of a locally finite order relation, where the order, corresponding with the macroscopic notion of spacetime causality, is taken to be a fundamental aspect of nature. After an introduction to the Causal Set approach, this thesis considers a simple toy dynamics for causal sets. Numerical simulations of the model provide evidence for the existence of a continuum limit. While studying this toy dynamics, a picture arises of how the dynamics can be generalized in such a way that the theory could hope to produce more physically realistic causal sets. By thinking in terms of a stochastic growth process, and positing some fundamental principles, we are led almost uniquely to a family of dynamical laws (stochastic processes) parameterized by a countable sequence of coupling constants. This result is quite promising in that we now know how to speak of dynamics ...
Arrighi, Pablo
2016-01-01
Consider a graph having quantum systems lying at each node. Suppose that the whole thing evolves in discrete time steps, according to a global, unitary causal operator. By causal we mean that information can only propagate at a bounded speed, with respect to the distance given by the graph. Suppose, moreover, that the graph itself is subject to the evolution, and may be driven to be in a quantum superposition of graphs---in accordance to the superposition principle. We show that these unitary causal operators must decompose as a finite-depth circuit of local unitary gates. This unifies a result on Quantum Cellular Automata with another on Reversible Causal Graph Dynamics. Along the way we formalize a notion of causality which is valid in the context of quantum superpositions of time-varying graphs, and has a number of good properties. Keywords: Quantum Lattice Gas Automata, Block-representation, Curtis-Hedlund-Lyndon, No-signalling, Localizability, Quantum Gravity, Quantum Graphity, Causal Dynamical Triangula...
Exploring Euclidean Dynamical Triangulations with a Non-trivial Measure Term
Coumbe, Daniel
2014-01-01
We investigate a nonperturbative formulation of quantum gravity defined via Euclidean dynamical triangulations (EDT) with a non-trivial measure term in the path integral. We are motivated to revisit this older formulation of dynamical triangulations by hints from renormalization group approaches that gravity may be asymptotically safe and by the emergence of a semiclassical phase in causal dynamical triangulations (CDT). We study the phase diagram of this model and identify the two phases that are well known from previous work: the branched polymer phase and the collapsed phase. We verify that the order of the phase transition dividing the branched polymer phase from the collapsed phase is almost certainly first-order. The nontrivial measure term enlarges the phase diagram, allowing us to explore a region of the phase diagram that has been dubbed the crinkled region. Although the collapsed and branched polymer phases have been studied extensively in the literature, the crinkled region has not received the sam...
Critical Behavior of Dynamically Triangulated Quantum Gravity in Four Dimensions
Agishtein, M. E.; Migdal, A. A.
1992-01-01
We performed detailed study of the phase transition region in Four Dimensional Simplicial Quantum Gravity, using the dynamical triangulation approach. The phase transition between the Gravity and Antigravity phases turned out to be asymmetrical, so that we observed the scaling laws only when the Newton constant approached the critical value from perturbative side. The curvature susceptibility diverges with the scaling index $-.6$. The physical (i.e. measured with heavy particle propagation) H...
On Causality in Dynamical Systems
Harnack, Daniel
2016-01-01
Identification of causal links is fundamental for the analysis of complex systems. In dynamical systems, however, nonlinear interactions may hamper separability of subsystems which poses a challenge for attempts to determine the directions and strengths of their mutual influences. We found that asymmetric causal influences between parts of a dynamical system lead to characteristic distortions in the mappings between the attractor manifolds reconstructed from respective local observables. These distortions can be measured in a model-free, data-driven manner. This approach extends basic intuitions about cause-effect relations to deterministic dynamical systems and suggests a mathematically well defined explanation of results obtained from previous methods based on state space reconstruction.
Correlation Measure Equivalence in Dynamic Causal Structures
Gyongyosi, Laszlo
2016-01-01
We prove an equivalence transformation between the correlation measure functions of the causally-unbiased quantum gravity space and the causally-biased standard space. The theory of quantum gravity fuses the dynamic (nonfixed) causal structure of general relativity and the quantum uncertainty of quantum mechanics. In a quantum gravity space, the events are causally nonseparable and all time bias vanishes, which makes it no possible to use the standard causally-biased entropy and the correlation measure functions. Since a corrected causally-unbiased entropy function leads to an undefined, obscure mathematical structure, in our approach the correction is made in the data representation of the causally-unbiased space. We prove that the standard causally-biased entropy function with a data correction can be used to identify correlations in dynamic causal structures. As a corollary, all mathematical properties of the causally-biased correlation measure functions are preserved in the causally-unbiased space. The eq...
Ten simple rules for dynamic causal modeling.
Stephan, K.E.; Penny, W.D.; Moran, R.J.; Ouden, H.E.M. den; Daunizeau, J.; Friston, K.J.
2010-01-01
Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and
Ten simple rules for dynamic causal modeling
Stephan, K E; Penny, W.D.; Moran, R. J.; den Ouden, H.E.M.; Daunizeau, J.; Friston, K J
2010-01-01
Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to convent...
Chen, Jun; Luo, Chaomin; Krishnan, Mohan; Paulik, Mark; Tang, Yipeng
2010-01-01
An enhanced dynamic Delaunay Triangulation-based (DT) path planning approach is proposed for mobile robots to plan and navigate a path successfully in the context of the Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The Autonomous Challenge course requires the application of vision techniques since it involves path-based navigation in the presence of a tightly clustered obstacle field. Course artifacts such as switchbacks, ramps, dashed lane lines, trap etc. are present which could turn the robot around or cause it to exit the lane. The main contribution of this work is a navigation scheme based on dynamic Delaunay Triangulation (DDT) that is heuristically enhanced on the basis of a sense of general lane direction. The latter is computed through a "GPS (Global Positioning System) tail" vector obtained from the immediate path history of the robot. Using processed data from a LADAR, camera, compass and GPS unit, a composite local map containing both obstacles and lane line segments is built up and Delaunay Triangulation is continuously run to plan a path. This path is heuristically corrected, when necessary, by taking into account the "GPS tail" . With the enhancement of the Delaunay Triangulation by using the "GPS tail", goal selection is successfully achieved in a majority of situations. The robot appears to follow a very stable path while navigating through switchbacks and dashed lane line situations. The proposed enhanced path planning and GPS tail technique has been successfully demonstrated in a Player/Stage simulation environment. In addition, tests on an actual course are very promising and reveal the potential for stable forward navigation.
We propose a new method which analyzes the dynamical triangulation from the viewpoint of the non-critical string field theory. By using the transfer matrix formalism, we construct the non-critical string field theory (including c > 1 cases) at the discrete level. For pure quantum gravity, we succeed in taking the continuum limit and obtain the c = 0 non-critical string field theory at the continuous level. We also study about the universality of the non-critical string field theory. (author)
Summing Feynman graphs by Monte-Carlo: Planar φ3-theory and dynamically triangulated random surfaces
New combinatorial identities are suggested relating the ratio of (n-1)-th and n-th orders of (planar) perturbation expansion for any quantity to some average over the ensemble of all planar graphs of the n-th order. These identities are used for Monte-Carlo calculation of critical exponents γstr (string susceptibility) in planar φ3-theory and in the dynamically triangulated random surface (DTRS) model near the convergence circle for various dimensions. In the solvable case D = 1 the exact critical properties of the theory are reproduced numerically. (orig.)
Summing Feynman graphs by Monte Carlo: Planar φ3-theory and dynamically triangulated random surfaces
New combinatorial identities are suggested relating the ratio of (n-1)th and nth orders of (planar) perturbation expansion for any quantity to some average over the ensemble of all planar graphs of the nth order. These identities are used for Monte Carlo calculation of critical exponents γstr (string susceptibility) in planar φ3-theory and in the dynamically triangulated random surface (DTRS) model near the convergence circle for various dimensions. In the solvable case D=1 the exact critical properties of the theory are reproduced numerically. (orig.)
Causal random geometry from stochastic quantization
Ambjørn, Jan; Loll, R.; Westra, W.; Zohren, S.
2010-01-01
in this short note we review a recently found formulation of two-dimensional causal quantum gravity defined through Causal Dynamical Triangulations and stochastic quantization. This procedure enables one to extract the nonperturbative quantum Hamiltonian of the random surface model including the...
Dynamic causal models and autopoietic systems.
David, Olivier
2007-01-01
Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated. PMID:18575681
Simulations of four-dimensional simplicial quantum gravity as dynamical triangulation
Agishtein, M.E.; Migdal, A.A. (Program in Applied and Computational Mathematics, Fine Hall, Princeton Univ., Princeton, NJ (US))
1992-04-20
In this paper, Four-Dimensional Simplicial Quantum Gravity is simulated using the dynamical triangulation approach. The authors studied simplicial manifolds of spherical topology and found the critical line for the cosmological constant as a function of the gravitational one, separating the phases of opened and closed Universe. When the bare cosmological constant approaches this line from above, the four-volume grows: the authors reached about 5 {times} 10{sup 4} simplexes, which proved to be sufficient for the statistical limit of infinite volume. However, for the genuine continuum theory of gravity, the parameters of the lattice model should be further adjusted to reach the second order phase transition point, where the correlation length grows to infinity. The authors varied the gravitational constant, and they found the first order phase transition, similar to the one found in three-dimensional model, except in 4D the fluctuations are rather large at the transition point, so that this is close to the second order phase transition. The average curvature in cutoff units is large and positive in one phase (gravity), and small negative in another (antigravity). The authors studied the fractal geometry of both phases, using the heavy particle propagator to define the geodesic map, as well as with the old approach using the shortest lattice paths.
Simulations of four-dimensional simplicial quantum gravity as dynamical triangulation
In this paper, Four-Dimensional Simplicial Quantum Gravity is simulated using the dynamical triangulation approach. The authors studied simplicial manifolds of spherical topology and found the critical line for the cosmological constant as a function of the gravitational one, separating the phases of opened and closed Universe. When the bare cosmological constant approaches this line from above, the four-volume grows: the authors reached about 5 x 104 simplexes, which proved to be sufficient for the statistical limit of infinite volume. However, for the genuine continuum theory of gravity, the parameters of the lattice model should be further adjusted to reach the second order phase transition point, where the correlation length grows to infinity. The authors varied the gravitational constant, and they found the first order phase transition, similar to the one found in three-dimensional model, except in 4D the fluctuations are rather large at the transition point, so that this is close to the second order phase transition. The average curvature in cutoff units is large and positive in one phase (gravity), and small negative in another (antigravity). The authors studied the fractal geometry of both phases, using the heavy particle propagator to define the geodesic map, as well as with the old approach using the shortest lattice paths
Pearl, Judea
2000-03-01
Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.
CAUSAL DYNAMICAL TRIANGULATIONS AND THE SEARCH FOR A THEORY OF QUANTUM GRAVITY
Ambjørn, Jan; Görlich, Andrzej; Jurkiewicz, J.;
2013-01-01
High Energy Physics - Theory (hep-th); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Lattice (hep-lat)......High Energy Physics - Theory (hep-th); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Lattice (hep-lat)...
Dynamical Causal Modeling from a Quantum Dynamical Perspective
Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called ''Quantum Harmonical Form (QHF)''. QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, this limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.
Bell, Mark C.
2016-01-01
We give a new algorithm to simplify a given triangulation with respect to a given curve. The simplification uses flips together with powers of Dehn twists in order to complete in polynomial time in the bit-size of the curve.
Does stability of relativistic dissipative fluid dynamics imply causality?
We investigate the causality and stability of relativistic dissipative fluid dynamics in the absence of conserved charges. We perform a linear stability analysis in the rest frame of the fluid and find that the equations of relativistic dissipative fluid dynamics are always stable. We then perform a linear stability analysis in a Lorentz-boosted frame. Provided that the ratio of the relaxation time for the shear stress tensor τπ to the sound attenuation length Γs=4η/3(ε+P) fulfills a certain asymptotic causality condition, the equations of motion give rise to stable solutions. Although the group velocity associated with perturbations may exceed the velocity of light in a certain finite range of wave numbers, we demonstrate that this does not violate causality, as long as the asymptotic causality condition is fulfilled. Finally, we compute the characteristic velocities and show that they remain below the velocity of light if the ratio τπ/Γs fulfills the asymptotic causality condition.
Bernard N. Iyke
2014-06-01
Full Text Available This paper examines the dynamic causal relationship between electricity consumption and economic growth in Ghana within a trivariate ARDL framework, for the period 1971–2012.The paper obviates the variable omission bias, and the use of cross-sectional techniques that characterise most existing studies. The results show that there is a distinct causal flow from economic growth to electricity consumption: both in the short run and in the long run. This finding supports the growth-led electricity consumption hypothesis, as documented in the literature. The paper urges policymakers in Ghana to resort to alternative sources of electric power generation, in order to reduce any future pressures on the current sources of electricity production. Appropriate monetary policies must also be put in place, in order to accommodate potential inflation hikes stemming from excessive demands for electricity in the near future.
Zou, Bin; Wang, Debby D.; Ma, Lichun; Chen, Lijiang; Yan, Hong
2016-05-01
Epidermal growth factor receptor (EGFR) mutation is a pathogenic factor of non-small cell lung cancer (NSCLC). Tyrosine kinase inhibitors (TKIs), such as gefitinib, are widely used in NSCLC treatment. In this work, we investigated the relationship between the number of EGFR residues connected with gefitinib and the response level for each EGFR mutation type. Three-dimensional trimmed Delaunay triangulation was applied to construct connections between EGFR residues and gefitinib atoms. Through molecular dynamics (MD) simulations, we discovered that when the number of EGFR residues connected with gefitinib increases, the response level of the corresponding EGFR mutation tends to descend.
Variational multi-fluid dynamics and causal heat conductivity
Andersson, N.; Comer, G. L.
2009-01-01
We discuss heat conductivity from the point of view of a variational multi-fluid model, treating entropy as a dynamical entity. We demonstrate that a two-fluid model with a massive fluid component and a massless entropy can reproduce a number of key results from extended irreversible thermodynamics. In particular, we show that the entropy entrainment is intimately linked to the thermal relaxation time that is required to make heat propagation in solids causal. We also discuss non-local terms ...
Argyris Arnellos
2005-02-01
Full Text Available Initially, the analysis and development of adaptive artificial systems has been based in metaphors taken from philosophical schools as well as the disciplines of biology and cognitive science. So far, the dominant approaches exhibit many advantages in specific domains of application but there all have a certain drawback, which is their inability to produce an artificial system which will be able to internally ground its representations so as to use them to produce newer, more developed ones. The respective frameworks are studied in terms of this inability and it is concluded that the problem is traced in the purely causal treatment, function and creation of the notion of representation, wherever it is used. In the case of purely dynamic systems, where the representations seem not to be very useful, it is proposed that the incorporation of a special non-causal kind of representations would give a framework which seems promising in realizing real adaptation. The relevant architecture is analyzed and discussed mainly in terms of its functionality and its contribution to the integration of pragmatic meaning aspects in an artificial system's interaction.
Zheleznyakova, A. L.
2015-05-01
A new computational approach for automated triangulation of Computer-Aided Design (CAD) surface models, applicable to various CFD (Computational Fluid Dynamics) problems of practical interest is proposed. The complex shaped product configurations are represented by a set of Non-Uniform Rational B-Splines (NURBS) surface patches. The suggested technique is based on the molecular dynamics method. The main idea of the approach is that the mesh nodes are considered as similarly charged interacting particles which move within the region to be meshed under the influence of internal (such as particle-particle interaction forces) and external forces as well as optional additional forces. Moreover, the particles experience a medium resistance due to which the system comes to equilibrium within a relatively short period of time. The proposed 3D surface mesh generation algorithm uses a parametric NURBS representation as initial definition of the domain boundary. This method first distributes the interacting nodes into optimal locations in the parametric domain of the NURBS surface patch using molecular dynamics simulation. Then, the well-shaped triangles can be created after connecting the nodes by Delaunay triangulation. Finally, the mapping from parametric space to 3D physical space is performed. Since the presented interactive algorithm allows to control the distance between a pair of nodes depending on the curvature of the NURBS surface, the method generates high quality triangular mesh. The algorithm enables to produce uniform mesh, as well as anisotropic adaptive mesh with refinement in the large gradient regions. The mesh generation approach has the abilities to preserve the representation accuracy of the input geometry model, create a close relationship between geometry modeling and grid generation process, be automated to a large degree. Some examples are considered in order to illustrate the method's ability to generate a surface mesh for a complicated CAD model.
Emergence of a 4D world from causal quantum gravity
Ambjørn, J.; Jurkiewicz, J.(Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 11, Krakow, PL 30-348, Poland); Loll, R
2006-01-01
Causal Dynamical Triangulations in four dimensions provide a background- independent definition of the sum over geometries in nonperturbative quantum gravity, with a positive cosmological constant. We present evidence that a macro- scopic four-dimensional world emerges from this theory dynamically.
Dynamical symmetries and causality in non-equilibrium phase transitions
Henkel, Malte
2015-01-01
Dynamical symmetries are of considerable importance in elucidating the complex behaviour of strongly interacting systems with many degrees of freedom. Paradigmatic examples are cooperative phenomena as they arise in phase transitions, where conformal invariance has led to enormous progress in equilibrium phase transitions, especially in two dimensions. Non-equilibrium phase transitions can arise in much larger portions of the parameter space than equilibrium phase transitions. The state of the art of recent attempts to generalise conformal invariance to a new generic symmetry, taking into account the different scaling behaviour of space and time, will be reviewed. Particular attention will be given to the causality properties as they follow for co-variant $n$-point functions. These are important for the physical identification of n-point functions as responses or correlators.
Dynamical Symmetries and Causality in Non-Equilibrium Phase Transitions
Malte Henkel
2015-11-01
Full Text Available Dynamical symmetries are of considerable importance in elucidating the complex behaviour of strongly interacting systems with many degrees of freedom. Paradigmatic examples are cooperative phenomena as they arise in phase transitions, where conformal invariance has led to enormous progress in equilibrium phase transitions, especially in two dimensions. Non-equilibrium phase transitions can arise in much larger portions of the parameter space than equilibrium phase transitions. The state of the art of recent attempts to generalise conformal invariance to a new generic symmetry, taking into account the different scaling behaviour of space and time, will be reviewed. Particular attention will be given to the causality properties as they follow for co-variant n-point functions. These are important for the physical identification of n-point functions as responses or correlators.
OPTIMAL DELAUNAY TRIANGULATIONS
Long Chen; Jin-chao Xu
2004-01-01
The Delaunay triangulation, in both classic and more generalized sense, is studied in this paper for minimizing the linear interpolation error (measure in Lp-norm) for a given function. The classic Delaunay triangulation can then be characterized as an optimal triangulation that minimizes the interpolation error for the isotropic function ‖x‖2 among all the triangulations with a given set of vertices. For a more general function, a functiondependent Delaunay triangulation is then defined to be an optimal triangulation that minimizes the interpolation error for this .function and its construction can be obtained by a simple lifting and projection procedure.The optimal Delaunay triangulation is the one that minimizes the interpolation error among all triangulations with the same number of vertices, i.e. the distribution of vertices are optimized in order to minimize the interpolation error. Such a function-dependent optimal Delaunay triangulation is proved to exist for any given convex continuous function.On an optimal Delaunay triangulation associated with f, it is proved that ▽f at the interior vertices can be exactly recovered by the function values on its neighboring vertices.Since the optimal Delaunay triangulation is difficult to obtain in practice, the concept of nearly optimal triangulation is introduced and two sufficient conditions are presented for a triangulation to be nearly optimal.
When two become one: the limits of causality analysis of brain dynamics.
Daniel Chicharro
Full Text Available Biological systems often consist of multiple interacting subsystems, the brain being a prominent example. To understand the functions of such systems it is important to analyze if and how the subsystems interact and to describe the effect of these interactions. In this work we investigate the extent to which the cause-and-effect framework is applicable to such interacting subsystems. We base our work on a standard notion of causal effects and define a new concept called natural causal effect. This new concept takes into account that when studying interactions in biological systems, one is often not interested in the effect of perturbations that alter the dynamics. The interest is instead in how the causal connections participate in the generation of the observed natural dynamics. We identify the constraints on the structure of the causal connections that determine the existence of natural causal effects. In particular, we show that the influence of the causal connections on the natural dynamics of the system often cannot be analyzed in terms of the causal effect of one subsystem on another. Only when the causing subsystem is autonomous with respect to the rest can this interpretation be made. We note that subsystems in the brain are often bidirectionally connected, which means that interactions rarely should be quantified in terms of cause-and-effect. We furthermore introduce a framework for how natural causal effects can be characterized when they exist. Our work also has important consequences for the interpretation of other approaches commonly applied to study causality in the brain. Specifically, we discuss how the notion of natural causal effects can be combined with Granger causality and Dynamic Causal Modeling (DCM. Our results are generic and the concept of natural causal effects is relevant in all areas where the effects of interactions between subsystems are of interest.
The causal structure of dynamical charged black holes
Hong, Sungwook E; Hwang, Dong-il; Stewart, Ewan D; Yeom, Dong-han, E-mail: eostm@muon.kaist.ac.k, E-mail: enotsae@gmail.co, E-mail: innocent@muon.kaist.ac.k [Department of Physics, KAIST, Daejeon 305-701 (Korea, Republic of)
2010-02-21
We study the causal structure of dynamical charged black holes, with a sufficient number of massless fields, using numerical simulations. Neglecting Hawking radiation, the inner horizon is a null Cauchy horizon and a curvature singularity due to mass inflation. When we include Hawking radiation, the inner horizon becomes space-like and is separated from the Cauchy horizon, which is parallel to the out-going null direction. Since a charged black hole must eventually transit to a neutral black hole, we studied the neutralization of the black hole and observed that the inner horizon evolves into a space-like singularity, generating a Cauchy horizon which is parallel to the in-going null direction. Since the mass function is finite around the inner horizon, the inner horizon is regular and penetrable in a general relativistic sense. However, since the curvature functions become trans-Planckian, we cannot say more about the region beyond the inner horizon, and it is natural to say that there is a 'physical' space-like singularity. However, if we assume an exponentially large number of massless scalar fields, our results can be extended beyond the inner horizon. In this case, strong cosmic censorship and black hole complementarity can be violated.
Imposing causality on a matrix model
We introduce a new matrix model that describes Causal Dynamical Triangulations (CDT) in two dimensions. In order to do so, we introduce a new, simpler definition of 2D CDT and show it to be equivalent to the old one. The model makes use of ideas from dually weighted matrix models, combined with multi-matrix models, and can be studied by the method of character expansion.
A general solution for classical sequential growth dynamics of Causal Sets
Varadarajan, Madhavan; Rideout, David
2005-01-01
A classical precursor to a full quantum dynamics for causal sets has been forumlated in terms of a stochastic sequential growth process in which the elements of the causal set arise in a sort of accretion process. The transition probabilities of the Markov growth process satisfy certain physical requirements of causality and general covariance, and the generic solution with all transition probabilities non-zero has been found. Here we remove the assumption of non-zero probabilities, define a ...
Causality analysis in business performance measurement system using system dynamics methodology
Yusof, Zainuridah; Yusoff, Wan Fadzilah Wan; Maarof, Faridah
2014-07-01
One of the main components of the Balanced Scorecard (BSC) that differentiates it from any other performance measurement system (PMS) is the Strategy Map with its unidirectional causality feature. Despite its apparent popularity, criticisms on the causality have been rigorously discussed by earlier researchers. In seeking empirical evidence of causality, propositions based on the service profit chain theory were developed and tested using the econometrics analysis, Granger causality test on the 45 data points. However, the insufficiency of well-established causality models was found as only 40% of the causal linkages were supported by the data. Expert knowledge was suggested to be used in the situations of insufficiency of historical data. The Delphi method was selected and conducted in obtaining the consensus of the causality existence among the 15 selected expert persons by utilizing 3 rounds of questionnaires. Study revealed that only 20% of the propositions were not supported. The existences of bidirectional causality which demonstrate significant dynamic environmental complexity through interaction among measures were obtained from both methods. With that, a computer modeling and simulation using System Dynamics (SD) methodology was develop as an experimental platform to identify how policies impacting the business performance in such environments. The reproduction, sensitivity and extreme condition tests were conducted onto developed SD model to ensure their capability in mimic the reality, robustness and validity for causality analysis platform. This study applied a theoretical service management model within the BSC domain to a practical situation using SD methodology where very limited work has been done.
Denzin, Norman K.
2012-01-01
The author's thesis is simple and direct. Those in the mixed methods qualitative inquiry community need a new story line, one that does not confuse pragmatism for triangulation, and triangulation for mixed methods research (MMR). A different third way is required, one that inspires generative politics and dialogic democracy and helps shape…
The connected brain: Causality, models and intrinsic dynamics
A razi; Friston, K.
2016-01-01
Recently, there have been several concerted international efforts - the BRAIN initiative, European Human Brain Project and the Human Connectome Project, to name a few - that hope to revolutionize our understanding of the connected brain. Over the past two decades, functional neuroimaging has emerged as the predominant technique in systems neuroscience. This is foreshadowed by an ever increasing number of publications on functional connectivity, causal modeling, connectomics, and multivariate ...
Taming the cosmological constant in 2D causal quantum gravity with topology change
Loll, R.; Westra, W.; Zohren, S.
2006-01-01
As shown in previous work, there is a well-defined nonperturbative gravitational path integral including an explicit sum over topologies in the setting of Causal Dy- namical Triangulations in two dimensions. In this paper we derive a complete ana- lytical solution of the quantum continuum dynamics o
Temporal Granger causality and the dynamics examination on the tourism-growth nexus in Malaysia
Tang, Chor Foon
2011-01-01
This study applied the cointegration, error-correction modelling and persistence profile to analyse the dynamic relationship between real tourism receipts, real income and real exchange rate in Malaysia. This study covers the annual sample period from 1974 to 2009. This study finds that the variables are cointegrated. In the short run, this study finds that neutrality causality between real tourism receipts and real income, while they are bi-directional Granger causality in the long run. Neve...
Dynamic causal models of neural system dynamics: current state and future extensions
Klaas E Stephan; Lee M Harrison; Stefan J Kiebel; Olivier David; Will D Penny; Karl J Friston
2007-01-01
Complex processes resulting from interaction of multiple elements can rarely be understood by analytical scientific approaches alone; additional, mathematical models of system dynamics are required. This insight, which disciplines like physics have embraced for a long time already, is gradually gaining importance in the study of cognitive processes by functional neuroimaging. In this field, causal mechanisms in neural systems are described in terms of effective connectivity. Recently, dynamic causal modelling (DCM) was introduced as a generic method to estimate effective connectivity from neuroimaging data in a Bayesian fashion. One of the key advantages of DCM over previous methods is that it distinguishes between neural state equations and modality-specific forward models that translate neural activity into a measured signal. Another strength is its natural relation to Bayesian model selection (BMS) procedures. In this article, we review the conceptual and mathematical basis of DCM and its implementation for functional magnetic resonance imaging data and event-related potentials. After introducing the application of BMS in the context of DCM, we conclude with an outlook to future extensions of DCM. These extensions are guided by the long-term goal of using dynamic system models for pharmacological and clinical applications, particularly with regard to synaptic plasticity.
Triangulated categories (AM-148)
Neeman, Amnon
2014-01-01
The first two chapters of this book offer a modern, self-contained exposition of the elementary theory of triangulated categories and their quotients. The simple, elegant presentation of these known results makes these chapters eminently suitable as a text for graduate students. The remainder of the book is devoted to new research, providing, among other material, some remarkable improvements on Brown''s classical representability theorem. In addition, the author introduces a class of triangulated categories""--the ""well generated triangulated categories""--and studies their properties. This
Who Is the Dynamic Duo? How Infants Learn about the Identity of Objects in a Causal Chain
Rakison, David H.; Smith, Gabriel Tobin; Ali, Areej
2016-01-01
Four experiments investigated infants' and adults' knowledge of the identity of objects in a causal sequence of events. In Experiments 1 and 2, 18- and 22-month-olds in the visual habituation procedure were shown a 3-step causal chain event in which the relation between an object's part (dynamic or static) and its causal role was either consistent…
Causal wave mechanics and the advent of complexity; 1, dynamic multivaluedness
Kirilyuk, A P
1995-01-01
Two major deviations from causality in the existing formulation of quantum mechanics, related respectively to quantum chaos and indeterminate wave reduction, are interpreted within the same universal analysis of complexity of dynamical system behaviour. The analysis involves a new paradigm for the formal description of such behaviour, the principle of dynamic multivaluedness, and the ensuing physical concept of the fundamental dynamic uncertainty. The presentation is divided into five parts. The first three parts deal with deterministic randomness in Hamiltonian quantum systems as the basic case of dynamical chaos. In the last two parts a causal solution to the problem of quantum indeterminacy and wave reduction is proposed. Part I introduces the method of the effective dynamical functions as a generalisation of the optical potential formalism. The method provides a reformulation of the Schr\\"odinger equation revealing the multivaluedness of the effective Hamiltonian, i. e. its natural splitting into many bra...
A general solution for classical sequential growth dynamics of Causal Sets
Varadarajan, M; Rideout, David; Varadarajan, Madhavan
2006-01-01
A classical precursor to a full quantum dynamics for causal sets has been forumlated in terms of a stochastic sequential growth process in which the elements of the causal set arise in a sort of accretion process. The transition probabilities of the Markov growth process satisfy certain physical requirements of causality and general covariance, and the generic solution with all transition probabilities non-zero has been found. Here we remove the assumption of non-zero probabilities, define a reasonable extension of the physical requirements to cover the case of vanishing probabilities, and find the completely general solution to these physical conditions. The resulting family of growth processes has an interesting structure reminiscent of an ``infinite tower of turtles'' cosmology.
Who is the dynamic duo? How infants learn about the identity of objects in a causal chain.
Rakison, David H; Smith, Gabriel Tobin; Ali, Areej
2016-03-01
Four experiments investigated infants' and adults' knowledge of the identity of objects in a causal sequence of events. In Experiments 1 and 2, 18- and 22-month-olds in the visual habituation procedure were shown a 3-step causal chain event in which the relation between an object's part (dynamic or static) and its causal role was either consistent or inconsistent with the real-world. In Experiment 3, 22-month-olds were tested with a delayed launching causal chain in which the second object, rather than the first, was the agent of the outcome. In Experiment 4, adults were shown the same events and were asked to judge whether the first or second object in the causal chain was animate or inanimate. Experiments 1 and 2 revealed that 18-month-olds were unconstrained in the part-causal role relations they would encode, but 22-month-olds learned only those relations that were consistent with the real-world. Experiment 3 showed that 22-month-olds expect the second object in a delayed launching sequence to possess a dynamic, moving part. Experiment 4 showed that adults expect the first object of a causal chain to be animate and the second object to be inanimate. The results are discussed with regard to the developmental timetable for causal learning and the mechanisms for early concept acquisition. (PsycINFO Database Record PMID:26689760
Inferring causal metabolic signals that regulate the dynamic TORC1-dependent transcriptome
Oliveira, Ana Paula; Dimopoulos, Sotiris; Busetto, Alberto Giovanni; Christen, Stefan; Dechant, Reinhard; Falter, Laura; Haghir Chehreghani, Morteza; Jozefczuk, Szymon; Ludwig, Christina; Rudroff, Florian; Schulz, Juliane Caroline; González, Asier; Soulard, Alexandre; Stracka, Daniele; Aebersold, Ruedi; Buhmann, Joachim M; Hall, Michael N; Peter, Matthias; Sauer, Uwe; Stelling, Jörg
2015-01-01
Cells react to nutritional cues in changing environments via the integrated action of signaling, transcriptional, and metabolic networks. Mechanistic insight into signaling processes is often complicated because ubiquitous feedback loops obscure causal relationships. Consequently, the endogenous inputs of many nutrient signaling pathways remain unknown. Recent advances for system-wide experimental data generation have facilitated the quantification of signaling systems, but the integration of multi-level dynamic data remains challenging. Here, we co-designed dynamic experiments and a probabilistic, model-based method to infer causal relationships between metabolism, signaling, and gene regulation. We analyzed the dynamic regulation of nitrogen metabolism by the target of rapamycin complex 1 (TORC1) pathway in budding yeast. Dynamic transcriptomic, proteomic, and metabolomic measurements along shifts in nitrogen quality yielded a consistent dataset that demonstrated extensive re-wiring of cellular networks during adaptation. Our inference method identified putative downstream targets of TORC1 and putative metabolic inputs of TORC1, including the hypothesized glutamine signal. The work provides a basis for further mechanistic studies of nitrogen metabolism and a general computational framework to study cellular processes. PMID:25888284
Topology Change and the Emergence of Geometry in Two Dimensional Causal Quantum Gravity
Westra, Willem
2008-01-01
In this thesis we analyze a very simple model of two dimensional quantum gravity based on causal dynamical triangulations (CDT). We present an exactly solvable model which indicates that it is possible to incorporate spatial topology changes in the nonperturbative path integral. It is shown that if the change in spatial topology is accompanied by a coupling constant it is possible to evaluate the path integral to all orders in the coupling and that the result can be viewed as a hybrid between causal and Euclidian dynamical triangulation. The second model we describe shows how a classical geometry with constant negative curvature emerges naturally from a path integral over noncompact manifolds. No initial singularity is present, hence the quantum geometry is naturally compatible with the Hartle Hawking boundary condition. Furthermore, we demonstrate that under certain conditions the quantum fluctuations are small! To conclude, we treat the problem of spacetime topology change. Although we are not able to compl...
Differentiation on spaces of triangulations and optimized triangulations
Magnot, Jean-Pierre
2016-01-01
We describe a smooth structure, called Fr\\"olicher space, on CW complexes and spaces of triangulations. This structure enables differential methods for e.g. minimization of functionnals. As an application, we exhibit how an optimized triangulation can be obtained in order to solve a standard PDE.
Veering triangulations admit strict angle structures
Hodgson, Craig D; Segerman, Henry; Tillmann, Stephan
2010-01-01
Agol recently introduced the concept of a veering taut triangulation, which is a taut triangulation with some extra combinatorial structure. We define the weaker notion of a "veering triangulation" and use it to show that all veering triangulations admit strict angle structures. We also answer a question of Agol, giving an example of a veering taut triangulation that is not layered.
Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI
Koush, Yury; Rosa, Maria Joao; Robineau, Fabien; Heinen, Klaartje; Rieger, Sebastian Walter; Weiskopf, Nikolaus; Vuilleumier, Patrik; Van De Ville, Dimitri; Scharnowski, Frank
2013-01-01
Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to pr...
Lymbouridou, Chrystalla; Sevastidou, Alexia
2003-01-01
This study investigated the effectiveness of a computational model (made with Stagecast Creator1) in teaching forms of causality in system dynamics. Systems causality forms were examined within the context of food web perturbations. The research sample included two equivalent sixth grade classes from the same elementary school in Cyprus. The same teacher taught students in both classes a unit on ecosystems that was completed in two lessons (4 class periods). Students in the experimental group...
Fundamental triangulation networks in Denmark
Borre, Kai
2014-01-01
Academy of Sciences and Letters initiated a mapping project which should be based on the principle of triangulation. Eventually 24 maps were printed in varying scales, predominantly in 1:120 000. The last map was engraved in 1842. The Danish GradeMeasurement initiated remeasurements and redesign of the...... fundamental triangulation network. This network served scientific as well as cartographic purposes in more than a century. Only in the 1960s all triangulation sides were measured electronically. A combined least-squares adjustment followed in the 1970s...
Hu, Zhenghui; Ni, Pengyu; Wan, Qun; Zhang, Yan; Shi, Pengcheng; Lin, Qiang
2016-01-01
Changes in BOLD signals are sensitive to the regional blood content associated with the vasculature, which is known as V0 in hemodynamic models. In previous studies involving dynamic causal modeling (DCM) which embodies the hemodynamic model to invert the functional magnetic resonance imaging signals into neuronal activity, V0 was arbitrarily set to a physiolog-ically plausible value to overcome the ill-posedness of the inverse problem. It is interesting to investigate how the V0 value influences DCM. In this study we addressed this issue by using both synthetic and real experiments. The results show that the ability of DCM analysis to reveal information about brain causality depends critically on the assumed V0 value used in the analysis procedure. The choice of V0 value not only directly affects the strength of system connections, but more importantly also affects the inferences about the network architecture. Our analyses speak to a possible refinement of how the hemody-namic process is parameterized (i.e., by making V0 a free parameter); however, the conditional dependencies induced by a more complex model may create more problems than they solve. Obtaining more realistic V0 information in DCM can improve the identifiability of the system and would provide more reliable inferences about the properties of brain connectivity. PMID:27389074
Systemic risk and causality dynamics of the world international shipping market
Zhang, Xin; Podobnik, Boris; Kenett, Dror Y.; Eugene Stanley, H.
2014-12-01
Various studies have reported that many economic systems have been exhibiting an increase in the correlation between different market sectors, a factor that exacerbates the level of systemic risk. We measure this systemic risk of three major world shipping markets, (i) the new ship market, (ii) the second-hand ship market, and (iii) the freight market, as well as the shipping stock market. Based on correlation networks during three time periods, that prior to the financial crisis, during the crisis, and after the crisis, minimal spanning trees (MSTs) and hierarchical trees (HTs) both exhibit complex dynamics, i.e., different market sectors tend to be more closely linked during financial crisis. Brownian distance correlation and Granger causality test both can be used to explore the directional interconnectedness of market sectors, while Brownian distance correlation captures more dependent relationships, which are not observed in the Granger causality test. These two measures can also identify and quantify market regression periods, implying that they contain predictive power for the current crisis.
Lindstrom, P
2009-12-23
We describe a simple and efficient algorithm for two-view triangulation of 3D points from approximate 2D matches based on minimizing the L2 reprojection error. Our iterative algorithm improves on the one by Kanatani et al. by ensuring that in each iteration the epipolar constraint is satisfied. In the case where the two cameras are pointed in the same direction, the method provably converges to an optimal solution in exactly two iterations. For more general camera poses, two iterations are sufficient to achieve convergence to machine precision, which we exploit to devise a fast, non-iterative method. The resulting algorithm amounts to little more than solving a quadratic equation, and involves a fixed, small number of simple matrixvector operations and no conditional branches. We demonstrate that the method computes solutions that agree to very high precision with those of Hartley and Sturm's original polynomial method, though achieves higher numerical stability and 1-4 orders of magnitude greater speed.
Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects
F. Claveau (Francois)
2012-01-01
textabstractEconomists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding of how causal reasoning proceeds in economics. By using the research on the causes of unemployment as a case s
Entropy of unimodular Lattice Triangulations
Knauf, Johannes F; Mecke, Klaus
2014-01-01
Triangulations are important objects of study in combinatorics, finite element simulations and quantum gravity, where its entropy is crucial for many physical properties. Due to their inherent complex topological structure even the number of possible triangulations is unknown for large systems. We present a novel algorithm for an approximate enumeration which is based on calculations of the density of states using the Wang-Landau flat histogram sampling. For triangulations on two-dimensional integer lattices we achive excellent agreement with known exact numbers of small triangulations as well as an improvement of analytical calculated asymptotics. The entropy density is $C=2.196(3)$ consistent with rigorous upper and lower bounds. The presented numerical scheme can easily be applied to other counting and optimization problems.
Frisch, Mathias
2014-01-01
Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.
Villacorta-Atienza, José Antonio; Velarde, Manuel G; Makarov, Valeri A
2010-10-01
Animals for survival in complex, time-evolving environments can estimate in a "single parallel run" the fitness of different alternatives. Understanding of how the brain makes an effective compact internal representation (CIR) of such dynamic situations is a challenging problem. We propose an artificial neural network capable of creating CIRs of dynamic situations describing the behavior of a mobile agent in an environment with moving obstacles. The network exploits in a mental world model the principle of causality, which enables reduction of the time-dependent structure of real situations to compact static patterns. It is achieved through two concurrent processes. First, a wavefront representing the agent's virtual present interacts with mobile and immobile obstacles forming static effective obstacles in the network space. The dynamics of the corresponding neurons in the virtual past is frozen. Then the diffusion-like process relaxes the remaining neurons to a stable steady state, i.e., a CIR is given by a single point in the multidimensional phase space. Such CIRs can be unfolded into real space for execution of motor actions, which allows a flexible task-dependent path planning in realistic time-evolving environments. Besides, the proposed network can also work as a part of "autonomous thinking", i.e., some mental situations can be supplied for evaluation without direct motor execution. Finally we hypothesize the existence of a specific neuronal population responsible for detection of possible time-space coincidences of the animal and moving obstacles. PMID:20589508
Ryali, Srikanth; Shih, Yen-Yu Ian; Chen, Tianwen; Kochalka, John; Albaugh, Daniel; Fang, Zhongnan; Supekar, Kaustubh; Lee, Jin Hyung; Menon, Vinod
2016-05-15
State-space multivariate dynamical systems (MDS) (Ryali et al. 2011) and other causal estimation models are being increasingly used to identify directed functional interactions between brain regions. However, the validity and accuracy of such methods are poorly understood. Performance evaluation based on computer simulations of small artificial causal networks can address this problem to some extent, but they often involve simplifying assumptions that reduce biological validity of the resulting data. Here, we use a novel approach taking advantage of recently developed optogenetic fMRI (ofMRI) techniques to selectively stimulate brain regions while simultaneously recording high-resolution whole-brain fMRI data. ofMRI allows for a more direct investigation of causal influences from the stimulated site to brain regions activated downstream and is therefore ideal for evaluating causal estimation methods in vivo. We used ofMRI to investigate whether MDS models for fMRI can accurately estimate causal functional interactions between brain regions. Two cohorts of ofMRI data were acquired, one at Stanford University and the University of California Los Angeles (Cohort 1) and the other at the University of North Carolina Chapel Hill (Cohort 2). In each cohort, optical stimulation was delivered to the right primary motor cortex (M1). General linear model analysis revealed prominent downstream thalamic activation in Cohort 1, and caudate-putamen (CPu) activation in Cohort 2. MDS accurately estimated causal interactions from M1 to thalamus and from M1 to CPu in Cohort 1 and Cohort 2, respectively. As predicted, no causal influences were found in the reverse direction. Additional control analyses demonstrated the specificity of causal interactions between stimulated and target sites. Our findings suggest that MDS state-space models can accurately and reliably estimate causal interactions in ofMRI data and further validate their use for estimating causal interactions in f
Eric Delattre; Richard Moussa
2015-01-01
In order to assess causality between binary economic outcomes, we consider the estimation of a bivariate dynamic probit model on panel data that has the particulary to account the initial conditions of the dynamic process. Due to the untractable form of the likelihood function that is a two dimensions integral, we use an approximation method: the adaptative Gauss-Hermite quadrature method as proposed by Liu and Pierce (1994). For the accuracy of the method and to reduce computing time, we der...
Dynamic causal modeling of touch-evoked potentials in the rubber hand illusion.
Zeller, Daniel; Friston, Karl J; Classen, Joseph
2016-09-01
The neural substrate of bodily ownership can be disclosed by the rubber hand illusion (RHI); namely, the illusory self-attribution of an artificial hand that is induced by synchronous tactile stimulation of the subject's hand that is hidden from view. Previous studies have pointed to the premotor cortex (PMC) as a pivotal area in such illusions. To investigate the effective connectivity between - and within - sensory and premotor areas involved in bodily perceptions, we used dynamic causal modeling of touch-evoked responses in 13 healthy subjects. Each subject's right hand was stroked while viewing their own hand ("REAL"), or an artificial hand presented in an anatomically plausible ("CONGRUENT") or implausible ("INCONGRUENT") position. Bayesian model comparison revealed strong evidence for a differential involvement of the PMC in the generation of touch-evoked responses under the three conditions, confirming a crucial role of PMC in bodily self-attribution. In brief, the extrinsic (forward) connection from left occipital cortex to left PMC was stronger for CONGRUENT and INCONGRUENT as compared to REAL, reflecting the augmentation of bottom-up visual input when multisensory integration is challenged. Crucially, intrinsic connectivity in the primary somatosensory cortex (S1) was attenuated in the CONGRUENT condition, during the illusory percept. These findings support predictive coding models of the functional architecture of multisensory integration (and attenuation) in bodily perceptual experience. PMID:27241481
Identifying abnormal connectivity in patients using Dynamic Causal Modelling of fMRI responses.
Mohamed L Seghier
2010-08-01
Full Text Available Functional imaging studies of brain damaged patients offer a unique opportunity to understand how sensori-motor and cognitive tasks can be carried out when parts of the neural system that support normal performance are no longer available. In addition to knowing which regions a patient activates, we also need to know how these regions interact with one another, and how these inter-regional interactions deviate from normal. Dynamic Causal Modelling (DCM offers the opportunity to assess task-dependent interactions within a set of regions. Here we review its use in patients when the question of interest concerns the characterisation of abnormal connectivity for a given pathology. We describe the currently available implementations of DCM for fMRI responses, varying from the deterministic bilinear models with one-state equation to the stochastic nonlinear models with two-state equations. We also highlight the importance of the new Bayesian model selection and averaging tools that allow different plausible models to be compared at the single subject and group level. These procedures allow inferences to be made at different levels of model selection, from features (model families to connectivity parameters. Following a critical review of previous DCM studies that investigated abnormal connectivity we propose a systematic procedure that will ensure more flexibility and efficiency when using DCM in patients. Finally, some practical and methodological issues crucial for interpreting or generalising DCM findings in patients are discussed.
Triangulation in Friedmann's cosmological model
In Friedmann's model, physical 3-space has a curvature K = constant. In the cases of greatest interest (K different from 0) triangulation for the measurement of great distances should be based on non-Euclidean geometries: Riemannian (or doubly elliptic) geometry for a closed universe and Bolyai-Lobatchevsky's (or hiperbolic) geometry for an open universe
Kirilyuk, A P
1998-01-01
This work introduces the Universal Science of Complexity. It emerges together with the paradigm of the dynamic redundance, or fundamental multivaluedness of dynamical functions, based on the plurality of incompatible, but equally real, solutions to a problem which naturally appear in the formal description of a generic dynamical behaviour, if one tries to avoid, in a universally applicable fashion, the simplification of the ordinary perturbative reduction to an effectively one-dimensional, 'separable' problem. The discovered dynamic multivaluedness directly leads to the new, universal concept of dynamic complexity and its naturally forming hierarchical structure. The lowest levels of the universal hierarchy of complexity give the complete causal wave mechanics that can be described as the unreduced version of the double solution proposed by Louis de Broglie and amplified here with the idea of the intrinsic dynamical chaos realising the dynamic redundance at the lowest levels of being. This complete wave mecha...
Harun
2016-01-01
The purpose of this research is to examine the causal and dynamic relationship among stock market, trading volume, and return volatility in South-East Asia market period of 2011-2014. This research employs Vector Auto-Regression (VAR) and E-GARCH model. The causal and dynamic relationship between stock return and trading volume analyzed using VAR model, whereas dynamic relationship between return volatility and trading volume analyzed using E-GARCH model. Result showed that Thailand market re...
Explicit angle structures for veering triangulations
Futer, David
2010-01-01
Agol recently introduced the notion of a veering triangulation, and showed that such triangulations naturally arise as layered triangulations of fibered hyperbolic 3-manifolds. We prove, by a constructive argument, that every veering triangulation admits positive angle structures, recovering a result of Hodgson, Rubinstein, Segerman, and Tillmann. Our construction leads to explicit lower bounds on the smallest angle in this positive angle structure, and to information about angled holonomy of the boundary tori.
Adams, R. A.; Bauer, M.; Pinotsis, D; Friston, K J
2016-01-01
This paper shows that it is possible to estimate the subjective precision (inverse variance) of Bayesian beliefs during oculomotor pursuit. Subjects viewed a sinusoidal target, with or without random fluctuations in its motion. Eye trajectories and magnetoencephalographic (MEG) data were recorded concurrently. The target was periodically occluded, such that its reappearance caused a visual evoked response field (ERF). Dynamic causal modelling (DCM) was used to fit models of eye trajectories a...
Kirilyuk, A P
1995-01-01
The concept of the fundamental dynamic uncertainty (or the fundamental multivaluedness of dynamical functions) developed in parts I-III of this work and used to re-establish the correspondence principle for chaotic Hamiltonian systems provides also a causal description of the basic properties of quantum measurement, - quantum indeterminacy and wave reduction. The modified Schrödinger formalism involving multivalued effective dynamical functions reveals the dynamical origin of quantum indeterminacy as the intrinsic nonlinear instability in the combined quantum system of the measured object interacting with the instrument. As a result of this instability, the originally wide measured wave dynamically "shrinks" around a random accessible point of the combined configurational space loosing its coherence with respect to other possibilities. We do not use any assumptions on particular "classical", "macroscopic", "stochastic", etc. nature of the instrument or environment: full quantum indeterminacy dynamically appe...
Rosalyn J Moran
Full Text Available Generative models of neuroimaging and electrophysiological data present new opportunities for accessing hidden or latent brain states. Dynamic causal modeling (DCM uses Bayesian model inversion and selection to infer the synaptic mechanisms underlying empirically observed brain responses. DCM for electrophysiological data, in particular, aims to estimate the relative strength of synaptic transmission at different cell types and via specific neurotransmitters. Here, we report a DCM validation study concerning inference on excitatory and inhibitory synaptic transmission, using different doses of a volatile anaesthetic agent (isoflurane to parametrically modify excitatory and inhibitory synaptic processing while recording local field potentials (LFPs from primary auditory cortex (A1 and the posterior auditory field (PAF in the auditory belt region in rodents. We test whether DCM can infer, from the LFP measurements, the expected drug-induced changes in synaptic transmission mediated via fast ionotropic receptors; i.e., excitatory (glutamatergic AMPA and inhibitory GABA(A receptors. Cross- and auto-spectra from the two regions were used to optimise three DCMs based on biologically plausible neural mass models and specific network architectures. Consistent with known extrinsic connectivity patterns in sensory hierarchies, we found that a model comprising forward connections from A1 to PAF and backward connections from PAF to A1 outperformed a model with forward connections from PAF to A1 and backward connections from A1 to PAF and a model with reciprocal lateral connections. The parameter estimates from the most plausible model indicated that the amplitude of fast glutamatergic excitatory postsynaptic potentials (EPSPs and inhibitory postsynaptic potentials (IPSPs behaved as predicted by previous neurophysiological studies. Specifically, with increasing levels of anaesthesia, glutamatergic EPSPs decreased linearly, whereas fast GABAergic IPSPs
Philippe eAlbouy
2015-02-01
Full Text Available Congenital amusia is a neuro-developmental disorder that primarily manifests as a difficulty in the perception and memory of pitch-based materials, including music. Recent findings have shown that the amusic brain exhibits altered functioning of a fronto-temporal network during pitch perception and memory. Within this network, during the encoding of melodies, a decreased right backward frontal-to-temporal connectivity was reported in amusia, along with an abnormal connectivity within and between auditory cortices. The present study investigated whether connectivity patterns between these regions were affected during the retrieval of melodies. Amusics and controls had to indicate whether sequences of six tones that were presented in pairs were the same or different. When melodies were different only one tone changed in the second melody. Brain responses to the changed tone in Different trials and to its equivalent (original tone in Same trials were compared between groups using Dynamic Causal Modeling (DCM. DCM results confirmed that congenital amusia is characterized by an altered effective connectivity within and between the two auditory cortices during sound processing. Furthermore, right temporal-to-frontal message passing was altered in comparison to controls, with an increase in Same trials and a decrease in Different trials. An additional analysis in control participants emphasized that the detection of an unexpected event in the typically functioning brain is supported by right fronto-temporal connections. The results can be interpreted in a predictive coding framework as reflecting an abnormal prediction error sent by temporal auditory regions towards frontal areas in the amusic brain.
Liangsuo Ma
2015-01-01
Full Text Available Cocaine dependence is associated with increased impulsivity in humans. Both cocaine dependence and impulsive behavior are under the regulatory control of cortico-striatal networks. One behavioral laboratory measure of impulsivity is response inhibition (ability to withhold a prepotent response in which altered patterns of regional brain activation during executive tasks in service of normal performance are frequently found in cocaine dependent (CD subjects studied with functional magnetic resonance imaging (fMRI. However, little is known about aberrations in specific directional neuronal connectivity in CD subjects. The present study employed fMRI-based dynamic causal modeling (DCM to study the effective (directional neuronal connectivity associated with response inhibition in CD subjects, elicited under performance of a Go/NoGo task with two levels of NoGo difficulty (Easy and Hard. The performance on the Go/NoGo task was not significantly different between CD subjects and controls. The DCM analysis revealed that prefrontal–striatal connectivity was modulated (influenced during the NoGo conditions for both groups. The effective connectivity from left (L anterior cingulate cortex (ACC to L caudate was similarly modulated during the Easy NoGo condition for both groups. During the Hard NoGo condition in controls, the effective connectivity from right (R dorsolateral prefrontal cortex (DLPFC to L caudate became more positive, and the effective connectivity from R ventrolateral prefrontal cortex (VLPFC to L caudate became more negative. In CD subjects, the effective connectivity from L ACC to L caudate became more negative during the Hard NoGo conditions. These results indicate that during Hard NoGo trials in CD subjects, the ACC rather than DLPFC or VLPFC influenced caudate during response inhibition.
Aging into perceptual control: A Dynamic Causal Modeling for fMRI study of bistable perception
Ehsan eDowlati
2016-03-01
Full Text Available Aging is accompanied by stereotyped changes in functional brain activations, for example a cortical shift in activity patterns from posterior to anterior regions is one hallmark revealed by functional magnetic resonance imaging (fMRI of aging cognition. Whether these neuronal effects of aging could potentially contribute to an amelioration of or resistance to the cognitive symptoms associated with psychopathology remains to be explored. We used a visual illusion paradigm to address whether aging affects the cortical control of perceptual beliefs and biases. Our aim was to understand the effective connectivity associated with volitional control of ambiguous visual stimuli and to test whether greater top-down control of early visual networks emerged with advancing age. Using a bias training paradigm for ambiguous images we found that older participants (n = 16 resisted experimenter-induced visual bias compared to a younger cohort (n = 14 and that this resistance was associated with greater activity in prefrontal and temporal cortices. By applying Dynamic Causal Models for fMRI we uncovered a selective recruitment of top-down connections from the middle temporal to lingual gyrus by the older cohort during the perceptual switch decision following bias training. In contrast, our younger cohort did not exhibit any consistent connectivity effects but instead showed a loss of driving inputs to orbitofrontal sources following training. These findings suggest that perceptual beliefs are more readily controlled by top-down strategies in older adults and introduce age-dependent neural mechanisms that may be important for understanding aberrant belief states associated with psychopathology.
Yuan, Zhen
2014-03-01
Identifying directional influences in neural circuits from functional near infrared spectroscopy (fNIRS) recordings presents one of the main challenges for understanding brain dynamics. In this study a new strategy that combines Granger causality mapping (GCM) and independent component analysis (ICA) is proposed to reveal complex neural network dynamics underlying cognitive processes with fNIRS measurements. The GCM-ICA algorithm implements the following two procedures: (i) extraction of the region of interests (ROIs) of cortical activations by ICA, and (ii) estimation of the direct causal influences in local brain networks using Granger causality among voxels of ROIs. Our results show the use of GCM in conjunction with ICA is able to effectively capture the brain network dynamics in time-frequency domain with significantly reduced computational cost. We thus suggest that the GCM-ICA technique is a potentially valuable tool that could be used for the investigation of directional causality influences of brain network dynamics in biophotonics fields.
Triangulation methods in engineering measurement
Kyle, S. A.
1988-01-01
Industrial surveying and photogrammetry are being increasingly applied to the measurement of engineering objects which have typical dimensions in the range 2-100 metres. Both techniques are examples of the principle of triangulation. By applying photocrammetric concepts to surveying methods and vice-versa, a general approach is established which has a number of advantages. In particular. alternative strategies for constructing and analysing measurement networks are dev...
The causal dynamics between coal consumption and growth: Evidence from emerging market economies
This study examines the relationship between coal consumption and economic growth for 15 emerging market economies within a multivariate panel framework over the period 1980-2006. The heterogeneous panel cointegration results indicate there is a long-run equilibrium relationship between real GDP, coal consumption, real gross fixed capital formation, and the labor force. While in the long-run both real gross fixed capital formation and the labor force have a significant positive impact on real GDP, coal consumption has a significant negative impact. The panel causality tests show bidirectional causality between coal consumption and economic growth in both the short- and long-run. (author)
Kirilyuk, A P
1995-01-01
The intrinsic multivaluedness of the effective dynamical functions, revealed in part I of this series of papers, is interpreted as the origin of the true dynamical (in particular, quantum) chaos. The main postulate of the fundamental dynamic uncertainty thus formulated is specified for Hamiltonian quantum systems and applied to quantum chaos description in periodically perturbed systems. The ordinary semiclassical transition in our quantum-mechanical results leads to the reproduction of the main features of chaotic behaviour of the same systems known from classical mechanics, which permits one to "re-establish" the correspondence principle for chaotic systems. The causal dynamical randomness in the extended quantum mechanics is not restricted, however, to semiclassical conditions and occurs also in essentially quantum regimes, although partial "quantum suppression of chaos" does exist and is specified in our description, as well as other particular types of the quantum chaotic behaviour.
The Nonlinear Dynamic Relationship of Exchange Rates: Parametric and Nonparametric Causality testing
S.D. Bekiros; C. Diks
2007-01-01
The present study investigates the long-term linear and nonlinear causal linkages among six currencies, namely EUR/USD, GBP/USD, USD/JPY, USD/CHF, AUD/USD and USD/CAD. The prime motivation for choosing these exchange rates comes from the fact that they are the most liquid and widely traded, covering
Kirilyuk, A P
2000-01-01
On 14 December 1900 Max Planck first formulated the idea of energy quanta related to a new universal constant, now known as Planck's constant. Despite the following progress of the thus initiated 'quantum mechanics', the physical origin of both quantization and universality of Planck's constant remains mysterious, as well as other 'peculiar' properties of quantum dynamics. In this paper we review a recent causal extension of quantum mechanics consistently explaining all its 'mysteries' by the irreducibly complex, 'dynamically multivalued' behaviour of the underlying system of two interacting 'protofields' (quant-ph/9902015, quant-ph/9902016). The theory contains no imposed postulates or entities except one, unavoidable, assumption about the physical nature of the protofields. All the observed entities and their properties, starting from physically real space, time, and elementary particles, are consistently derived, in exact correspondence with their emergence in the real, irreducibly complex, system dynamics...
Annular-Efficient Triangulations of 3-manifolds
Jaco, William
2011-01-01
A triangulation of a compact 3-manifold is annular-efficient if it is 0-efficient and the only normal, incompressible annuli are thin edge-linking. If a compact 3-manifold has an annular-efficient triangulation, then it is irreducible, boundary-irreducible, and an-annular. Conversely, it is shown that for a compact, irreducible, boundary-irreducible, and an-annular 3-manifold, any triangulation can be modified to an annular-efficient triangulation. It follows that for a manifold satisfying this hypothesis, there are only a finite number of boundary slopes for incompressible and boundary-incompressible surfaces of a bounded Euler characteristic.
Following the recent global economic downturn, attention has gradually shifted towards emerging economies which have experienced robust growth amidst sluggish growth of the world economy. A significant number of these emerging economies are in Africa. Rising growth in these economies is associated with surging demand for energy to propel the engines of growth, with direct implications on emissions into the atmosphere. Further, these economies are constantly being shaped by series of structural reforms with direct and indirect effects on growth, demand for energy, etc. To this end, this paper examines the causal dynamics among energy use, real GDP and CO2 emissions in the presence of regime shifts in six emerging African economies using the Gregory and Hansen (1996a). J. Econ. 70, 99–126 threshold cointegration and the Toda and Yamamoto (1995). J. Econometrics. 66, 225–250 Granger causality techniques. Results confirm the presence of regime shift effects in the long run inter-linkages among energy use, real GDP and CO2 emissions in the countries considered, thus indicating that structural changes have both economic and environmental effects. Hence, integration of energy and environmental policies into development plans is imperative towards attaining sustainable growth and development. - Highlights: • The paper examines the causal dynamics among output, energy demand and carbon emissions in the presence of regime shifts. • Regime shift have significant effects on the nexus among energy use, real GDP and CO2 emissions. • Results suggest that structural changes in selected countries have both economic and environmental effects. • Integration of energy and environmental policies into development plans is desirable
DYNAMICS OF MUTUAL FUNDS IN RELATION TO STOCK MARKET: A VECTOR AUTOREGRESSIVE CAUSALITY ANALYSIS
Md. Shahadath Hossain
2013-01-01
Full Text Available In Bangladesh, primary and secondary mutual fund markets behave in a completely different way, where initial public offering (IPO investors of mutual funds earn more than 250 percent rerun, whereas secondary market investors cannot even manage to cover the opportunity cost of their investment. There are few other abnormalities present in this market – unlike everywhere in the world, most of the mutual funds are closed-end (92 percent and closed-end mutual funds are barred to issue bonus or right shares. A total of 714 day’s observations, from January 2008 to December 2010, of four variables– DSE (Dhaka Stock Exchange general index return, DSE general index turnover, mutual funds’ return and mutual funds’ turnover– are utilized. Stationarity of the variables are tested with Augmented Dickey-Fuller (ADF unit root test and found that variables are in different order of integration. Long-term equilibrium relationships among the variables are tested with Johansen cointegration and it is found that DSE general index return and mutual funds’ return are cointegrated. Toda-Yamamoto (TY version of granger non-causality test is employed and bidirectional causality is found moving from DSE (Dhaka Stock Exchange general index turnover to DSE general index return, whereas unidirectional causality is found moving from mutual fund’s return to DSE general index return, mutual funds’ return to mutual funds turnover, and DSE general index turnover to mutual funds turnover. This finding helps to conclude that equity shares’ demand drives the mutual funds demand but even higher demand of mutual funds fails to raise its own price unless underlying value of the mutual funds changes.
Serakos, Demetrios
2010-01-01
A causal input-output system may be described by a function space for inputs, a function space for outputs, and a causal operator mapping the input space into the output space. A particular representation of the state of such a system at any instant has been defined as an operator from the space of possible future inputs to that of future outputs. This representation is called the natural state. The purpose of this report is to investigate additional properties of the natural state in two areas. The first area has to do with the possibility of determining the input-output system from its natural state set. A counterexample where this is not possible is given. Sufficient conditions for identifying the system from its natural state set are given. The results in this area are mostly for time-invariant systems. There are also some preliminary observations on reachability. The second area deals with differentiability properties involving the natural state inherited from the input-output system, including different...
Interferometer predictions with triangulated images
Brinch, Christian; Dullemond, C. P.
2014-01-01
requires a model image that is a list of intensities at arbitrarily placed positions on the image-plane. It creates a triangulated grid from these vertices, and assumes that the intensity inside each triangle of the grid is a linear function. The Fourier integral over each triangle is then evaluated with...... synthetic model images. To get the correct values of these integrals, the model images must have the right size and resolution. Insufficient care in these choices can lead to wrong results. We present a new general-purpose scheme for the computation of visibilities of radiative transfer images. Our method...... an analytic expression and the complex visibility of the entire image is then the sum of all triangles. The result is a robust Fourier transform that does not suffer from aliasing effects due to grid regularities. The method automatically ensures that all structure contained in the model gets...
Maksim eSharaev
2016-02-01
Full Text Available The Default Mode Network (DMN is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of BOLD (Blood-oxygen-level dependent activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e. effective connectivity, however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex mPFC, the posterior cingulate cortex PCC, left and right intraparietal cortex LIPC and RIPC. For this purpose fMRI (functional magnetic resonance imaging data from 30 healthy subjects (1000 time points from each one was acquired and spectral dynamic causal modeling (DCM on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078–0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p<0.05. Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain’s functioning at resting state.
Synergy and redundancy in the Granger causal analysis of dynamical networks
We analyze, by means of Granger causality (GC), the effect of synergy and redundancy in the inference (from time series data) of the information flow between subsystems of a complex network. While we show that fully conditioned GC (CGC) is not affected by synergy, the pairwise analysis fails to prove synergetic effects. In cases when the number of samples is low, thus making the fully conditioned approach unfeasible, we show that partially conditioned GC (PCGC) is an effective approach if the set of conditioning variables is properly chosen. Here we consider two different strategies (based either on informational content for the candidate driver or on selecting the variables with highest pairwise influences) for PCGC and show that, depending on the data structure, either one or the other might be equally valid. On the other hand, we observe that fully conditioned approaches do not work well in the presence of redundancy, thus suggesting the strategy of separating the pairwise links in two subsets: those corresponding to indirect connections of the CGC (which should thus be excluded) and links that can be ascribed to redundancy effects and, together with the results from the fully connected approach, provide a better description of the causality pattern in the presence of redundancy. Finally we apply these methods to two different real datasets. First, analyzing electrophysiological data from an epileptic brain, we show that synergetic effects are dominant just before seizure occurrences. Second, our analysis applied to gene expression time series from HeLa culture shows that the underlying regulatory networks are characterized by both redundancy and synergy. (paper)
Rasmussen, Lauge Baungaard
2006-01-01
The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method......The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method...
Intervention and causality: forecasting traffic flows using a dynamic Bayesian network
Queen, Catriona; Albers, Casper
2009-01-01
Real-time traffic flow data across entire networks can be used in a traffic management system to monitor current traffic flows so that traffic can be directed and managed efficiently. Reliable short-term forecasting models of traffic flows are crucial for the success of any traffic management system. The model proposed in this paper for forecasting traffic flows is a multivariate Bayesian dynamic model called the multiregression dynamic model (MDM). This model is an example of a dynamic ...
Detection of motor changes in Huntington’s disease using dynamic causal modeling
Lora Minkova
2015-11-01
Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD, and 16 patients with manifest HD symptoms (earlyHD performed a motor finger tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA, dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Ward’s method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters which also differed significantly among these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.
Gobert, Janice D.; Clement, John J.
1999-01-01
Grade five students' (n=58) conceptual understanding of plate tectonics was measured by analysis of student-generated summaries and diagrams, and by posttest assessment of both the spatial/static and causal/dynamic aspects of the domain. The diagram group outperformed the summary and text-only groups on the posttest measures. Discusses the effects…
Kirilyuk, A P
2003-01-01
The universal concept of complexity by the dynamic redundance paradigm and the ensuing concept of extended dynamic fractality (physics/9806002) are applied here to higher levels of complexity corresponding to living systems. After recalling the framework of unreduced dynamic complexity and dynamically probabilistic fractality (see also physics/0211071), we concentrate on the novelties they propose for the case of living systems with respect to the conventional, dynamically single-valued theory. The phenomenon of life can now be demystified and consistently understood as a particular case of the universal symmetry of complexity realised by unreduced complexity transformation from dynamic information into (extended) entropy that preserves the total complexity amount and involves its high enough levels. This intrinsically creative, and therefore realistic, version of bio-physical 'reductionism' reveals the explicit, dynamical source of adaptability and qualitatively new entity emergence and leads to essential, w...
Witherington, David C.
2011-01-01
The dynamic systems (DS) approach has emerged as an influential and potentially unifying metatheory for developmental science. Its central platform--the argument against design--suggests that structure spontaneously and without prescription emerges through self-organization. In one of the most prominent accounts of DS, Thelen and her colleagues…
Field theories with Lorentz (or diffeomorphism invariant) action can exhibit superluminal behavior through the breaking of local Lorentz invariance. Quantum induced superluminal velocities are well-known examples of this effect. The issue of the causal behavior of such propagation is somewhat controversial in the literature and we intend to clarify it. We provide a careful analysis of the meaning of causality in classical relativistic field theories and stress the role played by the Cauchy problem and the notion of chronology. We show that, in general, superluminal behavior threatens causality only if one assumes that a prior chronology in spacetime exists. In the case where superluminal propagation occurs, however, there are at least two nonconformally related metrics in spacetime and thus two available notions of chronology. These two chronologies are on equal footing, and it would thus be misleading to choose ab initio one of them to define causality. Rather, we provide a formulation of causality in which no prior chronology is assumed. We argue that this is the only way to deal with the issue of causality in the case where some degrees of freedom propagate faster than others. In that framework, then, it is shown that superluminal propagation is not necessarily noncausal, the final answer depending on the existence of an initial data formulation. This also depends on global properties of spacetime that we discuss in detail. As an illustration of these conceptual issues, we consider two field theories, namely, k-essence scalar fields and bimetric theories of gravity, and we derive the conditions imposed by causality. We discuss various applications such as the dark energy problem, modified-Newtonian-dynamics-like theories of gravity, and varying speed of light theories
Piliponytė, Agnė
2014-01-01
Research objective: To assess species ratio of L. maculans and L. biglobosa during oilseed rape growing season and determine the response of oilseed rape plants to L. maculans and L. biglobosa infection. Experimental objectives: 1. To investigate seasonal dynamics of Leptosphaeria spp. ascospore release and investigate species composition of L. maculans and L. biglobosa ascospores in spore samples using real time PCR. 2. To assess the occurrence of L. maculans and L. biglobosa on different Br...
Roaming moduli space using dynamical triangulations
Ambjørn, J.; Barkley, J.; Budd, T.G.
2012-01-01
In critical as well as in non-critical string theory the partition function reduces to an integral over modulispace after integration over matter fields. For non-critical string theory this moduli integrand is known for genus one surfaces. The formalism of dynamicaltriangulations provides us with a
Blume, T.; Heidbuechel, I.; Hassler, S. K.; Simard, S.; Guntner, A.; Stewart, R. D.; Weiler, M.
2015-12-01
We hypothesize that there is a shift in controls on landscape scale soil moisture patterns when plants become active during the growing season. Especially during the summer soil moisture patterns are not only controlled by soils, topography and related abiotic site characteristics but also by root water uptake. Root water uptake influences soil moisture patterns both in the lateral and vertical direction. Plant water uptake from different soil depths is estimated based on diurnal fluctuations in soil moisture content and was investigated with a unique setup of 46 field sites in Luxemburg and 15 field sites in Germany. These sites cover a range of geologies, soils, topographic positions and types of vegetation. Vegetation types include pasture, pine forest (young and old) and different deciduous forest stands. Available data at all sites includes information at high temporal resolution from 3-5 soil moisture and soil temperature profiles, matrix potential, piezometers and sapflow sensors as well as standard climate data. At sites with access to a stream, discharge or water level is also recorded. The analysis of soil moisture patterns over time indicates a shift in regime depending on season. Depth profiles of root water uptake show strong differences between different forest stands, with maximum depths ranging between 50 and 200 cm. Temporal dynamics of signal strength within the profile furthermore suggest a locally shifting spatial distribution of root water uptake depending on water availability. We will investigate temporal thresholds (under which conditions spatial patterns of root water uptake become most distinct) as well as landscape controls on soil moisture and root water uptake dynamics.
Xi, Yi-Bin; Li, Chen; Cui, Long-Biao; Liu, Jian; Guo, Fan; Li, Liang; Liu, Ting-Ting; Liu, Kang; Chen, Gang; Xi, Min; Wang, Hua-Ning; Yin, Hong
2016-01-01
Familial risk plays a significant role in the etiology of schizophrenia (SZ). Many studies using neuroimaging have demonstrated structural and functional alterations in relatives of SZ patients, with significant results found in diverse brain regions involving the anterior cingulate cortex (ACC), caudate, dorsolateral prefrontal cortex (DLPFC), and hippocampus. This study investigated whether unaffected relatives of first episode SZ differ from healthy controls (HCs) in effective connectivity measures among these regions. Forty-six unaffected first-degree relatives of first episode SZ patients-according to the DSM-IV-were studied. Fifty HCs were included for comparison. All subjects underwent resting state functional magnetic resonance imaging (fMRI). We used stochastic dynamic causal modeling (sDCM) to estimate the directed connections between the left ACC, right ACC, left caudate, right caudate, left DLPFC, left hippocampus, and right hippocampus. We used Bayesian parameter averaging (BPA) to characterize the differences. The BPA results showed hyperconnectivity from the left ACC to right hippocampus and hypoconnectivity from the right ACC to right hippocampus in SZ relatives compared to HCs. The pattern of anterior cingulate cortico-hippocampal connectivity in SZ relatives may be a familial feature of SZ risk, appearing to reflect familial susceptibility for SZ. PMID:27512370
Huang, Xu-Guang; Koide, Tomoi
2012-09-01
The microscopic formulas for the shear viscosity η, the bulk viscosity ζ, and the corresponding relaxation times τπ and τΠ of causal dissipative relativistic fluid-dynamics are obtained at finite temperature and chemical potential by using the projection operator method. The non-triviality of the finite chemical potential calculation is attributed to the arbitrariness of the operator definition for the bulk viscous pressure. We show that, when the operator definition for the bulk viscous pressure Π is appropriately chosen, the leading-order result of the ratio, ζ over τΠ, coincides with the same ratio obtained at vanishing chemical potential. We further discuss the physical meaning of the time-convolutionless (TCL) approximation to the memory function, which is adopted to derive the main formulas. We show that the TCL approximation violates the time reversal symmetry appropriately and leads results consistent with the quantum master equation obtained by van Hove. Furthermore, this approximation can reproduce an exact relation for transport coefficients obtained by using the f-sum rule derived by Kadanoff and Martin. Our approach can reproduce also the result in Baier et al. (2008) [8] by taking into account the next-order correction to the TCL approximation, although this correction causes several problems.
Within the new developed causality-in-variance approach, this paper builds up a broad methodological framework to more accurately capture the risk spillover effects between global oil prices and Jordanian stock market returns during the period 1 March 2003–31 January 2014. The sample period is divided, on the basis of the 2008 financial crisis, into pre-crisis and post-crisis periods. Results for the pre-crisis period show a lack of risk spillovers between global oil and the Jordanian stock market. After the crisis, however, we find evidence for one-way risk spillover running from the oil market. These findings have implications for the design of appropriate asset allocation and regulatory policies to manage risk spillover effects. -- Highlights: •A broad methodological framework accurately seizes dynamic risk spillover between oil prices and Jordanian stock returns. •We find insignificant risk spillover until the start of the financial crisis. •Crude oil transmits its risk to the Jordanian stock market
Chi, Do Minh
2001-01-01
We advance a famous principle - causality principle - but under a new view. This principle is a principium automatically leading to most fundamental laws of the nature. It is the inner origin of variation, rules evolutionary processes of things, and the answer of the quest for ultimate theories of the Universe.
Triangulations of hyperbolic 3-manifolds admitting strict angle structures
Hodgson, Craig D; Segerman, Henry
2011-01-01
It is conjectured that every cusped hyperbolic 3-manifold has a decomposition into positive volume ideal hyperbolic tetrahedra (a "geometric" triangulation of the manifold). Under a mild homology assumption on the manifold we construct topological ideal triangulations which admit a strict angle structure, which is a necessary condition for the triangulation to be geometric. In particular, every knot or link complement in the 3-sphere has such a triangulation. We also give an example of a triangulation without a strict angle structure, where the obstruction is related to the homology hypothesis, and an example illustrating that the triangulations produced using our methods are not generally geometric.
Improving machine translation via triangulation and transliteration
Durrani, Nadir; Koehn, Philipp
2014-01-01
In this paper we improve Urdu→Hindi-English machine translation through triangulation and transliteration. First we built an Urdu→Hindi SMT system by inducing triangulated and transliterated phrase-tables from Urdu–English and Hindi–English phrase translation models. We then use it to translate the Urdu part of the Urdu-English parallel data into Hindi, thus creating an artificial Hindi-English parallel data. Our phrase-translation strategies give an improvement of up to +3.35 BLEU points ove...
Tuma, Nancy Brandon; Hannan, Michael T.
The document, part of a series of chapters described in SO 011 759, examines sociological research methods for the study of change. The advantages and procedures for dynamic analysis of event-history data (data giving the number, timing, and sequence of changes in a categorical dependent variable) are considered. The authors argue for grounding…
Adams, Rick A; Bauer, Markus; Pinotsis, Dimitris; Friston, Karl J
2016-05-15
This paper shows that it is possible to estimate the subjective precision (inverse variance) of Bayesian beliefs during oculomotor pursuit. Subjects viewed a sinusoidal target, with or without random fluctuations in its motion. Eye trajectories and magnetoencephalographic (MEG) data were recorded concurrently. The target was periodically occluded, such that its reappearance caused a visual evoked response field (ERF). Dynamic causal modelling (DCM) was used to fit models of eye trajectories and the ERFs. The DCM for pursuit was based on predictive coding and active inference, and predicts subjects' eye movements based on their (subjective) Bayesian beliefs about target (and eye) motion. The precisions of these hierarchical beliefs can be inferred from behavioural (pursuit) data. The DCM for MEG data used an established biophysical model of neuronal activity that includes parameters for the gain of superficial pyramidal cells, which is thought to encode precision at the neuronal level. Previous studies (using DCM of pursuit data) suggest that noisy target motion increases subjective precision at the sensory level: i.e., subjects attend more to the target's sensory attributes. We compared (noisy motion-induced) changes in the synaptic gain based on the modelling of MEG data to changes in subjective precision estimated using the pursuit data. We demonstrate that imprecise target motion increases the gain of superficial pyramidal cells in V1 (across subjects). Furthermore, increases in sensory precision - inferred by our behavioural DCM - correlate with the increase in gain in V1, across subjects. This is a step towards a fully integrated model of brain computations, cortical responses and behaviour that may provide a useful clinical tool in conditions like schizophrenia. PMID:26921713
Adams, Rick A.; Bauer, Markus; Pinotsis, Dimitris; Friston, Karl J.
2016-01-01
This paper shows that it is possible to estimate the subjective precision (inverse variance) of Bayesian beliefs during oculomotor pursuit. Subjects viewed a sinusoidal target, with or without random fluctuations in its motion. Eye trajectories and magnetoencephalographic (MEG) data were recorded concurrently. The target was periodically occluded, such that its reappearance caused a visual evoked response field (ERF). Dynamic causal modelling (DCM) was used to fit models of eye trajectories and the ERFs. The DCM for pursuit was based on predictive coding and active inference, and predicts subjects' eye movements based on their (subjective) Bayesian beliefs about target (and eye) motion. The precisions of these hierarchical beliefs can be inferred from behavioural (pursuit) data. The DCM for MEG data used an established biophysical model of neuronal activity that includes parameters for the gain of superficial pyramidal cells, which is thought to encode precision at the neuronal level. Previous studies (using DCM of pursuit data) suggest that noisy target motion increases subjective precision at the sensory level: i.e., subjects attend more to the target's sensory attributes. We compared (noisy motion-induced) changes in the synaptic gain based on the modelling of MEG data to changes in subjective precision estimated using the pursuit data. We demonstrate that imprecise target motion increases the gain of superficial pyramidal cells in V1 (across subjects). Furthermore, increases in sensory precision – inferred by our behavioural DCM – correlate with the increase in gain in V1, across subjects. This is a step towards a fully integrated model of brain computations, cortical responses and behaviour that may provide a useful clinical tool in conditions like schizophrenia. PMID:26921713
Delta-groupoids and ideal triangulations
Kashaev, Rinat Mavlyavievich
2009-01-01
A Delta-groupoid is an algebraic structure which axiomatizes the combinatorics of a truncated tetrahedron. By considering two simplest examples coming from knot theory, we illustrate how can one associate a Delta-groupoid to an ideal triangulation of a three-manifold. We also describe in detail the rings associated with the Delta-groupoids of these examples.
Spectral Properties of Unimodular Lattice Triangulations
Krüger, Benedikt; Schmidt, Ella M.; Mecke, Klaus
2016-05-01
Random unimodular lattice triangulations have been recently used as an embedded random graph model, which exhibit a crossover behavior between an ordered, large-world and a disordered, small-world behavior. Using the ergodic Pachner flips that transform such triangulations into another and an energy functional that corresponds to the degree distribution variance, Markov chain Monte Carlo simulations can be applied to study these graphs. Here, we consider the spectra of the adjacency and the Laplacian matrix as well as the algebraic connectivity and the spectral radius. Power law dependencies on the system size can clearly be identified and compared to analytical solutions for periodic ground states. For random triangulations we find a qualitative agreement of the spectral properties with well-known random graph models. In the microcanonical ensemble analytical approximations agree with numerical simulations. In the canonical ensemble a crossover behavior can be found for the algebraic connectivity and the spectral radius, thus combining large-world and small-world behavior in one model. The considered spectral properties can be applied to transport problems on triangulation graphs and the crossover behavior allows a tuning of important transport quantities.
Klarenberg, G.
2015-12-01
Infrastructure projects such as road paving have proven to bring a variety of (mainly) socio-economic advantages to countries and populations. However, many studies have also highlighted the negative socio-economic and biophysical effects that these developments have at local, regional and even larger scales. The "MAP" area (Madre de Dios in Peru, Acre in Brazil, and Pando in Bolivia) is a biodiversity hotspot in the southwestern Amazon where sections of South America's Inter-Oceanic Highway were paved between 2006 and 2010. We are interested in vegetation dynamics in the area since it plays an important role in ecosystem functions and ecosystem services in socio-ecological systems: it provides information on productivity and structure of the forest. In preparation of more complex and mechanistic simulation of vegetation, non-linear time series analysis and Dynamic Factor Analysis (DFA) was conducted on Enhanced Vegetation Index (EVI) time series - which is a remote sensing product and provides information on vegetation dynamics as it detects chlorophyll (productivity) and structural change. Time series of 30 years for EVI2 (from MODIS and AVHRR) were obtained for 100 communities in the area. Through specific time series cluster analysis of the vegetation data, communities were clustered to facilitate data analysis and pattern recognition. The clustering is spatially consistent, and appears to be driven by median road paving progress - which is different for each cluster. Non-linear time series analysis (multivariate singular spectrum analysis, MSSA) separates common signals (or low-dimensional attractors) across clusters. Despite the presence of this deterministic structure though, time series behavior is mostly stochastic. Granger causality analysis between EVI2 and possible response variables indicates which variables (and with what lags) are to be included in DFA, resulting in unique Dynamic Factor Models for each cluster.
This paper employs annual data from 1971 to 2006 to examine the causal relationship between aggregate output, electricity consumption, exports, labor and capital in a multivariate model for Malaysia. We find that there is bidirectional Granger causality running between aggregate output and electricity consumption. The policy implication of this result is that Malaysia should adopt the dual strategy of increasing investment in electricity infrastructure and stepping up electricity conservation policies to reduce unnecessary wastage of electricity, in order to avoid the negative effect of reducing electricity consumption on aggregate output. We also find support for the export-led hypothesis which states Granger causality runs from exports to aggregate output. This result is consistent with Malaysia pursuing a successful export-orientated strategy. (author)
Palosaari, Anna-Leena
2014-01-01
The aim of the present study was to investigate how and to what extent mathematics- and Finnish language-related causal attributions and self-concept of abilities related among adolescents in upper comprehensive school. The present study also examined whether it is self-concepts that predict subsequent attributions or vice versa. A total of 237 students participated in the study. The data was gathered via questionnaires (attributions and self-concepts) and tests (performance in math and in Fi...
Data Reduction and Triangulation Approach to Scattered Points
JIANG Dan; WANG Lan-cheng
2004-01-01
For the generation of the model in reverse engineering, a laser scanner is currently used a lot due to the fast measuring speed and high precision. Direct triangulation of data points captured from a physical object has a great advantage in that it can reduce the time and error in modeling process. It is important to reduce the number of data points for triangulating points with maintaining precision. To triangulate data points within a tolerance ε a new approach is developed in this paper. Different level of triangulations can be generated directly from data points using the proposed strategy that reduces and triangulates data points based on triangulation of 3D parametric surfaces. An experimental example is presented to demonstrate the effectiveness and efficiency of the proposed algorithm.
Diffractive triangulation of radiative point sources
Vespucci, Stefano; Maneuski, Dzmitry; O'Shea, Val; Winkelmann, Aimo
2016-01-01
We describe a general method to determine the location of a point source of waves relative to a two-dimensional active pixel detector. Based on the inherent structural sensitivity of crystalline sensor materials, characteristic detector diffraction patterns can be used to triangulate the location of a wave emitter. As a practical application of the wide-ranging principle, a digital hybrid pixel detector is used to localize a source of electrons for Kikuchi diffraction pattern measurements in the scanning electron microscope. This provides a method to calibrate Kikuchi diffraction patterns for accurate measurements of microstructural crystal orientations, strains, and phase distributions.
On causality of extreme events
Zanin, Massimiliano
2016-01-01
Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect both linear and non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task.
Computational Hardness of Enumerating Satisfying Spin-Assignments in Triangulations
Jiménez, Andrea
2011-01-01
Satisfying spin-assignments in triangulations of a surface are states of minimum energy of the antiferromagnetic Ising model on triangulations which correspond (via geometric duality) to perfect matchings in cubic bridgeless graphs. In this work we show that it is NP-complete to decide whether or not a surface triangulation admits a satisfying spin-assignment, and that it is #P-complete to determine the number of such assignments. Both results are derived via an elaborate (and atypical) reduction that maps a Boolean formula in 3-conjunctive normal form into a triangulation of an orientable closed surface.
Triangulation, Respondent Validation, and Democratic Participation in Mixed Methods Research
Torrance, Harry
2012-01-01
Over the past 10 years or so the "Field" of "Mixed Methods Research" (MMR) has increasingly been exerting itself as something separate, novel, and significant, with some advocates claiming paradigmatic status. Triangulation is an important component of mixed methods designs. Triangulation has its origins in attempts to validate research findings…
Metodologisk triangulering i arbejdslivsforskning – potentialer og udfordringer
Warring, Niels
2015-01-01
Metodologisk triangulering i arbejdslivsforskning – potentialer og udfordringer Med inddragelse af eksempler fra to forskningsprojekter om pædagogers arbejdsliv, vil der blive argumenteret for det frugtbare i metodologisk triangulering, når der forskes i moderne arbejdsliv – og ikke mindst, når a...
New deghosting method based on generalized triangulation
Bai Jing; Wang Guohong; Xiu Jianjuan; Wang Xiaobo
2009-01-01
A new deghosting method baaed on the generalized triangulation is presented. First, two intersection points corresponding to the emitter position are obtained by utilizing two azimuth angles and two elevation angles from two jammed 3-D radars (or 2-D passive sensors). Then, hypothesis testing baaed deghosting method in the multiple target scenarios is proposed using the two intersection points. In order to analyze the performance of the proposed method, the correct association probability of the true targets and the incorrect association probability of the ghost targets are defined. Finally, the Monte Carlo simulations are given for the proposed method compared with the hinge angle method in the cases of both two and three radars. The simulation results show that the proposed method has better performance than the hinge angle method in three radars case.
Efficient triangulation of Poisson-disk sampled point sets
Guo, Jianwei
2014-05-06
In this paper, we present a simple yet efficient algorithm for triangulating a 2D input domain containing a Poisson-disk sampled point set. The proposed algorithm combines a regular grid and a discrete clustering approach to speedup the triangulation. Moreover, our triangulation algorithm is flexible and performs well on more general point sets such as adaptive, non-maximal Poisson-disk sets. The experimental results demonstrate that our algorithm is robust for a wide range of input domains and achieves significant performance improvement compared to the current state-of-the-art approaches. © 2014 Springer-Verlag Berlin Heidelberg.
Fixed Points of the Restricted Delaunay Triangulation Operator
Khoury, Marc; Shewchuk, Jonathan Richard
2016-01-01
The restricted Delaunay triangulation can be conceived as an operator that takes as input a k-manifold (typically smooth) embedded in R^d and a set of points sampled with sufficient density on that manifold, and produces as output a k-dimensional triangulation of the manifold, the input points serving as its vertices. What happens if we feed that triangulation back into the operator, replacing the original manifold, while retaining the same set of input points? If k = 2 and the sample point...
Granger causality in wall-bounded turbulence
Granger causality is based on the idea that if a variable helps to predict another one, then they are probably involved in a causality relationship. This technique is based on the identification of a predictive model for causality detection. The aim of this paper is to use Granger causality to study the dynamics and the energy redistribution between scales and components in wall-bounded turbulent flows. In order to apply it on flows, Granger causality is generalized for snapshot-based observations of large size using linear-model identification methods coming from model reduction. Optimized DMD, a variant of the Dynamic Mode Decomposition, is considered for building a linear model based on snapshots. This method is used to link physical events and extract physical mechanisms associated to the bursting process in the logarithmic layer of a turbulent channel flow.
Container integrity verification using laser triangulation
Busboom, Axel; Sequeira, Vítor
2007-04-01
We present a system for verifying the integrity of storage containers using a laser triangulation scanner, with applications in nuclear security. Any intrusion into the container shell and subsequent reconstruction of the surface inevitably leaves slight changes to the three-dimensional surface structure which the proposed system can detect. The setup consists of a laser line scanner, mounted on a rotation stage. We propose an auto-calibration procedure for this system which - from several scans of a planar calibration target acquired from different viewpoints - automatically determines the position and orientation of the rotation axis with respect to the scanner coordinate frame. We further present an algorithm for the automatic registration of two 3D scans of a cylindrical surface, not requiring any user interaction such as the identification of corresponding point pairs. We show that the algorithm accurately aligns two scans of the same object, acquired from different viewpoints. The accuracy of the overall system is dominated by the measurement uncertainty of the 3D scanner; residual errors resulting from the calibration and registration are subordinate. The system can reliably detect changes in the surface shape resulting from tampering.
Surface Triangulation for CSG in Mercury
Engel, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Georgia Inst. of Technology, Atlanta, GA (United States); O' Brien, Matthew J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-08-26
Visualization routines for rendering complicated geometries are very useful for engineers and scientists who are trying to build 3D prototypes of their designs. A common way to rapidly add interesting features to a 3D model is through the use of a concept called Constructive Solid Geometry. CSG uses compositions of the boolean set operations to manipulate basic geometric primitives to form more complicated objects. The most common boolean operations employed are union, intersection, and subtraction. Most computer-aided design software packages contain some sort of ability visualize CSG. The typical workflow for the user is as follows: The user specifies the individual primitive components, the user arbitrarily combines each of these primitives with boolean operations, the software generates a CSG tree structure which normally stores these solids implicitly with their defining equation, the tree is traversed and a general algorithm is applied to render the appropriate geometry onto the screen. Algorithms for visualizing CSG have been extensively developed for over a decade. Points sampled from the implicit solids are typically used as input by variations of algorithms like marching cubes and point-cloud surface reconstruction. Here, we explain a surface triangulation method from the graphics community that is being used for surface visualization in the framework of a Monte-Carlo neutron transport code called Mercury.
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models should note carefully both their models’ identifying assumptions and which causal attributions can safely be concluded from their analysis....
Chi, Do Minh
1999-01-01
We research the natural causality of the Universe. We find that the equation of causality provides very good results on physics. That is our first endeavour and success in describing a quantitative expression of the law of causality. Hence, our theoretical point suggests ideas to build other laws including the law of the Universe's evolution.
Aerial Triangulation Close-range Images with Dual Quaternion
SHENG Qinghong
2015-05-01
Full Text Available A new method for the aerial triangulation of close-range images based on dual quaternion is presented. Using dual quaternion to represent the spiral screw motion of the beam in the space, the real part of dual quaternion represents the angular elements of all the beams in the close-range area networks, the real part and the dual part of dual quaternion represents the line elements corporately. Finally, an aerial triangulation adjustment model based on dual quaternion is established, and the elements of interior orientation and exterior orientation and the object coordinates of the ground points are calculated. Real images and large attitude angle simulated images are selected to run the experiments of aerial triangulation. The experimental results show that the new method for the aerial triangulation of close-range images based on dual quaternion can obtain higher accuracy.
Diagonal flips in outer-triangulations on closed surfaces
Cortés Parejo, María del Carmen; Grima Ruiz, Clara Isabel; Márquez Pérez, Alberto; Nakamoto, Atsuhiro
2002-01-01
We show that any two outer-triangulations on the same closed surface can be transformed into each other by a sequence of diagonal flips, up to isotopy, if they have a sufficiently large and equal number of vertices.
Computing triangulation of points in the plane using the GPU
Pavlič, Matevž
2012-01-01
The thesis deals with the problem of triangulation in a real plane using a graphics processing unit, specifically the CUDA architecture. An additional requirement posed is that the calculated triangulation should have the least possible total edge length. The problem thus defined is of the NP complexity. There are a number of different methods for reaching the desired solution, but we do not know which of these are appropriate for running on a graphics processing unit. In this paper we co...
From recollement of triangulated categories to recollement of abelian categories
无
2010-01-01
In this paper,we prove that if a triangulated category D admits a recollement relative to triangulated categories D’ and D″,then the abelian category D/T admits a recollement relative to abelian categories D’/i(T) and D″/j(T) where T is a cluster tilting subcategory of D and satisfies i i (T) T,j j (T) T.
Rigorous LiDAR Strip Adjustment with Triangulated Aerial Imagery
Zhang, Y. J.; Xiong, X. D.; X. Y. Hu
2013-01-01
This paper proposes a POS aided LiDAR strip adjustment method. Firstly, aero-triangulation of the simultaneously obtained aerial images is conducted with a few photogrammetry-specific ground control points. Secondly, LiDAR intensity images are generated from the reflectance signals of laser foot points, and conjugate points are automatically matched between the LiDAR intensity image and the aero-triangulated aerial image. Control points used in LiDAR strip adjustment are derived from...
A TQFT of Tuarev-Viro type on shaped triangulations
Kashaev, Rinat [Geneva Univ. (Switzerland); Luo, Feng [Rutgers Univ., Piscataway, NJ (United States). Dept. of Mathematics; Vartanov, Grigory [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2012-10-15
A shaped triangulation is a finite triangulation of an oriented pseudo three manifold where each tetrahedron carries dihedral angles of an ideal hyberbolic tetrahedron. To each shaped triangulation, we associate a quantum partition function in the form of an absolutely convergent state integral which is invariant under shaped 3-2 Pachner moves and invariant with respect to shape gauge transformations generated by total dihedral angles around internal edges through the Neumann-Zagier Poisson bracket. Similarly to Turaev-Viro theory, the state variables live on edges of the triangulation but take their values on the whole real axis. The tetrahedral weight functions are composed of three hyperbolic gamma functions in a way that they enjoy a manifest tetrahedral symmetry. We conjecture that for shaped triangulations of closed 3-manifolds, our partition function is twice the absolute value squared of the partition function of Techmueller TQFT defined by Andersen and Kashaev. This is similar to the known relationship between the Turaev-Viro and the Witten-Reshetikhin-Turaev invariants of three manifolds. We also discuss interpretations of our construction in terms of three-dimensional supersymmetric field theories related to triangulated three-dimensional manifolds.
A TQFT of Tuarev-Viro type on shaped triangulations
A shaped triangulation is a finite triangulation of an oriented pseudo three manifold where each tetrahedron carries dihedral angles of an ideal hyberbolic tetrahedron. To each shaped triangulation, we associate a quantum partition function in the form of an absolutely convergent state integral which is invariant under shaped 3-2 Pachner moves and invariant with respect to shape gauge transformations generated by total dihedral angles around internal edges through the Neumann-Zagier Poisson bracket. Similarly to Turaev-Viro theory, the state variables live on edges of the triangulation but take their values on the whole real axis. The tetrahedral weight functions are composed of three hyperbolic gamma functions in a way that they enjoy a manifest tetrahedral symmetry. We conjecture that for shaped triangulations of closed 3-manifolds, our partition function is twice the absolute value squared of the partition function of Techmueller TQFT defined by Andersen and Kashaev. This is similar to the known relationship between the Turaev-Viro and the Witten-Reshetikhin-Turaev invariants of three manifolds. We also discuss interpretations of our construction in terms of three-dimensional supersymmetric field theories related to triangulated three-dimensional manifolds.
Continuous phase transitions occur in a wide range of physical systems, and provide a context for the study of non-equilibrium dynamics and the formation of topological defects. The Kibble–Zurek (KZ) mechanism predicts the scaling of the resulting density of defects as a function of the quench rate through a critical point, and this can provide an estimate of the critical exponents of a phase transition. In this work, we extend our previous study of the miscible–immiscible phase transition of a binary Bose–Einstein condensate (BEC) composed of two hyperfine states in which the spin dynamics are confined to one dimension (Sabbatini et al 2011 Phys. Rev. Lett. 107 230402). The transition is engineered by controlling a Hamiltonian quench of the coupling amplitude of the two hyperfine states and results in the formation of a random pattern of spatial domains. Using the numerical truncated Wigner phase-space method, we show that in a ring BEC the number of domains formed in the phase transitions scales as predicted by the KZ theory. We also consider the same experiment performed with a harmonically trapped BEC, and investigate how the density inhomogeneity modifies the dynamics of the phase transition and the KZ scaling law for the number of domains. We then make use of the symmetry between inhomogeneous phase transitions in anisotropic systems, and an inhomogeneous quench in a homogeneous system, to engineer coupling quenches that allow us to quantify several aspects of inhomogeneous phase transitions. In particular, we quantify the effect of causality in the propagation of the phase transition front on the resulting formation of domain walls and find indications that the density of defects is determined during the impulse to adiabatic transition after the crossing of the critical point. (paper)
Triangulation of the Interstellar Magnetic Field
Schwadron, N. A.; Richardson, J. D.; Burlaga, L. F.; McComas, D. J.; Moebius, E.
2015-11-01
Determining the direction of the local interstellar magnetic field (LISMF) is important for understanding the heliosphere’s global structure, the properties of the interstellar medium, and the propagation of cosmic rays in the local galactic medium. Measurements of interstellar neutral atoms by Ulysses for He and by SOHO/SWAN for H provided some of the first observational insights into the LISMF direction. Because secondary neutral H is partially deflected by the interstellar flow in the outer heliosheath and this deflection is influenced by the LISMF, the relative deflection of H versus He provides a plane—the so-called B-V plane in which the LISMF direction should lie. Interstellar Boundary Explorer (IBEX) subsequently discovered a ribbon, the center of which is conjectured to be the LISMF direction. The most recent He velocity measurements from IBEX and those from Ulysses yield a B-V plane with uncertainty limits that contain the centers of the IBEX ribbon at 0.7-2.7 keV. The possibility that Voyager 1 has moved into the outer heliosheath now suggests that Voyager 1's direct observations provide another independent determination of the LISMF. We show that LISMF direction measured by Voyager 1 is >40° off from the IBEX ribbon center and the B-V plane. Taking into account the temporal gradient of the field direction measured by Voyager 1, we extrapolate to a field direction that passes directly through the IBEX ribbon center (0.7-2.7 keV) and the B-V plane, allowing us to triangulate the LISMF direction and estimate the gradient scale size of the magnetic field.
This paper examines the interrelationships between energy consumption, foreign direct investment and economic growth using dynamic panel data models in simultaneous-equations for a global panel consisting of 65 countries. The time component of our dataset is 1990–2011 inclusive. To make the panel data analysis more homogenous, we also investigate this interrelationship for a number of sub-panels which are constructed based on the income level of countries. In this way, we end up with three income panels; namely, high income, middle income, and low income panels. In the empirical part, we draw on the growth theory and augment the classical growth model, which consists of capital stock, labor force and inflation, with foreign direct investment and energy. Generally, we show mixed results about the interrelationship between energy consumption, FDI and economic growth. - Highlights: • We examine the energy–FDI–growth nexus for a global panel of 65 countries. • Dynamic simultaneous-equation panel data models are used to address this issue. • We also investigate this nexus for three sub-panels which are constructed based on the income level of countries. • We show mixed results about the interrelationship between the three variables
Xu, Fang-Fang; Han, Lu; He, Hong-Jian; Zhu, Yi-Hong; Zhong, Jian-Hui
2016-06-25
The effective connectivity of default mode network (DMN) and its change after taking methylphenidate (MPH) were investigated in this study based on resting-state functional magnetic resonance imaging. Dynamic causal modeling (DCM) was applied to compare the effective connectivity between the conditions of taking MPH and placebo for 18 healthy male volunteers. Started with the network structural basis provided by a recent literature, endogenous low frequency fluctuation signals (0.01-0.08 Hz) of each node of DMN were taken as the driving input, and thirty-two possible models were designed according to the modulation effect of MPH on different connections between nodes. Model fitting and Bayesian model selection were performed to find the winning model and corresponding parameters. Our results indicated that the effective connectivity from medial prefrontal cortex (MPFC) to posterior cingulated cortex (PCC), from left/right inferior parietal lobule (L/RIPL) to MPFC, and from RIPL to PCC were excitatory, whereas the connectivity from LIPL to PCC was inhibitory. Further t-test statistics on connectivity parameters found that MPH significantly reduced the link from RIPL to MPFC in DMN (t = 2.724, P = 0.016) and changed the weak excitatory state to inhibitory state. However, it had no significant effect on other connections. In all, our results demonstrated that MPH modulates the effective connectivity within DMN in resting state. PMID:27350198
Esker, P D; Nutter, F W
2003-02-01
ABSTRACT In order to better understand the epidemiology of the Stewart's disease of corn pathosystem, quantitative information concerning the temporal dynamics of the amount of pathogen inoculum present in the form of Pantoea stewartii-infested corn flea beetles (Chaetocnema pulicaria) is needed. Temporal changes in the proportion of P. stewartii-infested corn flea beetle populations were monitored by testing individual corn flea beetles for the presence of P. stewartii using a peroxidase-labeled, enzyme-linked immunosorbent assay. Approximately 90 corn flea beetles were collected each week from seven locations in Iowa from September 1998 through October 2000 using sweep nets. The proportion of P. stewartii-infested beetles at the end of the 1998 growing season ranged from 0.04 to 0.19. In spring 1999, the proportion of overwintering adult corn flea beetles infested with P. stewartii ranged from 0.10 to 0.11 and did not differ significantly from the previous fall based on chi(2). During the 1999 corn-growing season, the proportion of infested corn flea beetles ranged from 0.04 to 0.86, with the highest proportions occurring in August. In fall 1999, the proportion of beetles infested with P. stewartii ranged from 0.20 to 0.77. In spring 2000, the proportion of overwintering adult corn flea beetles infested with P. stewartii ranged from 0.08 to 0.30; these proportions were significantly lower than the proportions observed in fall 1999 at Ames, Chariton, and Nashua. During the 2000 corn-growing season, the proportion of P. stewartii-infested corn flea beetles ranged from 0.08 to 0.53, and the highest observed proportions again occurred in August. Corn flea beetle populations sampled in late fall 2000 had proportions of infested beetles ranging from 0.08 to 0.20. This is the first study to quantify the temporal population dynamics of P. stewartii-infested C. pulicaria populations in hybrid corn and provides new quantitative information that should be useful in
Aberle-Grasse John
2010-07-01
Full Text Available Abstract Background Public health triangulation is a process for reviewing, synthesising and interpreting secondary data from multiple sources that bear on the same question to make public health decisions. It can be used to understand the dynamics of HIV transmission and to measure the impact of public health programs. While traditional intervention research and metaanalysis would be ideal sources of information for public health decision making, they are infrequently available, and often decisions can be based only on surveillance and survey data. Methods The process involves examination of a wide variety of data sources and both biological, behavioral and program data and seeks input from stakeholders to formulate meaningful public health questions. Finally and most importantly, it uses the results to inform public health decision-making. There are 12 discrete steps in the triangulation process, which included identification and assessment of key questions, identification of data sources, refining questions, gathering data and reports, assessing the quality of those data and reports, formulating hypotheses to explain trends in the data, corroborating or refining working hypotheses, drawing conclusions, communicating results and recommendations and taking public health action. Results Triangulation can be limited by the quality of the original data, the potentials for ecological fallacy and "data dredging" and reproducibility of results. Conclusions Nonetheless, we believe that public health triangulation allows for the interpretation of data sets that cannot be analyzed using meta-analysis and can be a helpful adjunct to surveillance, to formal public health intervention research and to monitoring and evaluation, which in turn lead to improved national strategic planning and resource allocation.
Davidson, Russell
2013-01-01
The understanding of causal chains and mechanisms is an essential part of any scientific activity that aims at better explanation of its subject matter, and better understanding of it. While any account of causality requires that a cause should precede its effect, accounts of causality inphysics are complicated by the fact that the role of time in current theoretical physics has evolved very substantially throughout the twentieth century. In this article, I review the status of time and causa...
Spin foam models as energetic causal sets
Cortês, Marina; Smolin, Lee
2016-04-01
Energetic causal sets are causal sets endowed by a flow of energy-momentum between causally related events. These incorporate a novel mechanism for the emergence of space-time from causal relations [M. Cortês and L. Smolin, Phys. Rev. D 90, 084007 (2014); Phys. Rev. D 90, 044035 (2014)]. Here we construct a spin foam model which is also an energetic causal set model. This model is closely related to the model introduced in parallel by Wolfgang Wieland in [Classical Quantum Gravity 32, 015016 (2015)]. What makes a spin foam model also an energetic causal set is Wieland's identification of new degrees of freedom analogous to momenta, conserved at events (or four-simplices), whose norms are not mass, but the volume of tetrahedra. This realizes the torsion constraints, which are missing in previous spin foam models, and are needed to relate the connection dynamics to those of the metric, as in general relativity. This identification makes it possible to apply the new mechanism for the emergence of space-time to a spin foam model. Our formulation also makes use of Markopoulou's causal formulation of spin foams [arXiv:gr-qc/9704013]. These are generated by evolving spin networks with dual Pachner moves. This endows the spin foam history with causal structure given by a partial ordering of the events which are dual to four-simplices.
Causality in Europeanization Research
Lynggaard, Kennet
2012-01-01
Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours to......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the...
Algorithms for Sampling 3-Orientations of Planar Triangulations
Miracle, Sarah; Streib, Amanda Pascoe; Tetali, Prasad
2012-01-01
Given a planar triangulation, a 3-orientation is an orientation of the internal edges so all internal vertices have out-degree three. Each 3-orientation gives rise to a unique edge coloring known as a Schnyder wood that has proven powerful for various computing and combinatorics applications. We consider natural Markov chains for sampling uniformly from the set of 3-orientations. First, we study a "triangle-reversing" chain on the space of 3-orientations of a fixed triangulation that reverses the orientation of the edges around a triangle in each move. It was shown previously that this chain connects the state space and we show that (i) when restricted to planar triangulations of maximum degree six, the Markov chain is rapidly mixing, and (ii) there exists a triangulation with high degree on which this Markov chain mixes slowly. Next, we consider an "edge-flipping" chain on the larger state space consisting of 3-orientations of all planar triangulations on a fixed number of vertices. It was also shown previou...
Causality in 3D Massive Gravity Theories
Edelstein, Jose D; Kilicarslan, Ercan; Leoni, Matias; Tekin, Bayram
2016-01-01
We study the constraints coming from local causality requirement in various 2+1 dimensional dynamical theories of gravity. In Topologically Massive Gravity, with a single parity noninvariant massive degree of freedom, and in New Massive Gravity, with two massive spin-$2$ degrees of freedom, causality and unitarity are compatible with each other and they both require the Newton's constant to be negative. In their extensions, such as the Born-Infeld gravity and the minimal massive gravity the situation is similar and quite different from their higher dimensional counterparts, such as quadratic (e.g., Einstein-Gauss-Bonnet) or cubic theories, where causality and unitarity are in conflict.
Triangulation of Needs Analysis in English for Tourism Purposes
Aleksandar Tonić
2010-05-01
Full Text Available The article presents the results of my research in English for Tourism Purposes, a branch of English Language Teaching which is still relatively underdeveloped and which, in Slovenia, has been rather scarcely researched and studied. The base for the research is triangulation, the latest procedure used in the planning and realization of needs analyses. It is more reliable than informal crosschecking as it makes use of multiple sources and/ or methods of acquiring information. The research thus outlines an overview of the basics of English for Specific Purposes, illustrating and stressing the use of triangulation, which has never before been used in similar Slovenian researches. Learners, teachers and domain experts are the sources used; methods are questionnaire and interview. In conclusion, the importance of using triangulation in Needs Analysis is commented upon, the reliability of study results is substantiated and grounds for further studies in English for Tourism Purposes in Slovenia are set.
Musgrove, Donald R; Eberly, Lynn E; Klimes-Dougan, Bonnie; Basgoze, Zeynep; Thomas, Kathleen M; Mueller, Bryon A; Houri, Alaa; Lim, Kelvin O; Cullen, Kathryn R
2015-12-01
Major depressive disorder (MDD) is a significant contributor to lifetime disability and frequently emerges in adolescence, yet little is known about the neural mechanisms of MDD in adolescents. Dynamic causal modeling (DCM) analysis is an innovative tool that can shed light on neural network abnormalities. A DCM analysis was conducted to test several frontolimbic effective connectivity models in 27 adolescents with MDD and 21 healthy adolescents. The best neural model for each person was identified using Bayesian model selection. The findings revealed that the two adolescent groups fit similar optimal neural models. The best across-groups model was then used to infer upon both within-group and between-group tests of intrinsic and modulation parameters of the network connections. First, for model validation, within-group tests revealed robust evidence for bottom-up connectivity, but less evidence for strong top-down connectivity in both groups. Second, we tested for differences between groups on the validated parameters of the best model. This revealed that adolescents with MDD had significantly weaker bottom-up connectivity in one pathway, from amygdala to sgACC (p=0.008), than healthy controls. This study provides the first examination of effective connectivity using DCM within neural circuitry implicated in emotion processing in adolescents with MDD. These findings aid in advancing understanding the neurobiology of early-onset MDD during adolescence and have implications for future research investigating how effective connectivity changes across contexts, with development, over the course of the disease, and after intervention. PMID:26050933
Gian Paolo Beretta
2006-09-01
Full Text Available
We overview the main features of the general equation of motion that completes the Gyftopoulos-Hatsopoulos unified theory of mechanics and thermodynamics with a quantal law of causal evolution that entails relaxation towards stable equilibrium for any non-equilibrium state, no matter how far from thermodynamic equilibrium. We illustrate with numerical examples the behavior of the equation of motion by discussing spontaneous energy redistribution within an isolated, closed system composed of non-interacting identical particles with energy levels ei and i = 1, 2,…, N. For this system the time-dependent occupation probabilities pi(t obey the nonlinear rate equations which include functions of the pi(t’s that maintain invariant the mean energy and the normalization condition. The entropy is a non-decreasing function of time until the initially nonzero occupation probabilities reach a Boltzmann-like canonical distribution over the occupied energy eigenstates. Initially zero occupation probabilities, instead, remain zero at all times. The solutions of the rate equations are unique and well-defined for arbitrary initial conditions pi(0 and for all times, -∞
A set of spatially homogeneous and isotropic cosmological geometries generated by a class of non-perfect is investigated fluids. The irreversibility if this system is studied in the context of causal thermodynamics which provides a useful mechanism to conform to the non-violation of the causal principle. (author)
Causality in Classical Electrodynamics
Savage, Craig
2012-01-01
Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…
Nielsen, Max; Jensen, Frank; Setälä, Jari;
2011-01-01
to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological......This article focuses on causality in demand. A methodology where causality is imposed and tested within an empirical co-integrated demand model, not prespecified, is suggested. The methodology allows different causality of different products within the same demand system. The methodology is applied...... implication is that more explicit focus on causality in demand analyses provides improved information. The results suggest that frozen trout forms part of a large European whitefish market, where prices of fresh trout are formed on a relatively separate market. Redfish is a substitute on both markets. The...
Causality and Composite Structure
Joglekar, Satish D
2007-01-01
We study the question of whether a composite structure of elementary particles, with a length scale $1/\\Lambda$, can leave observable effects of non-locality and causality violation at higher energies (but $\\lesssim \\Lambda$). We formulate a model-independent approach based on Bogoliubov-Shirkov formulation of causality. We analyze the relation between the fundamental theory (of finer constituents) and the derived theory (of composite particles). We assume that the fundamental theory is causal and formulate a condition which must be fulfilled for the derived theory to be causal. We analyze the condition and exhibit possibilities which fulfil and which violate the condition. We make comments on how causality violating amplitudes can arise.
Thomas eWidlok
2014-11-01
Full Text Available Cognitive Scientists interested in causal cognition increasingly search for evidence from non-WEIRD people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.
Research on pavement roughness based on the laser triangulation
Chen, Wenxue; Ni, Zhibin; Hu, Xinhan; Lu, Xiaofeng
2016-06-01
Pavement roughness is one of the most important factors for appraising highway construction. In this paper, we choose the laser triangulation to measure pavement roughness. The principle and configuration of laser triangulation are introduced. Based on this technology, the pavement roughness of a road surface is measured. The measurement results are given in this paper. The measurement range of this system is 50 μm. The measurement error of this technology is analyzed. This technology has an important significance to appraise the quality of highway after completion of the workload.
Digital aerial-triangulation system on personal computers
Tseng, Yi-Hsing; Chang, Shau-Yen
1994-08-01
This paper demonstrates a prototype of a PC-based digital aerial-triangulation system (PC- DATS). The system takes all of the procedures of aerial triangulation and is constructed by five working modules: preparation, interior orientation, tie point measurement, target point measurement, and bundle adjustment. All of the modules are integrated on the platform Microsoft-Windows. A test block containing 15 photos was processed by using the system. The operation was quite smooth, and the adjustment result shows an accuracy of about 0.3 pixel in average. The success of this proto-DATS was quite encouraging.
Degree-Regular Triangulations of Torus and Klein Bottle-Erratum
Basudeb Datta; Ashish Kumar Upadhyay
2005-08-01
A triangulation of a connected closed surface is called weakly regular if the action of its automorphism group on its vertices is transitive. A triangulation of a connected closed surface is called degree-regular if each of its vertices have the same degree. Clearly, a weakly regular triangulation is degree-regular. In [8], Lutz has classified all the weakly regular triangulations on at most 15 vertices. In [5], Datta and Nilakantan have classified all the degree-regular triangulations of closed surfaces on at most 11 vertices. In this article, we have proved that any degree-regular triangulation of the torus is weakly regular. We have shown that there exists an -vertex degree-regular triangulation of the Klein bottle if and only if is a composite number ≥ 9. We have constructed two distinct -vertex weakly regular triangulations of the torus for each ≥ 12 and a (4+2)-vertex weakly regular triangulation of the Klein bottle for each ≥ 2. For 12 ≤ ≤ 15, we have classified all the -vertex degree-regular triangulations of the torus and the Klein bottle. There are exactly 19 such triangulations, 12 of which are triangulations of the torus and remaining 7 are triangulations of the Klein bottle. Among the last 7, only one is weakly regular.
Satisfying states of triangulations of a convex n-gon
Jiménez, Andrea; Loebl, Martin
2009-01-01
In this work we count the number of satisfying states of triangulations of a convex n-gon using the transfer matrix method. We show an exponential (in n) lower bound. We also give the exact formula for the number of satisfying states of a strip of triangles.
Mutating loops and 2-cycles in 2-CY triangulated categories
Bertani-Økland, Marco Angel
2010-01-01
We derive an algorithm for mutating quivers of 2-CY tilted algebras that have loops and 2-cycles, under certain specific conditions. Further, we give the classification of the 2-CY tilted algebras coming from standard algebraic 2-CY triangulated categories with a finite number of indecomposables. These form a class of algebras that satisfy the setup for our mutation algorithm.
A Kinetic Triangulation Scheme for Moving Points in The Plane
Kaplan, Haim; Sharir, Micha
2010-01-01
We present a simple randomized scheme for triangulating a set $P$ of $n$ points in the plane, and construct a kinetic data structure which maintains the triangulation as the points of $P$ move continuously along piecewise algebraic trajectories of constant description complexity. Our triangulation scheme experiences an expected number of $O(n^2\\beta_{s+2}(n)\\log^2n)$ discrete changes, and handles them in a manner that satisfies all the standard requirements from a kinetic data structure: compactness, efficiency, locality and responsiveness. Here $s$ is the maximum number of times where any specific triple of points of $P$ can become collinear, $\\beta_{s+2}(q)=\\lambda_{s+2}(q)/q$, and $\\lambda_{s+2}(q)$ is the maximum length of Davenport-Schinzel sequences of order $s+2$ on $n$ symbols. Thus, compared to the previous solution of Agarwal et al.~\\cite{AWY}, we achieve a (slightly) improved bound on the number of discrete changes in the triangulation. In addition, we believe that our scheme is simpler to implemen...
Wuthrich, Christian
2015-01-01
Unlike the relativity theory it seeks to replace, causal set theory has been interpreted to leave space for a substantive, though perhaps 'localized', form of 'becoming'. The possibility of fundamental becoming is nourished by the fact that the analogue of Stein's theorem from special relativity does not hold in causal set theory. Despite this, we find that in many ways, the debate concerning becoming parallels the well-rehearsed lines it follows in the domain of relativity. We present, however, some new twists and challenges. In particular, we show that a novel and exotic notion of becoming is compatible with causal sets. In contrast to the 'localized' becoming considered compatible with the dynamics of causal set theory by its advocates, our novel kind of becoming, while not answering to the typical A-theoretic demands, is 'global' and objective.
An Algorithm Of Semi-Delaunay Triangulation Of Points Cloud Scattered On Surface
Jan Kucwaj
2014-01-01
The purpose of the paper is to generalize the Delaunay triangulation onto surfaces. A formal definition and appropriate algorithm are presented. Starting from plane domain Delaunay triangulation definition a theoretical approach is evolved which is a background for further considerations. It is proved that in case of plane surface the introduced Delaunay triangulation of surfaces is identical with classical Delaunay triangulation of plane domain. The proposed algorithm is implemented and nume...
Dynamic triangulations for efficient 3D simulation of granular materials
Ferrez, Jean-Albert; Liebling, Thomas M.
2007-01-01
Granular materials are omnipresent in many fields ranging from civil engineering to food, mining and pharmaceutical industries. Often considered a fourth state of matter, they exhibit specific phenomena such as segregation, arching effects, pattern formation, etc. Due to its potential capability of realistically rendering these behaviors, the Distinct Element Method (DEM) is a very enticing simulation technique. Indeed it makes it possible to analyze and observe phenomena that are barely if a...
Causal Inference and Causal Explanation with Background Knowledge
Meek, Christopher
2013-01-01
This paper presents correct algorithms for answering the following two questions; (i) Does there exist a causal explanation consistent with a set of background knowledge which explains all of the observed independence facts in a sample? (ii) Given that there is such a causal explanation what are the causal relationships common to every such causal explanation?
Optical Triangulation on Instationary Water Surfaces
Mulsow, C.; Maas, H.-G.; Hentschel, B.
2016-06-01
The measurement of water surfaces is a key task in the field of experimental hydromechanics. Established techniques are usually gauge-based and often come with a large instrumental effort and a limited spatial resolution. The paper shows a photogrammetric alternative based on the well-known laser light sheet projection technique. While the original approach is limited to surfaces with diffuse reflection properties, the developed technique is capable of measuring dynamically on reflecting instationary surfaces. Contrary to the traditional way, the laser line is not observed on the object. Instead, using the properties of water, the laser light is reflected on to a set of staggered vertical planes. The resulting laser line is observed by a camera and measured by subpixel operators. A calibration based on known still water levels provides the parameters for the translation of image space measurements into water level and gradient determination in dynamic experiments. As a side-effect of the principle of measuring the reflected laser line rather than the projected one, the accuracy can be improved by almost a factor two. In experiments a standard deviation of 0.03 mm for water level changes could be achieved. The measuring rate corresponds to the frame rate of the camera. A complete measuring system is currently under development for the Federal Waterways Engineering and Research Institute (BAW). This article shows the basic principle, potential and limitations of the method. Furthermore, several system variants optimised for different requirements are presented. Besides the geometrical models of different levels of complexity, system calibration procedures are described too. The applicability of the techniques and their accuracy potential are shown in several practical tests.
Causality and the Doppler Peaks
Turok, Neil
1996-01-01
Could cosmic structure have formed by the action of causal physics within the standard hot big bang, or was a prior period of inflation required? Recently there has been some discussion of whether causal sources could reproduce the pattern of Doppler peaks of the standard scale-invariant adiabatic theory. This paper gives a rigorous definition of causality, and a causal decomposition of a general source. I present an example of a simple causal source which mimics the standard adiabatic theory...
Biased causal inseparable game
Bhattacharya, Some Sankar
2015-01-01
Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...
Performance Evaluation of Triangulation Based Range Sensors
Monica Bordegoni
2010-07-01
Full Text Available The performance of 2D digital imaging systems depends on several factors related with both optical and electronic processing. These concepts have originated standards, which have been conceived for photographic equipment and bi-dimensional scanning systems, and which have been aimed at estimating different parameters such as resolution, noise or dynamic range. Conversely, no standard test protocols currently exist for evaluating the corresponding performances of 3D imaging systems such as laser scanners or pattern projection range cameras. This paper is focused on investigating experimental processes for evaluating some critical parameters of 3D equipment, by extending the concepts defined by the ISO standards to the 3D domain. The experimental part of this work concerns the characterization of different range sensors through the extraction of their resolution, accuracy and uncertainty from sets of 3D data acquisitions of specifically designed test objects whose geometrical characteristics are known in advance. The major objective of this contribution is to suggest an easy characterization process for generating a reliable comparison between the performances of different range sensors and to check if a specific piece of equipment is compliant with the expected characteristics.
A new insertion sequence for incremental Delaunay triangulation
Jian-Fei Liu; Jin-Hui Yan; S.H.Lo
2013-01-01
Incremental algorithm is one of the most popular procedures for constructing Delaunay triangulations (DTs).However,the point insertion sequence has a great impact on the amount of work needed for the construction of DTs.It affects the time for both point location and structure update,and hence the overall computational time of the triangulation algorithm.In this paper,a simple deterministic insertion sequence is proposed based on the breadth-first-search on a Kd-tree with some minor modifications for better performance.Using parent nodes as search-hints,the proposed insertion sequence proves to be faster and more stable than the Hilbert curve order and biased randomized insertion order (BRIO),especially for non-uniform point distributions over a wide range of benchmark examples.
RESEARCH ON ADAPTIVE DATA COMPRESSION METHOD FOR TRIANGULATED SURFACES
Wang Wen; Wu Shixiong; Chen Zichen
2004-01-01
NC code or STL file can be generated directly from measuring data in a fast reverse-engineering mode.Compressing the massive data from laser scanner is the key of the new mode.An adaptive compression method based on triangulated-surfaces model is put forward.Normal-vector angles between triangles are computed to find prime vertices for removal.Ring data structure is adopted to save massive data effectively.It allows the efficient retrieval of all neighboring vertices and triangles of a given vertices.To avoid long and thin triangles,a new re-triangulation approach based on normalized minimum-vertex-distance is proposed,in which the vertex distance and interior angle of triangle are considered.Results indicate that the compression method has high efficiency and can get reliable precision.The method can be applied in fast reverse engineering to acquire an optimal subset of the original massive data.
Discovery and problem solving: Triangulation as a weak heuristic
Rochowiak, Daniel
1987-01-01
Recently the artificial intelligence community has turned its attention to the process of discovery and found that the history of science is a fertile source for what Darden has called compiled hindsight. Such hindsight generates weak heuristics for discovery that do not guarantee that discoveries will be made but do have proven worth in leading to discoveries. Triangulation is one such heuristic that is grounded in historical hindsight. This heuristic is explored within the general framework of the BACON, GLAUBER, STAHL, DALTON, and SUTTON programs. In triangulation different bases of information are compared in an effort to identify gaps between the bases. Thus, assuming that the bases of information are relevantly related, the gaps that are identified should be good locations for discovery and robust analysis.
Experiences with systematic triangulation at the Global Environment Facility.
Carugi, Carlo
2016-04-01
Systematic triangulation may address common challenges in evaluation, such as the scarcity or unreliability of data, or the complexities of comparing and cross-checking evidence from diverse disciplines. Used to identify key evaluation findings, its application has proven to be effective in addressing the limitations encountered in country-level evaluation analysis conducted by the Independent Evaluation Office of the Global Environment Facility (GEF). These include the scarcity or unreliability of national statistics on environmental indicators and data series, especially in Least Developed Countries; challenges in evaluating the impacts of GEF projects; and inherent difficulties in defining the GEF portfolio of projects prior to the undertaking of the evaluation. In addition to responding to the need for further developing triangulation protocols, procedures and/or methodologies advocated by some authors, the approach offers a contribution to evaluation practice. This applies particularly to those evaluation units tasked with country-level evaluations in international organizations, facing similar constraints. PMID:26724715
Genus dependence of the number of (non-)orientable surface triangulations
Krüger, Benedikt; Mecke, Klaus
2016-04-01
Topological triangulations of orientable and nonorientable surfaces with arbitrary genus have important applications in quantum geometry, graph theory and statistical physics. However, until now, only the asymptotics for 2-spheres have been known analytically, and exact counts of triangulations are only available for both small genera and triangulations. We apply the Wang-Landau algorithm to calculate the number N (m ,h ) of triangulations for several orders of magnitude in system size m and type h (equals genus in orientable triangulations). We verify that the limit of the entropy density of triangulations is independent of genus and orientability and are able to determine the next-to-leading-order and the next-to-next-to-leading-order terms. We conjecture for the number of surface triangulations the asymptotic behavior N (m ,h )→(170.4 ±15.1 )hm-2 (h -1 )/5(256/27) m /2, which might guide a mathematician's proof for the exact asymptotics.
This paper investigated the short-run causal relationships and the long-run equilibrium relationships among carbon dioxide emissions, economic growth, technical efficiency, and industrial structure for three African countries. Using Bounds cointegration approach the result showed evidence of multiple long-run equilibrium relationships for Ghana and Senegal but a one-way long-run equilibrium relationship for Morocco. The result from the Toda and Yomamoto granger causality test showed a mix of bidirectional, unidirectional, and neutral relationships for all countries. Whilst in Senegal carbon dioxide emission was not found to be a limiting factor to economic growth; it was found to act as a limiting factor to economic growth in Morocco and Ghana. Lastly, the result from the variance decomposition analysis revealed that economic growth contributes largely to changes in future carbon dioxide emissions in Senegal and Morocco whilst in Ghana technical efficiency contributes largely to changes in future variations in carbon dioxide emissions. These results have important policy implications for these countries' energy efficiency systems. -- Highlights: ► A set of bidirectional and unidirectional causality relationships was found. ► CO2 acts as a limiting factor to growth in Ghana and Morocco but not in Senegal. ► Economic growth contributes largely to CO2 emissions in Senegal and Morocco. ► Technical efficiency contributes largely to CO2 emissions in Ghana.
The triangulated category of K-motives DK_(k)
Garkusha, Grigory; Panin, Ivan
2013-01-01
For any perfect field k a triangulated category of K-motives DK_(k) is constructed in the style of Voevodsky's construction of the category DM_(k). To each smooth k-variety X the K-motive is associated in the category DK_(k). Also, it is shown that K_n(X)=DK_(k)(M_K(X)[n],M_K(pt)), where K(X) is Quillen's K-theory of X.
A new approach to crushing 3-manifold triangulations
Burton, Benjamin A.
2012-01-01
The crushing operation of Jaco and Rubinstein is a powerful technique in algorithmic 3-manifold topology: it enabled the first practical implementations of 3-sphere recognition and prime decomposition of orientable manifolds, and it plays a prominent role in state-of-the-art algorithms for unknot recognition and testing for essential surfaces. Although the crushing operation will always reduce the size of a triangulation, it might alter its topology, and so it requires a careful theoretical a...
Assigning Wikipedia editing: Triangulation toward understanding university student engagement
Roth, Amy; Davis, Rochelle; Carver, Brian
2013-01-01
Professors across the United States participated in the first direct effort by the Wikimedia Foundation, the non-profit that supports Wikipedia, to engage the academic community and integrate Wikipedia into a class assignment. Three project participants, from different areas of study, conducted independent research into university student motivations for a Wikipedia assignment. We triangulate those data in this paper to describe how student motivations differ for a Wikipedia assignment from a...
Random discrete Morse theory and a new library of triangulations
Benedetti, Bruno; Lutz, Frank Hagen
2014-01-01
We introduce random discrete Morse theory as a computational scheme to measure the complexity of a triangulation. The idea is to try to quantify the frequency of discrete Morse matchings with few critical cells. Our measure will depend on the topology of the space, but also on how nicely the space...... easy” for testing algorithms based on discrete Morse theory. We propose a new library containing more complicated (and thus more meaningful) test examples....
Phase transition of triangulated spherical surfaces with elastic skeletons
Koibuchi, Hiroshi
2006-01-01
A first-order transition is numerically found in a spherical surface model with skeletons, which are linked to each other at junctions. The shape of the triangulated surfaces is maintained by skeletons, which have a one-dimensional bending elasticity characterized by the bending rigidity $b$, and the surfaces have no two-dimensional bending elasticity except at the junctions. The surfaces swell and become spherical at large $b$ and collapse and crumple at small $b$. These two phases are separ...
We discuss the geometry of trees endowed with a causal structure using the conventional framework of equilibrium statistical mechanics. We show how this ensemble is related to popular growing network models. In particular we demonstrate that on a class of afine attachment kernels the two models are identical but they can differ substantially for other choice of weights. We show that causal trees exhibit condensation even for asymptotically linear kernels. We derive general formulae describing the degree distribution, the ancestor--descendant correlation and the probability that a randomly chosen node lives at a given geodesic distance from the root. It is shown that the Hausdorff dimension dH of the causal networks is generically infinite. (author)
Bialas, Piotr
2003-10-01
We discuss the geometry of trees endowed with a causal structure using the conventional framework of equilibrium statistical mechanics. We show how this ensemble is related to popular growing network models. In particular we demonstrate that on a class of afine attachment kernels the two models are identical but they can differ substantially for other choice of weights. We show that causal trees exhibit condensation even for asymptotically linear kernels. We derive general formulae describing the degree distribution, the ancestor--descendant correlation and the probability that a randomly chosen node lives at a given geodesic distance from the root. It is shown that the Hausdorff dimension dH of the causal networks is generically infinite.
Causal inference in econometrics
Kreinovich, Vladik; Sriboonchitta, Songsak
2016-01-01
This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.
Fast triangulated vortex methods for the 2D Eulen equations
Russo, Giovanni; Strain, John A.
1994-04-01
Vortex methods for inviscid incompressible two-dimensional fluid flow are usually based on blob approximations. This paper presents a vortex method in which the vorticity is approximated by a piecewise polynomial interpolant on a Delaunay triangulation of the vortices. An efficient reconstruction of the Delaunay triangulation at each step makes the method accurate for long times. The vertices of the triangulation move with the fluid velocity, which is reconstructed from the vorticity via a simplified fast multipole method for the Biot-Savart law with a continuous source distribution. The initial distribution of vortices is constructed from the initial vorticity field by an adaptive approximation method which produces good accuracy even for discontinuous initial data. Numerical results show that the method is highly accurate over long time intervals. Experiments with single and multiple circular and elliptical rotating patches of both piecewise constant and smooth vorticity indicate that the method produces much smaller errors than blob methods with the same number of degrees of freedom, at little additional cost. Generalizations to domains with boundaries, viscous flow, and three space dimensions are discussed.
Refining a triangulation of a planar straight-line graph to eliminate large angles
Mitchell, S.A.
1993-05-13
Triangulations without large angles have a number of applications in numerical analysis and computer graphics. In particular, the convergence of a finite element calculation depends on the largest angle of the triangulation. Also, the running time of a finite element calculation is dependent on the triangulation size, so having a triangulation with few Steiner points is also important. Bern, Dobkin and Eppstein pose as an open problem the existence of an algorithm to triangulate a planar straight-line graph (PSLG) without large angles using a polynomial number of Steiner points. We solve this problem by showing that any PSLG with {upsilon} vertices can be triangulated with no angle larger than 7{pi}/8 by adding O({upsilon}{sup 2}log {upsilon}) Steiner points in O({upsilon}{sup 2} log{sup 2} {upsilon}) time. We first triangulate the PSLG with an arbitrary constrained triangulation and then refine that triangulation by adding additional vertices and edges. Some PSLGs require {Omega}({upsilon}{sup 2}) Steiner points in any triangulation achieving any largest angle bound less than {pi}. Hence the number of Steiner points added by our algorithm is within a log {upsilon} factor of worst case optimal. We note that our refinement algorithm works on arbitrary triangulations: Given any triangulation, we show how to refine it so that no angle is larger than 7{pi}/8. Our construction adds O(nm+nplog m) vertices and runs in time O(nm+nplog m) log(m+ p)), where n is the number of edges, m is one plus the number of obtuse angles, and p is one plus the number of holes and interior vertices in the original triangulation. A previously considered problem is refining a constrained triangulation of a simple polygon, where p = 1. For this problem we add O({upsilon}{sup 2}) Steiner points, which is within a constant factor of worst case optimal.
DIVE in the cosmic web: voids with Delaunay Triangulation from discrete matter tracer distributions
Zhao, Cheng; Liang, Yu; Kitaura, Francisco-Shu; Chuang, Chia-Hsun
2015-01-01
We present a novel parameter-free cosmological void finder (\\textsc{dive}, Delaunay TrIangulation Void findEr) based on Delaunay Triangulation (DT), which efficiently computes the empty spheres constrained by a discrete set of tracers. We define the spheres as DT voids, and describe their properties, including an universal density profile together with an intrinsic scatter. We apply this technique on 100 halo catalogues with volumes of 2.5\\,$h^{-1}$Gpc side each, with a bias and number density similar to the BOSS CMASS Luminous Red Galaxies, performed with the \\textsc{patchy} code. Our results show that there are two main species of DT voids, which can be characterised by the radius: they have different responses to halo redshift space distortions, to number density of tracers, and reside in different dark matter environments. Based on dynamical arguments using the tidal field tensor, we demonstrate that large DT voids are hosted in expanding regions, whereas the haloes used to construct them reside in collap...
DIVE in the cosmic web: voids with Delaunay triangulation from discrete matter tracer distributions
Zhao, Cheng; Tao, Charling; Liang, Yu; Kitaura, Francisco-Shu; Chuang, Chia-Hsun
2016-07-01
We present a novel parameter-free cosmological void finder (DIVE, Delaunay TrIangulation Void findEr) based on Delaunay Triangulation (DT), which efficiently computes the empty spheres constrained by a discrete set of tracers. We define the spheres as DT voids, and describe their properties, including a universal density profile together with an intrinsic scatter. We apply this technique on 100 halo catalogues with volumes of 2.5 h-1Gpc side each, with a bias and number density similar to the Baryon Oscillation Spectroscopic Survey CMASS luminous red galaxies, performed with the PATCHY code. Our results show that there are two main species of DT voids, which can be characterized by the radius: they have different responses to halo redshift space distortions, to number density of tracers, and reside in different dark matter environments. Based on dynamical arguments using the tidal field tensor, we demonstrate that large DT voids are hosted in expanding regions, whereas the haloes used to construct them reside in collapsing ones. Our approach is therefore able to efficiently determine the troughs of the density field from galaxy surveys, and can be used to study their clustering. We further study the power spectra of DT voids, and find that the bias of the two populations are different, demonstrating that the small DT voids are essentially tracers of groups of haloes.
Brustein, Ram
2000-01-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic space-like region. This "causal entropy bound", scaling as the square root of EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various "critical" situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso's holographic bound are stronger than Bekenstein's, while naive holography is too tight, and hence typically wrong.
Brustein, R; Veneziano, G
1999-01-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic space-like region. This "causal entropy bound", scaling as the square root of EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various "critical" situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso...
Triangulation of the neurocomputational architecture underpinning reading aloud.
Hoffman, Paul; Lambon Ralph, Matthew A; Woollams, Anna M
2015-07-14
The goal of cognitive neuroscience is to integrate cognitive models with knowledge about underlying neural machinery. This significant challenge was explored in relation to word reading, where sophisticated computational-cognitive models exist but have made limited contact with neural data. Using distortion-corrected functional MRI and dynamic causal modeling, we investigated the interactions between brain regions dedicated to orthographic, semantic, and phonological processing while participants read words aloud. We found that the lateral anterior temporal lobe exhibited increased activation when participants read words with irregular spellings. This area is implicated in semantic processing but has not previously been considered part of the reading network. We also found meaningful individual differences in the activation of this region: Activity was predicted by an independent measure of the degree to which participants use semantic knowledge to read. These characteristics are predicted by the connectionist Triangle Model of reading and indicate a key role for semantic knowledge in reading aloud. Premotor regions associated with phonological processing displayed the reverse characteristics. Changes in the functional connectivity of the reading network during irregular word reading also were consistent with semantic recruitment. These data support the view that reading aloud is underpinned by the joint operation of two neural pathways. They reveal that (i) the ATL is an important element of the ventral semantic pathway and (ii) the division of labor between the two routes varies according to both the properties of the words being read and individual differences in the degree to which participants rely on each route. PMID:26124121
Hvorecký, Juraj
2012-01-01
Roč. 19, Supp.2 (2012), s. 64-69. ISSN 1335-0668 R&D Projects: GA ČR(CZ) GAP401/12/0833 Institutional support: RVO:67985955 Keywords : conciousness * free will * determinism * causality Subject RIV: AA - Philosophy ; Religion
Wu, Huayi; Guan, Xuefeng; Gong, Jianya
2011-09-01
This paper presents a robust parallel Delaunay triangulation algorithm called ParaStream for processing billions of points from nonoverlapped block LiDAR files. The algorithm targets ubiquitous multicore architectures. ParaStream integrates streaming computation with a traditional divide-and-conquer scheme, in which additional erase steps are implemented to reduce the runtime memory footprint. Furthermore, a kd-tree-based dynamic schedule strategy is also proposed to distribute triangulation and merging work onto the processor cores for improved load balance. ParaStream exploits most of the computing power of multicore platforms through parallel computing, demonstrating qualities of high data throughput as well as a low memory footprint. Experiments on a 2-Way-Quad-Core Intel Xeon platform show that ParaStream can triangulate approximately one billion LiDAR points (16.4 GB) in about 16 min with only 600 MB physical memory. The total speedup (including I/O time) is about 6.62 with 8 concurrent threads.
Bulk viscous cosmology with causal transport theory
We consider cosmological scenarios originating from a single imperfect fluid with bulk viscosity and apply Eckart's and both the full and the truncated Müller-Israel-Stewart's theories as descriptions of the non-equilibrium processes. Our principal objective is to investigate if the dynamical properties of Dark Matter and Dark Energy can be described by a single viscous fluid and how such description changes when a causal theory (Müller-Israel-Stewart's, both in its full and truncated forms) is taken into account instead of Eckart's non-causal one. To this purpose, we find numerical solutions for the gravitational potential and compare its behaviour with the corresponding ΛCDM case. Eckart's and the full causal theory seem to be disfavoured, whereas the truncated theory leads to results similar to those of the ΛCDM model for a bulk viscous speed in the interval 10−11 || cb2 ∼−8
Quantum objects as elementary units of causality and locality
Diel, Hans H
2016-01-01
The author's attempt to construct a local causal model of quantum theory (QT) that includes quantum field theory (QFT) resulted in the identification of "quantum objects" as the elementary units of causality and locality. Quantum objects are collections of particles (including single particles) whose collective dynamics and measurement results can only be described by the laws of QT and QFT. Local causal models of quantum objects' internal dynamics are not possible if a locality is understood as a space-point locality. Within quantum objects, state transitions may occur which instantly affect the whole quantum object. The identification of quantum objects as the elementary units of causality and locality has two primary implications for a causal model of quantum objects: (1) quantum objects run autonomously with system-state update frequencies based on their local proper times and with either no or minimal dependency on external parameters. (2) The laws of physics that describe global (but relativistic) inter...
Triangulations of 3-manifolds, hyperbolic relative handlebodies, and Dehn filling
Costantino, Francois; Frigerio, Roberto; Martelli, Bruno; Petronio, Carlo
2004-01-01
We establish a bijective correspondence between the set T(n) of 3-dimensional triangulations with n tetrahedra and a certain class H(n) of relative handlebodies (i.e. handlebodies with boundary loops, as defined by Johannson) of genus n+1. We show that the manifolds in H(n) are hyperbolic (with geodesic boundary, and cusps corresponding to the loops), have least possible volume, and simplest boundary loops. Mirroring the elements of H(n) in their geodesic boundary we obtain a class D(n) of cu...
Triangulation of 3D Surfaces Recovered from STL Grids
D. Rypl
2004-01-01
Full Text Available In the present paper, an algorithm for the discretization of parametric 3D surfaces has been extended to the family of discrete surfaces represented by stereolithography (STL grids. The STL file format, developed for the rapid prototyping industry, is an attractive alternative to surface representation in solid modeling. Initially, a boundary representation is constructed from the STL file using feature recognition. Then a smooth surface is recovered over the original STL grid using an interpolating subdivision procedure. Finally, the reconstructed surface is subjected to the triangulation accomplished using the advancing front technique operating directly on the surface. The capability of the proposed methodology is illustrated on an example.
Detecting genus in vertex links for the fast enumeration of 3-manifold triangulations
Burton, Benjamin A.
2011-01-01
Enumerating all 3-manifold triangulations of a given size is a difficult but increasingly important problem in computational topology. A key difficulty for enumeration algorithms is that most combinatorial triangulations must be discarded because they do not represent topological 3-manifolds. In this paper we show how to preempt bad triangulations by detecting genus in partially-constructed vertex links, allowing us to prune the enumeration tree substantially. The key idea is to manipulate th...
Tachyon Kinematics and causality
The chronological order of the events along a space-like path is not invariant under Lorentz transformations, as wellknown. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stuckelberg-Feynman switching procedure (SWP) has been invoked as the suitable tool to eliminate those anomalies. The application of the SWP does eliminate the motions backwards in time, but interchanges the roles of source and dector. This fact triggered the proposal of a host of causal paradoxes. Till now, however, it has not been recognized that such paradoxes can be sensibly discussed (and completely solved, at least in microphysics) only after having properly developed the tachyon relativistic mechanics. We start by showing how to apply the SWP, both in the case of ordiry Special Relativity, and in the case with tachyons. Then, we carefully exploit the kinematics of the tachyon-exchange between to (ordinary) bodies. Being finally able to tackle the tachyon-causality problem, we successively solve the paradoxes: (i) by Tolman-Regge; (ii) by Pirani; (iii) by Edmonds; (iv) by Bell. At last, we discuss a further, new paradox associated with the transmission of signals by modulated tachyon beams
Liang, X San
2014-01-01
Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...
Causality in physiological signals.
Müller, Andreas; Kraemer, Jan F; Penzel, Thomas; Bonnemeier, Hendrik; Kurths, Jürgen; Wessel, Niels
2016-05-01
Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The
Revisiting Causality in Markov Chains
Shojaee, Abbas
2016-01-01
Identifying causal relationships is a key premise of scientific research. The growth of observational data in different disciplines along with the availability of machine learning methods offers the possibility of using an empirical approach to identifying potential causal relationships, to deepen our understandings of causal behavior and to build theories accordingly. Conventional methods of causality inference from observational data require a considerable length of time series data to capture cause-effect relationship. We find that potential causal relationships can be inferred from the composition of one step transition rates to and from an event. Also known as Markov chain, one step transition rates are a commonly available resource in different scientific disciplines. Here we introduce a simple, effective and computationally efficient method that we termed 'Causality Inference using Composition of Transitions CICT' to reveal causal structure with high accuracy. We characterize the differences in causes,...
The finite body triangulation: algorithms, subgraphs, homogeneity estimation and application.
Carson, Cantwell G; Levine, Jonathan S
2016-09-01
The concept of a finite body Dirichlet tessellation has been extended to that of a finite body Delaunay 'triangulation' to provide a more meaningful description of the spatial distribution of nonspherical secondary phase bodies in 2- and 3-dimensional images. A finite body triangulation (FBT) consists of a network of minimum edge-to-edge distances between adjacent objects in a microstructure. From this is also obtained the characteristic object chords formed by the intersection of the object boundary with the finite body tessellation. These two sets of distances form the basis of a parsimonious homogeneity estimation. The characteristics of the spatial distribution are then evaluated with respect to the distances between objects and the distances within them. Quantitative analysis shows that more physically representative distributions can be obtained by selecting subgraphs, such as the relative neighbourhood graph and the minimum spanning tree, from the finite body tessellation. To demonstrate their potential, we apply these methods to 3-dimensional X-ray computed tomographic images of foamed cement and their 2-dimensional cross sections. The Python computer code used to estimate the FBT is made available. Other applications for the algorithm - such as porous media transport and crack-tip propagation - are also discussed. PMID:26917441
Computing 2D constrained delaunay triangulation using the GPU.
Qi, Meng; Cao, Thanh-Tung; Tan, Tiow-Seng
2013-05-01
We propose the first graphics processing unit (GPU) solution to compute the 2D constrained Delaunay triangulation (CDT) of a planar straight line graph (PSLG) consisting of points and edges. There are many existing CPU algorithms to solve the CDT problem in computational geometry, yet there has been no prior approach to solve this problem efficiently using the parallel computing power of the GPU. For the special case of the CDT problem where the PSLG consists of just points, which is simply the normal Delaunay triangulation (DT) problem, a hybrid approach using the GPU together with the CPU to partially speed up the computation has already been presented in the literature. Our work, on the other hand, accelerates the entire computation on the GPU. Our implementation using the CUDA programming model on NVIDIA GPUs is numerically robust, and runs up to an order of magnitude faster than the best sequential implementations on the CPU. This result is reflected in our experiment with both randomly generated PSLGs and real-world GIS data having millions of points and edges. PMID:23492377
a Modified Method for Image Triangulation Using Inclined Angles
Alsadik, Bashar
2016-06-01
The ongoing technical improvements in photogrammetry, Geomatics, computer vision (CV), and robotics offer new possibilities for many applications requiring efficient acquisition of three-dimensional data. Image orientation is one of these important techniques in many applications like mapping, precise measurements, 3D modeling and navigation. Image orientation comprises three main techniques of resection, intersection (triangulation) and relative orientation, which are conventionally solved by collinearity equations or by using projection and fundamental matrices. However, different problems still exist in the state - of -the -art of image orientation because of the nonlinearity and the sensitivity to proper initialization and spatial distribution of the points. In this research, a modified method is presented to solve the triangulation problem using inclined angles derived from the measured image coordinates and based on spherical trigonometry rules and vector geometry. The developed procedure shows promising results compared to collinearity approach and to converge to the global minimum even when starting from far approximations. This is based on the strong geometric constraint offered by the inclined angles that are enclosed between the object points and the camera stations. Numerical evaluations with perspective and panoramic images are presented and compared with the conventional solution of collinearity equations. The results show the efficiency of the developed model and the convergence of the solution to global minimum even with improper starting values.
Eccentric error and compensation in rotationally symmetric laser triangulation
Wang Lei; Gao Jun; Wang Xiaojia; Johannes Eckstein; Peter Ott
2007-01-01
Rotationally symmetric triangulation (RST) sensor has more flexibility and less uncertainty limits becauseof the abaxial rotationally symmetric optical system.But if the incident laser is eccentric,the symmetry of the imagewill descend,and it will result in the eccentric error especially when some part of the imaged ring is blocked.Themodel of rotationally symmetric triangulation that meets the Schimpflug condition is presented in this paper.The errorfrom eccentric incident 1aser is analysed.It iS pointed out that the eccentric error is composed of two parts.one is acosine in circumference and proportional to the eccentric departure factor,and the other is a much smaller quadricfactor of the departure.When the ring is complete,the first error factor is zero because it is integrated in whole ring,but if some part of the ring iS blocked,the first factor will be the main error.Simulation verifies the result of the a-nalysis.At last,a compensation method to the error when some part of the ring is lost is presented based on neuralnetwork.The results of experiment show that the compensation will make the absolute maximum error descend tohalf,and the standard deviation of error descends to 1/3.
Quantum information causality.
Pitalúa-García, Damián
2013-05-24
How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combines the quantum teleportation and superdense coding protocols with a task that has classical inputs. PMID:23745844
Inferring deterministic causal relations
Daniusis, Povilas; Janzing, Dominik; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard
2012-01-01
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the ...
A comprehensive study on GPS-assisted aerial triangulation
Ebadi, Hamid
Aerial Triangulation (AT) has been used for mapping purposes for a long time to provide 3D coordinates of object points on the ground. This technique uses series of overlapping photographs, and some control points, in order to establish the relationship between the image coordinate system and object coordinate system. In the process of bundle block adjustment, image coordinate observations and coordinates of the ground control points are simultaneously adjusted and the exterior orientation parameters, as well as the ground coordinates of all tie and pass points, are estimated. One of the biggest challenges in AT is to reduce the number of control points. One effective way is to directly measure the exterior orientation parameters of the camera at the time of exposure. Airborne kinematic GPS (Global Positioning System) provides a means of determining the position of the aerial camera at each instant of exposure. The combined GPS-photogrammetric block adjustment takes advantage of weighted GPS observations, which significantly reduces the number of ground control points needed in a conventional block adjustment. A comprehensive software package, GAP (General Adjustment Program), was developed in this research to effectively integrate and adjust GPS, geodetic, and photogrammetric observations. Optimization of the GPS-photogrammetric bundle block adjustments for both simulated large scale mapping and real medium scale mapping was carried out. Aspects of reliability, and precision, as well as practical considerations, for an airborne GPS-photogrammetry system were also investigated. GPS coordinates of the camera exposure stations do not permit recovery of the roll angle of the aircraft in a GPS single strip triangulation. Therefore, ground control points are still required in addition to the GPS coordinates of exposure stations to overcome this problem, and to eliminate singularity of the normal matrix in the least squares adjustment. A new technique for GPS single
Granger-Causality Maps of Diffusion Processes
Wahl, B.; Feudel, U.; Hlinka, Jaroslav; Wächter, M.; Peinke, J.; Freund, J.A.
2016-01-01
Roč. 93, č. 2 (2016), 022213/1-022213/9. ISSN 1539-3755 R&D Projects: GA ČR GA13-23940S; GA MZd(CZ) NV15-29835A Institutional support: RVO:67985807 Keywords : Granger causality * stochastic process * diffusion process * nonlinear dynamical systems Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.288, year: 2014
Representation and reasoning: a causal model approach
Nikolic, M.
2014-01-01
How do we represent our world and how do we use these representations to reason about it? The three studies reported in this thesis explored different aspects of the answer to this question. Even though these investigations offered diverse angles, they all originated from the same psychological theory of representation and reasoning. This is the idea that people represent the world and reason about it by constructing dynamic qualitative causal networks. The first study investigated how mock j...
World oil and agricultural commodity prices: Evidence from nonlinear causality
The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies. - Research highlights: → This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). → The linear and nonlinear cointegration and causality methods are carried out. → The linear causality analysis supports evidence on the neutrality hypothesis. → The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.
Causal inference based on counterfactuals
Höfler M
2005-09-01
Full Text Available Abstract 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.
Experimental test of nonlocal causality.
Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro
2016-08-01
Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045
Relationship of causal effects in a causal chain and related inference
GENG; Zhi; HE; Yangbo; WANG; Xueli
2004-01-01
This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.
A novel spatial clustering algorithm based on Delaunay triangulation
Yang, Xiankun; Cui, Weihong
2008-12-01
Exploratory data analysis is increasingly more necessary as larger spatial data is managed in electro-magnetic media. Spatial clustering is one of the very important spatial data mining techniques. So far, a lot of spatial clustering algorithms have been proposed. In this paper we propose a robust spatial clustering algorithm named SCABDT (Spatial Clustering Algorithm Based on Delaunay Triangulation). SCABDT demonstrates important advantages over the previous works. First, it discovers even arbitrary shape of cluster distribution. Second, in order to execute SCABDT, we do not need to know any priori nature of distribution. Third, like DBSCAN, Experiments show that SCABDT does not require so much CPU processing time. Finally it handles efficiently outliers.
Skin lesion image segmentation using Delaunay Triangulation for melanoma detection.
Pennisi, Andrea; Bloisi, Domenico D; Nardi, Daniele; Giampetruzzi, Anna Rita; Mondino, Chiara; Facchiano, Antonio
2016-09-01
Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presented. Delaunay Triangulation is used to extract a binary mask of the lesion region, without the need of any training stage. A quantitative experimental evaluation has been conducted on a publicly available database, by taking into account six well-known state-of-the-art segmentation methods for comparison. The results of the experimental analysis demonstrate that the proposed approach is highly accurate when dealing with benign lesions, while the segmentation accuracy significantly decreases when melanoma images are processed. This behavior led us to consider geometrical and color features extracted from the binary masks generated by our algorithm for classification, achieving promising results for melanoma detection. PMID:27215953
Exact and approximate computations of watersheds on triangulated terrains
Tsirogiannis, Konstantinos; de Berg, Mark
2011-01-01
The natural way of modeling water flow on a triangulated terrain is to make the fundamental assumption that water follows the direction of steepest descent (dsd). However, computing watersheds and other flow-related structures according to the dsd model in an exact manner is difficult: the dsd...... model implies that water does not necessarily follow terrain edges, which makes designing exact algorithms difficult and causes robustness problems when implementing them. As a result, existing software implementations for computing watersheds are inexact: they either assume a simplified flow model or...... they perform computations using inexact arithmetic, which leads to inexact and sometimes inconsistent results. We perform a detailed study of various issues concerning the exact or approximate computation of watersheds according to the dsd model. Our main contributions are the following. • We provide...
Relativistic hydrodynamics - causality and stability
Ván, P.; Biró, T. S.
2007-01-01
Causality and stability in relativistic dissipative hydrodynamics are important conceptual issues. We argue that causality is not restricted to hyperbolic set of differential equations. E.g. heat conduction equation can be causal considering the physical validity of the theory. Furthermore we propose a new concept of relativistic internal energy that clearly separates the dissipative and non-dissipative effects. We prove that with this choice we remove all known instabilities of the linear re...
A REST Service for Triangulation of Point Sets Using Oriented Matroids
José Antonio Valero Medina
2014-05-01
Full Text Available This paper describes the implementation of a prototype REST service for triangulation of point sets collected by mobile GPS receivers. The first objective of this paper is to test functionalities of an application, which exploits mobile devices’ capabilities to get data associated with their spatial location. A triangulation of a set of points provides a mechanism through which it is possible to produce an accurate representation of spatial data. Such triangulation may be used for representing surfaces by Triangulated Irregular Networks (TINs, and for decomposing complex two-dimensional spatial objects into simpler geometries. The second objective of this paper is to promote the use of oriented matroids for finding alternative solutions to spatial data processing and analysis tasks. This study focused on the particular case of the calculation of triangulations based on oriented matroids. The prototype described in this paper used a wrapper to integrate and expose several tools previously implemented in C++.
Causality Statistical Perspectives and Applications
Berzuini, Carlo; Bernardinell, Luisa
2012-01-01
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addr
Inferring deterministic causal relations
Daniusis, Povilas; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard
2012-01-01
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the distribution of the effect will, in a certain sense, depend on the function. We provide a theoretical analysis of this method, showing that it also works in the low noise regime, and link it to information geometry. We report strong empirical results on various real-world data sets from different domains.
Bhuiyan, Tanveer Ahmed; Graff, Claus; Kanters, J.K.;
2013-01-01
Drug-induced triangulation of the cardiac action potential is associated with increased risk of arrhythmic events. It has been suggested that triangulation causes a flattening of the electrocardiographic T-wave but the relationship between triangulation, T-wave flattening and onset of arrhythmia...
Causal Inference and Developmental Psychology
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…
Friederich, Simon
2015-01-01
There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the es
Expert Causal Reasoning and Explanation.
Kuipers, Benjamin
The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…
The Visual Causality Analyst: An Interactive Interface for Causal Reasoning.
Wang, Jun; Mueller, Klaus
2016-01-01
Uncovering the causal relations that exist among variables in multivariate datasets is one of the ultimate goals in data analytics. Causation is related to correlation but correlation does not imply causation. While a number of casual discovery algorithms have been devised that eliminate spurious correlations from a network, there are no guarantees that all of the inferred causations are indeed true. Hence, bringing a domain expert into the casual reasoning loop can be of great benefit in identifying erroneous casual relationships suggested by the discovery algorithm. To address this need we present the Visual Causal Analyst-a novel visual causal reasoning framework that allows users to apply their expertise, verify and edit causal links, and collaborate with the causal discovery algorithm to identify a valid causal network. Its interface consists of both an interactive 2D graph view and a numerical presentation of salient statistical parameters, such as regression coefficients, p-values, and others. Both help users in gaining a good understanding of the landscape of causal structures particularly when the number of variables is large. Our framework is also novel in that it can handle both numerical and categorical variables within one unified model and return plausible results. We demonstrate its use via a set of case studies using multiple practical datasets. PMID:26529703
S-hull: a fast radial sweep-hull routine for Delaunay triangulation
Sinclair, David
2016-01-01
A new O(nlog(n)) algorithm is presented for performing Delaunay triangulation of sets of 2D points. The novel component of the algorithm is a radially propagating \\emph{sweep-hull} (sequentially created from the radially sorted set of 2D points, giving a non-overlapping triangulation), paired with a final triangle flipping step to give the Delaunay triangluation. In empirical tests the algorithm runs in approximately half the time of q-hull for 2D Delaunay triangulation on randomly generated ...
["Karoshi" and causal relationships].
Hamajima, N
1992-08-01
This paper aims to introduce a measure for use by physicians for stating the degree of probable causal relationship for "Karoshi", ie, a sudden death from cerebrovascular diseases or ischemic heart diseases under occupational stresses, as well as to give a brief description for legal procedures associated with worker's compensation and civil trial in Japan. It is a well-used measure in epidemiology, "attributable risk percent (AR%)", which can be applied to describe the extent of contribution to "Karoshi" of the excess occupational burdens the deceased worker was forced to bear. Although several standards such as average occupational burdens for the worker, average occupational burdens for an ordinary worker, burdens in a nonoccupational life, and a complete rest, might be considered for the AR% estimation, the average occupational burdens for an ordinary worker should normally be utilized as a standard for worker's compensation. The adoption of AR% could be helpful for courts to make a consistent judgement whether "Karoshi" cases are compensatable or not. PMID:1392028
Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt
2016-01-01
Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling. PMID:26470866
Time reordered: Causal perception guides the interpretation of temporal order.
Bechlivanidis, Christos; Lagnado, David A
2016-01-01
We present a novel temporal illusion in which the perceived order of events is dictated by their perceived causal relationship. Participants view a simple Michotte-style launching sequence featuring 3 objects, in which one object starts moving before its presumed cause. Not only did participants re-order the events in a causally consistent way, thus violating the objective temporal order, but they also failed to recognise the clip they had seen, preferring a clip in which temporal and causal order matched. We show that the effect is not due to lack of attention to the presented events and we discuss the problem of determining whether causality affects temporal order at an early perceptual stage or whether it distorts an accurately perceived order during retrieval. Alternatively, we propose a mechanism by which temporal order is neither misperceived nor misremembered but inferred "on-demand" given phenomenal causality and the temporal priority principle, the assumption that causes precede their effects. Finally, we discuss how, contrary to theories of causal perception, impressions of causality can be generated from dynamic sequences with strong spatiotemporal deviations. PMID:26402648
Principal stratification in causal inference.
Frangakis, Constantine E; Rubin, Donald B
2002-03-01
Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority. PMID:11890317
Stereo Matching Algorithm Based on 2D Delaunay Triangulation
Xue-he Zhang
2015-01-01
Full Text Available To fulfill the applications on robot vision, the commonly used stereo matching method for depth estimation is supposed to be efficient in terms of running speed and disparity accuracy. Based on this requirement, Delaunay-based stereo matching method is proposed to achieve the aforementioned standards in this paper. First, a Canny edge operator is used to detect the edge points of an image as supporting points. Those points are then processed using a Delaunay triangulation algorithm to divide the whole image into a series of linked triangular facets. A proposed module composed of these facets performs a rude estimation of image disparity. According to the triangular property of shared vertices, the estimated disparity is then refined to generate the disparity map. The method is tested on Middlebury stereo pairs. The running time of the proposed method is about 1 s and the matching accuracy is 93%. Experimental results show that the proposed method improves both running speed and disparity accuracy, which forms a steady foundation and good application prospect for a robot’s path planning system with stereo camera devices.
Reference LIDAR Surfaces for Enhanced Aerial Triangulation and Camera Calibration
Gneeniss, A. S.; Mills, J. P.; Miller, P. E.
2013-04-01
Due to the complementary characteristics of lidar and photogrammetry, the integration of data derived from these techniques continues to receive attention from the relevant research communities. The research presented in this paper draws on this by adopting lidar data as a control surface from which aerial triangulation and camera system calibration can be performed. The research methodology implements automatic registration between the reference lidar DTM and dense photogrammetric point clouds which are derived using Integrated Sensing Orientation (ISO). This utilises a robust least squares surface matching algorithm, which is iterated to improve results by increasing the photogrammetric point quality through self-calibrating bundle adjustment. After a successful registration, well distributed lidar control points (LCPs) are automatically extracted from the transformed photogrammetric point clouds using predefined criteria. Finally, self-calibrating bundle block adjustment using different configurations of LCPs is performed to refine camera interior orientation (IO) parameters. The methodology has been assessed using imagery from a Vexcel UltraCamX large format camera. Analysis and the performance of the camera and its impact on the registration accuracy was performed. Furthermore, refinement of camera IO parameters was also applied using the derived LCPs. Tests also included investigations into the influence of the number and weight of LCPs in the accuracy of the bundle adjustment. Results from the UltraCamX block were compared with reference calibration results using ground control points in the test area, with good agreement found between the two approaches.
3D Laser Triangulation for Plant Phenotyping in Challenging Environments
Katrine Heinsvig Kjaer
2015-06-01
Full Text Available To increase the understanding of how the plant phenotype is formed by genotype and environmental interactions, simple and robust high-throughput plant phenotyping methods should be developed and considered. This would not only broaden the application range of phenotyping in the plant research community, but also increase the ability for researchers to study plants in their natural environments. By studying plants in their natural environment in high temporal resolution, more knowledge on how multiple stresses interact in defining the plant phenotype could lead to a better understanding of the interaction between plant responses and epigenetic regulation. In the present paper, we evaluate a commercial 3D NIR-laser scanner (PlantEye, Phenospex B.V., Herleen, The Netherlands to track daily changes in plant growth with high precision in challenging environments. Firstly, we demonstrate that the NIR laser beam of the scanner does not affect plant photosynthetic performance. Secondly, we demonstrate that it is possible to estimate phenotypic variation amongst the growth pattern of ten genotypes of Brassica napus L. (rapeseed, using a simple linear correlation between scanned parameters and destructive growth measurements. Our results demonstrate the high potential of 3D laser triangulation for simple measurements of phenotypic variation in challenging environments and in a high temporal resolution.