Fernandez, R.; Deveaux, V.
2010-01-01
We provide a formal definition and study the basic properties of partially ordered chains (POC). These systems were proposed to model textures in image processing and to represent independence relations between random variables in statistics (in the later case they are known as Bayesian networks).
Partial Orders and Fully Abstract Models for Concurrency
DEFF Research Database (Denmark)
Engberg, Uffe Henrik
1990-01-01
In this thesis sets of labelled partial orders are employed as fundamental mathematical entities for modelling nondeterministic and concurrent processes thereby obtaining so-called noninterleaving semantics. Based on different closures of sets of labelled partial orders, simple algebraic language...
Latent Partially Ordered Classification Models and Normal Mixtures
Tatsuoka, Curtis; Varadi, Ferenc; Jaeger, Judith
2013-01-01
Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for…
Partial-Order Reduction for GPU Model Checking
Neele, T.; Wijs, A.; Bosnacki, D.; van de Pol, Jan Cornelis; Artho, C; Legay, A.; Peled, D.
2016-01-01
Model checking using GPUs has seen increased popularity over the last years. Because GPUs have a limited amount of memory, only small to medium-sized systems can be verified. For on-the-fly explicit-state model checking, we improve memory efficiency by applying partial-order reduction. We propose
Hierarchical partial order ranking
International Nuclear Information System (INIS)
Carlsen, Lars
2008-01-01
Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters
Partial-order reduction for GPU model checking
Neele, T.S.; Wijs, A.J.; Bošnački, D.; van de Pol, J.C.
2016-01-01
Model checking using GPUs has seen increased popularity over the last years. Because GPUs have a limited amount of memory, only small to medium-sized systems can be verified. For on-the-fly explicitstate model checking, we improve memory efficiency by applying partialorder reduction. We propose
Partial order infinitary term rewriting
DEFF Research Database (Denmark)
Bahr, Patrick
2014-01-01
We study an alternative model of infinitary term rewriting. Instead of a metric on terms, a partial order on partial terms is employed to formalise convergence of reductions. We consider both a weak and a strong notion of convergence and show that the metric model of convergence coincides with th...... to the metric setting -- orthogonal systems are both infinitarily confluent and infinitarily normalising in the partial order setting. The unique infinitary normal forms that the partial order model admits are Böhm trees....
An isotonic partial credit model for ordering subjects on the basis of their sum scores
Ligtvoet, R.
2012-01-01
In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable.
An Isotonic Partial Credit Model for Ordering Subjects on the Basis of Their Sum Scores
Ligtvoet, Rudy
2012-01-01
In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable. However, the PCM is very restrictive with respect…
Partially ordered algebraic systems
Fuchs, Laszlo
2011-01-01
Originally published in an important series of books on pure and applied mathematics, this monograph by a distinguished mathematician explores a high-level area in algebra. It constitutes the first systematic summary of research concerning partially ordered groups, semigroups, rings, and fields. The self-contained treatment features numerous problems, complete proofs, a detailed bibliography, and indexes. It presumes some knowledge of abstract algebra, providing necessary background and references where appropriate. This inexpensive edition of a hard-to-find systematic survey will fill a gap i
Shah, A A; Xing, W W; Triantafyllidis, V
2017-04-01
In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.
Unidimensional factor models imply weaker partial correlations than zero-order correlations.
van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J
2018-06-01
In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.
Lattice Boltzmann model for high-order nonlinear partial differential equations
Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang
2018-01-01
In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂tϕ +∑k=1mαk∂xkΠk(ϕ ) =0 (1 ≤k ≤m ≤6 ), αk are constant coefficients, Πk(ϕ ) are some known differential functions of ϕ . As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K (n ,n ) -Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009), 10.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009), 10.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.
Lattice Boltzmann model for high-order nonlinear partial differential equations.
Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang
2018-01-01
In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂_{t}ϕ+∑_{k=1}^{m}α_{k}∂_{x}^{k}Π_{k}(ϕ)=0 (1≤k≤m≤6), α_{k} are constant coefficients, Π_{k}(ϕ) are some known differential functions of ϕ. As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K(n,n)-Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009)1672-179910.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009)PHYADX0378-437110.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.
Algorithms over partially ordered sets
DEFF Research Database (Denmark)
Baer, Robert M.; Østerby, Ole
1969-01-01
in partially ordered sets, answer the combinatorial question of how many maximal chains might exist in a partially ordered set withn elements, and we give an algorithm for enumerating all maximal chains. We give (in § 3) algorithms which decide whether a partially ordered set is a (lower or upper) semi......-lattice, and whether a lattice has distributive, modular, and Boolean properties. Finally (in § 4) we give Algol realizations of the various algorithms....
Model Following and High Order Augmentation for Rotorcraft Control, Applied via Partial Authority
Spires, James Michael
only (HOC_FB), while the combined objective HOC has both feedback and feedforward elements (HOC_FBFF). The HOC_FB was found to be better at improving turbulence rejection but generally degrades the following of pilot commands. The HOC_FBFF improves turbulence rejection relative to the Baseline controller, but not by as much as HOC_FB. However, HOC_FBFF also generally improves the following of pilot commands. Future work is suggested and facilitated in the areas of DI, MIMO EMF, and HOC augmentation. High frequency dynamics, neglected in the DI design, unexpectedly change the low frequency behavior of the DI-plant system, in addition to the expected change in high frequency dynamics. This dissertation shows why, and suggests a technique for designing a pseudo-command pre-filter that at least partially restores the intended DI-plant dynamics. For EMF, a procedure is presented that avoids use of a reducedorder model, and instead uses a full-order model or even frequency-domain flight test data. With HOC augmentation, future research might investigate the utility of adding an H? constraint to the design objective, which is known as an equal-weighting mixed-norm H2/H infinity design. Because all the formulas in the published literature either require solution of three coupled Riccati Equations (for which there is no readily available tool), or make assumptions that do not fit the present problem, appropriate equalweighting H2/H infinity design formulas are derived which involve two de-coupled Riccati Equations.
San-José, Luis A.; Sicilia, Joaquín; González-de-la-Rosa, Manuel; Febles-Acosta, Jaime
2018-07-01
In this article, a deterministic inventory model with a ramp-type demand depending on price and time is developed. The cumulative holding cost is assumed to be a nonlinear function of time. Shortages are allowed and are partially backlogged. Thus, the fraction of backlogged demand depends on the waiting time and on the stock-out period. The aim is to maximize the total profit per unit time. To do this, a procedure that determines the economic lot size, the optimal inventory cycle and the maximum profit is presented. The inventory system studied here extends diverse inventory models proposed in the literature. Finally, some numerical examples are provided to illustrate the theoretical results previously propounded.
Energy Technology Data Exchange (ETDEWEB)
Moos, L. von, E-mail: lmoo@dtu.dk [Department of Energy Conversion and Storage, Technical University of Denmark, 4000 Roskilde (Denmark); Bahl, C.R.H.; Nielsen, K.K.; Engelbrecht, K. [Department of Energy Conversion and Storage, Technical University of Denmark, 4000 Roskilde (Denmark); Küpferling, M.; Basso, V. [Istituto Nazionale di Ricerca Metrologica, 10135 Torino (Italy)
2014-02-15
Magnetic refrigeration is an emerging technology that could provide energy efficient and environmentally friendly cooling. Magnetocaloric materials in which a structural phase transition is found concurrently with the magnetic phase transition are often termed first order magnetocaloric materials. Such materials are potential candidates for application in magnetic refrigeration devices. However, the first order materials often have adverse properties such as hysteresis, making actual performance troublesome to quantify, a subject not thoroughly studied within this field. Here we investigate the behavior of MnFe(P,As) under partial phase transitions, which is similar to what materials experience in actual magnetic refrigeration devices. Partial phase transition curves, in the absence of a magnetic field, are measured using calorimetry and the experimental results are compared to simulations of a Preisach-type model. We show that this approach is applicable and discuss what experimental data is required to obtain a satisfactory material model.
Molamohamadi, Zohreh; Arshizadeh, Rahman; Ismail, Napsiah
2015-05-01
In the classical inventory model, it was assumed that the retailer must settle the accounts of the purchased items as soon as they are received. In practice, however, the supplier usually offers a full or partial delay period to the retailer to pay for the amount of the purchasing costs. In the partial trade credit contract, which is mostly applied to avoid non-payment risks, the retailer must pay for a portion of the purchased goods at the time of ordering and may delay settling the rest until the end of the predefined agreed upon period, so-called credit period. This paper assumes a two-level partial trade credit where both supplier and retailer offer a partial trade credit to their downstream members. The objective here is to determine the retailer's ordering policy of a deteriorating item by formulating his economic order quantity (EOQ) inventory system with backorder as a cost minimization problem. The sensitivity of the variables on different parameters has been also analyzed by applying numerical examples.
Institute of Scientific and Technical Information of China (English)
Ruan Minzhi; Luo Yi; Li Hua
2014-01-01
Rational planning of spares configuration project is an effective approach to improve equipment availability as well as reduce life cycle cost (LCC). With an analysis of various impacts on support system, the spares demand rate forecast model is constructed. According to systemic analysis method, spares support effectiveness evaluation indicators system is built, and then, initial spares configuration and optimization method is researched. To the issue of discarding and con-sumption for incomplete repairable items, its expected backorders function is approximated by Laplace demand distribution. Combining the (s-1, s) and (R, Q) inventory policy, the spares resup-ply model is established under the batch ordering policy based on inventory state, and the optimi-zation analysis flow for spares configuration is proposed. Through application on shipborne equipment spares configuration, the given scenarios are analyzed under two constraint targets:one is the support effectiveness, and the other is the spares cost. Analysis reveals that the result is consistent with practical regulation;therefore, the model’s correctness, method’s validity as well as optimization project’s rationality are proved to a certain extent.
Kudryashov, Nikolay A.; Volkov, Alexandr K.
2017-01-01
We study a new nonlinear partial differential equation of the fifth order for the description of perturbations in the Fermi-Pasta-Ulam mass chain. This fifth-order equation is an expansion of the Gardner equation for the description of the Fermi-Pasta-Ulam model. We use the potential of interaction between neighbouring masses with both quadratic and cubic terms. The equation is derived using the continuous limit. Unlike the previous works, we take into account higher order terms in the Taylor series expansions. We investigate the equation using the Painlevé approach. We show that the equation does not pass the Painlevé test and can not be integrated by the inverse scattering transform. We use the logistic function method and the Laurent expansion method to find travelling wave solutions of the fifth-order equation. We use the pseudospectral method for the numerical simulation of wave processes, described by the equation.
Partially ordered sets in complex networks
International Nuclear Information System (INIS)
Xuan Qi; Du Fang; Wu Tiejun
2010-01-01
In this paper, a partial-order relation is defined among vertices of a network to describe which vertex is more important than another on its contribution to the connectivity of the network. A maximum linearly ordered subset of vertices is defined as a chain and the chains sharing the same end-vertex are grouped as a family. Through combining the same vertices appearing in different chains, a directed chain graph is obtained. Based on these definitions, a series of new network measurements, such as chain length distribution, family diversity distribution, as well as the centrality of families, are proposed. By studying the partially ordered sets in three kinds of real-world networks, many interesting results are revealed. For instance, the similar approximately power-law chain length distribution may be attributed to a chain-based positive feedback mechanism, i.e. new vertices prefer to participate in longer chains, which can be inferred by combining the notable preferential attachment rule with a well-ordered recommendation manner. Moreover, the relatively large average incoming degree of the chain graphs may indicate an efficient substitution mechanism in these networks. Most of the partially ordered set-based properties cannot be explained by the current well-known scale-free network models; therefore, we are required to propose more appropriate network models in the future.
Sound statistical model checking for MDP using partial order and confluence reduction
Hartmanns, Arnd; Timmer, Mark
Statistical model checking (SMC) is an analysis method that circumvents the state space explosion problem in model-based verification by combining probabilistic simulation with statistical methods that provide clear error bounds. As a simulation-based technique, it can in general only provide sound
First-order partial differential equations
Rhee, Hyun-Ku; Amundson, Neal R
2001-01-01
This first volume of a highly regarded two-volume text is fully usable on its own. After going over some of the preliminaries, the authors discuss mathematical models that yield first-order partial differential equations; motivations, classifications, and some methods of solution; linear and semilinear equations; chromatographic equations with finite rate expressions; homogeneous and nonhomogeneous quasilinear equations; formation and propagation of shocks; conservation equations, weak solutions, and shock layers; nonlinear equations; and variational problems. Exercises appear at the end of mo
Higher-order rewriting and partial evaluation
DEFF Research Database (Denmark)
Danvy, Olivier; Rose, Kristoffer H.
1998-01-01
We demonstrate the usefulness of higher-order rewriting techniques for specializing programs, i.e., for partial evaluation. More precisely, we demonstrate how casting program specializers as combinatory reduction systems (CRSs) makes it possible to formalize the corresponding program...
Partial synchronization and spontaneous spatial ordering in coupled chaotic systems
International Nuclear Information System (INIS)
Ying Zhang; Gang Hu; Cerdeira, Hilda A.; Shigang Chen; Braun, Thomas; Yugui Yao
2000-11-01
A model of many symmetrically and locally coupled chaotic oscillators is studied. Partial chaotic synchronizations associated with spontaneous spatial ordering are demonstrated. Very rich patterns of the system are revealed, based on partial synchronization analysis. The stabilities of different partially synchronous spatiotemporal structures and some novel dynamical behaviors of these states are discussed both numerically and analytically. (author)
DEFF Research Database (Denmark)
von Moos, Lars; Bahl, C.R.H.; Nielsen, Kaspar Kirstein
2014-01-01
of MnFe(P,As) under partial phase transitions, which is similar to what materials experience in actual magnetic refrigeration devices. Partial phase transition curves, in the absence of a magnetic field, are measured using calorimetry and the experimental results are compared to simulations......Magnetic refrigeration is an emerging technology that could provide energy efficient and environmentally friendly cooling. Magnetocaloric materials in which a structural phase transition is found concurrently with the magnetic phase transition are often termed first order magnetocaloric materials....... Such materials are potential candidates for application in magnetic refrigeration devices. However, the first order materials often have adverse properties such as hysteresis, making actual performance troublesome to quantify, a subject not thoroughly studied within this field.Here we investigate the behavior...
Pseudo Boolean Programming for Partially Ordered Genomes
Angibaud, Sébastien; Fertin, Guillaume; Thévenin, Annelyse; Vialette, Stéphane
Comparing genomes of different species is a crucial problem in comparative genomics. Different measures have been proposed to compare two genomes: number of common intervals, number of adjacencies, number of reversals, etc. These measures are classically used between two totally ordered genomes. However, genetic mapping techniques often give rise to different maps with some unordered genes. Starting from a partial order between genes of a genome, one method to find a total order consists in optimizing a given measure between a linear extension of this partial order and a given total order of a close and well-known genome. However, for most common measures, the problem turns out to be NP-hard. In this paper, we propose a (0,1)-linear programming approach to compute a linear extension of one genome that maximizes the number of common intervals (resp. the number of adjacencies) between this linear extension and a given total order. Next, we propose an algorithm to find linear extensions of two partial orders that maximize the number of adjacencies.
Directory of Open Access Journals (Sweden)
Bhanupriya Dash
2017-09-01
Full Text Available Background: Replenishment policy for entropic order quantity model with two component demand and partial backlogging under inflation is an important subject in the stock management. Methods: In this paper an inventory model for non-instantaneous deteriorating items with stock dependant consumption rate and partial back logged in addition the effect of inflection and time value of money on replacement policy with zero lead time consider was developed. Profit maximization model is formulated by considering the effects of partial backlogging under inflation with cash discounts. Further numerical example presented to evaluate the relative performance between the entropic order quantity and EOQ models separately. Numerical example is present to demonstrate the developed model and to illustrate the procedure. Lingo 13.0 version software used to derive optimal order quantity and total cost of inventory. Finally sensitivity analysis of the optimal solution with respect to different parameters of the system carried out. Results and conclusions: The obtained inventory model is very useful in retail business. This model can extend to total backorder.
Partially Hidden Markov Models
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Rissanen, Jorma
1996-01-01
Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where...
Partially composite Higgs models
DEFF Research Database (Denmark)
Alanne, Tommi; Buarque Franzosi, Diogo; Frandsen, Mads T.
2018-01-01
We study the phenomenology of partially composite-Higgs models where electroweak symmetry breaking is dynamically induced, and the Higgs is a mixture of a composite and an elementary state. The models considered have explicit realizations in terms of gauge-Yukawa theories with new strongly...... interacting fermions coupled to elementary scalars and allow for a very SM-like Higgs state. We study constraints on their parameter spaces from vacuum stability and perturbativity as well as from LHC results and find that requiring vacuum stability up to the compositeness scale already imposes relevant...... constraints. A small part of parameter space around the classically conformal limit is stable up to the Planck scale. This is however already strongly disfavored by LHC results. in different limits, the models realize both (partially) composite-Higgs and (bosonic) technicolor models and a dynamical extension...
Higher-Order Rewriting and Partial Evaluation
DEFF Research Database (Denmark)
Danvy, Olivier; Rose, Kristoffer H.
1997-01-01
transformations as meta-reductions, i.e., reductions in the internal “substitution calculus.” For partial-evaluation problems, this means that instead of having to prove on a case-by-case basis that one's “two-level functions” operate properly, one can concisely formalize them as a combinatory reduction system...... and obtain as a corollary that static reduction does not go wrong and yields a well-formed residual program. We have found that the CRS substitution calculus provides an adequate expressive power to formalize partial evaluation: it provides sufficient termination strength while avoiding the need...
Nonlinear partial differential equations of second order
Dong, Guangchang
1991-01-01
This book addresses a class of equations central to many areas of mathematics and its applications. Although there is no routine way of solving nonlinear partial differential equations, effective approaches that apply to a wide variety of problems are available. This book addresses a general approach that consists of the following: Choose an appropriate function space, define a family of mappings, prove this family has a fixed point, and study various properties of the solution. The author emphasizes the derivation of various estimates, including a priori estimates. By focusing on a particular approach that has proven useful in solving a broad range of equations, this book makes a useful contribution to the literature.
Partial word order freezing in Dutch
Bouma, G.J.; Hendriks, P.
2012-01-01
Dutch allows for variation as to whether the first position in the sentence is occupied by the subject or by some other constituent, such as the direct object. In particular situations, however, this commonly observed variation in word order is ‘frozen’ and only the subject appears in first
A Partial Order on Bipartite Graphs with n Vertices
Directory of Open Access Journals (Sweden)
Emil Daniel Schwab
2009-01-01
Full Text Available The paper examines a partial order on bipartite graphs (X1, X2, E with n vertices, X1∪X2={1,2,…,n}. The basis of such bipartite graph is X1 = {1,2,…,k}, 0≤k≤n. If U = (X1, X2, E(U and V = (Y1,Y2, E(V then U≤V iff |X1| ≤ |Y1| and {(i,jE(U: j>|Y1|} = ={(i,jE(V:i≤|X1|}. This partial order is a natural partial order of subobjects of an object in a triangular category with bipartite graphs as morphisms.
Graphene: A partially ordered non-periodic solid
International Nuclear Information System (INIS)
Wei, Dongshan; Wang, Feng
2014-01-01
Molecular dynamics simulations were performed to study the structural features of graphene over a wide range of temperatures from 50 to 4000 K using the PPBE-G potential [D. Wei, Y. Song, and F. Wang, J. Chem. Phys. 134, 184704 (2011)]. This potential was developed by force matching the Perdew-Burke-Ernzerhof (PBE) exchange correlation functional and has been validated previously to provide accurate potential energy surface for graphene at temperatures as high as 3000 K. Simulations with the PPBE‑G potential are the best available approximation to a direct Car-Parrinello Molecular Dynamics study of graphene. One advantage of the PBE-G potential is to allow large simulation boxes to be modeled efficiently so that properties showing strong finite size effects can be studied. Our simulation box contains more than 600 000 C atoms and is one of the largest graphene boxes ever modeled. With the PPBE-G potential, the thermal-expansion coefficient is negative up to 4000 K. With a large box and an accurate potential, the critical exponent for the scaling properties associated with the normal-normal and height-height correlation functions was confirmed to be 0.85. This exponent remains constant up to 4000 K suggesting graphene to be in the deeply cooled regime even close to the experimental melting temperature. The reduced peak heights in the radial distribution function of graphene show an inverse power law dependence to distance, which indicates that a macroscopic graphene sheet will lose long-range crystalline order as predicted by the Mermin-Wagner instability. Although graphene loses long-range translational order, it retains long range orientational order as indicated by its orientational correlation function; graphene is thus partially ordered but not periodic
Evaluation of analytical performance based on partial order methodology.
Carlsen, Lars; Bruggemann, Rainer; Kenessova, Olga; Erzhigitov, Erkin
2015-01-01
Classical measurements of performances are typically based on linear scales. However, in analytical chemistry a simple scale may be not sufficient to analyze the analytical performance appropriately. Here partial order methodology can be helpful. Within the context described here, partial order analysis can be seen as an ordinal analysis of data matrices, especially to simplify the relative comparisons of objects due to their data profile (the ordered set of values an object have). Hence, partial order methodology offers a unique possibility to evaluate analytical performance. In the present data as, e.g., provided by the laboratories through interlaboratory comparisons or proficiency testings is used as an illustrative example. However, the presented scheme is likewise applicable for comparison of analytical methods or simply as a tool for optimization of an analytical method. The methodology can be applied without presumptions or pretreatment of the analytical data provided in order to evaluate the analytical performance taking into account all indicators simultaneously and thus elucidating a "distance" from the true value. In the present illustrative example it is assumed that the laboratories analyze a given sample several times and subsequently report the mean value, the standard deviation and the skewness, which simultaneously are used for the evaluation of the analytical performance. The analyses lead to information concerning (1) a partial ordering of the laboratories, subsequently, (2) a "distance" to the Reference laboratory and (3) a classification due to the concept of "peculiar points". Copyright © 2014 Elsevier B.V. All rights reserved.
Partial Differential Equations Modeling and Numerical Simulation
Glowinski, Roland
2008-01-01
This book is dedicated to Olivier Pironneau. For more than 250 years partial differential equations have been clearly the most important tool available to mankind in order to understand a large variety of phenomena, natural at first and then those originating from human activity and technological development. Mechanics, physics and their engineering applications were the first to benefit from the impact of partial differential equations on modeling and design, but a little less than a century ago the Schrödinger equation was the key opening the door to the application of partial differential equations to quantum chemistry, for small atomic and molecular systems at first, but then for systems of fast growing complexity. Mathematical modeling methods based on partial differential equations form an important part of contemporary science and are widely used in engineering and scientific applications. In this book several experts in this field present their latest results and discuss trends in the numerical analy...
Adaptive Partially Hidden Markov Models
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Rasmussen, Tage
1996-01-01
Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding....
Partially molten magma ocean model
International Nuclear Information System (INIS)
Shirley, D.N.
1983-01-01
The properties of the lunar crust and upper mantle can be explained if the outer 300-400 km of the moon was initially only partially molten rather than fully molten. The top of the partially molten region contained about 20% melt and decreased to 0% at 300-400 km depth. Nuclei of anorthositic crust formed over localized bodies of magma segregated from the partial melt, then grew peripherally until they coverd the moon. Throughout most of its growth period the anorthosite crust floated on a layer of magma a few km thick. The thickness of this layer is regulated by the opposing forces of loss of material by fractional crystallization and addition of magma from the partial melt below. Concentrations of Sr, Eu, and Sm in pristine ferroan anorthosites are found to be consistent with this model, as are trends for the ferroan anorthosites and Mg-rich suites on a diagram of An in plagioclase vs. mg in mafics. Clustering of Eu, Sr, and mg values found among pristine ferroan anorthosites are predicted by this model
Complexity of universality and related problems for partially ordered NFAs
Czech Academy of Sciences Publication Activity Database
Krötzsch, M.; Masopust, Tomáš; Thomazo, M.
2017-01-01
Roč. 255, č. 1 (2017), s. 177-192 ISSN 0890-5401 Institutional support: RVO:67985840 Keywords : nondeterministic automata * partial order * universal ity Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 1.050, year: 2016 http://www.sciencedirect.com/science/article/pii/S0890540117300998?via%3Dihub
Ground-state properties of ordered, partially ordered, and random Cu-Au and Ni-Pt alloys
DEFF Research Database (Denmark)
Ruban, Andrei; Abrikosov, I. A.; Skriver, Hans Lomholt
1995-01-01
We have studied the ground-state properties of ordered, partially ordered, and random Cu-Au and Ni-Pt alloys at the stoichiometric 1/4, 1/2, and 3/4 compositions in the framework of the multisublattice single-site (SS) coherent potential approximation (CPA). Charge-transfer effects in the random ...... for the ordered alloys are in good agreement with experimental data. For all the alloys the calculated ordering energy and the equilibrium lattices parameters are found to be almost exact quadratic functions of the long-range-order parameter....... and the partially ordered alloys are included in the screened impurity model. The prefactor in the Madelung energy is determined by the requirement that the total energy obtained in direct SS CPA calculations should equal the total energy given by the Connolly-Williams expansion based on Green’s function...
Mathematical tools for data mining set theory, partial orders, combinatorics
Simovici, Dan A
2014-01-01
Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the firs
On the size of the subset partial order
DEFF Research Database (Denmark)
Elmasry, Amr Ahmed Abd Elmoneim
2012-01-01
Given a family of k sets with cardinalities S 1,S 2,⋯, S k and N=Σ k i=1S i, we show that the size of the partial order graph induced by the subset relation (called the subset graph) is O(Σ si≤B 2si+N/lgN·Σ si>Blg(s i/B)), 2 where B=lg(N/lg 2N). This implies a simpler proof to the O(N 2/lg 2N...
Cubical local partial orders on cubically subdivided spaces - existence and construction
DEFF Research Database (Denmark)
Fajstrup, Lisbeth
The geometric models of Higher Dimensional Automata and Dijkstra's PV-model are cubically subdivided topological spaces with a local partial order. If a cubicalization of a topological space is free of immersed cubic Möbius bands, then there are consistent choices of direction in all cubes, such ...... that the underlying geometry of an HDA may be quite complicated....
Cubical local partial orders on cubically subdivided spaces - Existence and construction
DEFF Research Database (Denmark)
Fajstrup, Lisbeth
2006-01-01
The geometric models of higher dimensional automata (HDA) and Dijkstra's PV-model are cubically subdivided topological spaces with a local partial order. If a cubicalization of a topological space is free of immersed cubic Möbius bands, then there are consistent choices of direction in all cubes...... that the underlying geometry of an HDA may be quite complicated....
Coding with partially hidden Markov models
DEFF Research Database (Denmark)
Forchhammer, Søren; Rissanen, J.
1995-01-01
Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general...... 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given....... The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt...
Mathematical Modelling of Intraretinal Oxygen Partial Pressure ...
African Journals Online (AJOL)
Purpose: The aim of our present work is to develop a simple steady state model for intraretinal oxygen partial pressure distribution and to investigate the effect of various model parameters on the partial pressure distribution under adapted conditions of light and darkness.. Method: A simple eight-layered mathematical model ...
Partially Observed Mixtures of IRT Models: An Extension of the Generalized Partial-Credit Model
Von Davier, Matthias; Yamamoto, Kentaro
2004-01-01
The generalized partial-credit model (GPCM) is used frequently in educational testing and in large-scale assessments for analyzing polytomous data. Special cases of the generalized partial-credit model are the partial-credit model--or Rasch model for ordinal data--and the two parameter logistic (2PL) model. This article extends the GPCM to the…
Shear-induced partial translational ordering of a colloidal solid
Ackerson, B. J.; Clark, N. A.
1984-08-01
Highly charged submicrometer plastic spheres suspended in water at low ionic strength will order spontaneously into bcc crystals or polycrystals. A simple linear shear orients and disorders these crystals by forcing (110) planes to stack normal to the shear gradient and to slide relative to each other with a direction parallel to the solvent flow. In this paper we analyze in detail the disordering and flow processes occurring beyond the intrinsic elastic limit of the bcc crystal. We are led to a model in which the flow of a colloidal crystal is interpreted as a fundamentally different process from that found in atomic crystals. In the colloidal crystal the coupling of particle motion to the background fluid forces a homogeneous flow, where every layer is in motion relative to its neighboring layers. In contrast, the plastic flow in an atomic solid is defect mediated flow. At the lowest applied stress, the local bcc order in the colloidal crystal exhibits shear strains both parallel and perpendicular to the direction of the applied stress. The magnitude of these deformations is estimated using the configurational energy for bcc and distorted bcc crystals, assuming a screened Coulomb pair interaction between colloidal particles. As the applied stress is increased, the intrinsic elastic limit of the crystal is exceeded and the crystal begins to flow with adjacent layers executing an oscillatory path governed by the balance of viscous and screened Coulomb forces. The path takes the structure from the bcc1 and bcc2 twins observed at zero shear to a distorted two-dimensional hcp structure at moderate shear rates, with a loss of interlayer registration as the shear is increased. This theoretical model is consistent with other experimental observations, as well.
Intention Recognition for Partial-Order Plans Using Dynamic Bayesian Networks
Krauthausen, Peter; Hanebeck, Uwe D.
2009-01-01
In this paper, a novel probabilistic approach to intention recognition for partial-order plans is proposed. The key idea is to exploit independences between subplans to substantially reduce the state space sizes in the compiled Dynamic Bayesian Networks. This makes inference more efficient. The main con- tributions are the computationally exploitable definition of subplan structures, the introduction of a novel Lay- ered Intention Model and a Dynamic Bayesian Net- work representation with an ...
Economic order quantity with partial backordering and sampling inspection
Taleizadeh, Ata Allah; Dehkordi, Negin Zamani
2017-09-01
To access the efficient inventory system, managers should consider all the situations that have happened in reality. One of these situations is the presence of the defective items in each received lot and the other situation is being the group of customers that do not wait to fulfill their requirements from the vendor and choose another one to get their orders so the proportion of the backordered items becomes lost sales. In this paper we consider both mentioned situations simultaneously to model the inventory system while the proportion of backordering is constant and the imperfect rate follows a uniform distribution, also the particular sampling process is considered that is explained in detail in "Problem definition". Our purpose in this paper is to access the optimum value for the total revenue in a year by a particular solution method that is provided in "Solution method". After these sections we provide the numerical results in "Numerical result" to show the effect of sensitive parameters on the decision variables and the total profit.
Some Considerations on the Partial Credit Model
Verhelst, N. D.; Verstralen, H. H. F. M.
2008-01-01
The Partial Credit Model (PCM) is sometimes interpreted as a model for stepwise solution of polytomously scored items, where the item parameters are interpreted as difficulties of the steps. It is argued that this interpretation is not justified. A model for stepwise solution is discussed. It is shown that the PCM is suited to model sums of binary…
A Model for Partial Kantian Cooperation
Kordonis, Ioannis
2016-01-01
This work presents a game theoretic model to describe game situations in which there is a partial cooperation among the players. Specifically, we assume that the players partially follow Kant's "Categorical Imperative". The model is stated for games with a continuum of players and the basic assumption made is that the participants consider that they belong to virtual groups in which they optimize their actions as if they were bound to follow the same strategy. The relation with the Nash, (Ben...
Conflict Resolution in Partially Ordered OWL DL Ontologies
Ji, Q.; Gao, Z.; Huang, Z.
2014-01-01
Inconsistency handling in OWL DL ontologies is an important problem because an ontology can easily be inconsistent when it is generated or modified. Current approaches to dealing with inconsistent ontologies often assume that there exists a total order over axioms and use such an order to select
Directory of Open Access Journals (Sweden)
Erkinjon Karimov
2017-10-01
Full Text Available In this work we discuss higher order multi-term partial differential equation (PDE with the Caputo-Fabrizio fractional derivative in time. Using method of separation of variables, we reduce fractional order partial differential equation to the integer order. We represent explicit solution of formulated problem in particular case by Fourier series.
Erkinjon Karimov; Sardor Pirnafasov
2017-01-01
In this work we discuss higher order multi-term partial differential equation (PDE) with the Caputo-Fabrizio fractional derivative in time. Using method of separation of variables, we reduce fractional order partial differential equation to the integer order. We represent explicit solution of formulated problem in particular case by Fourier series.
Fitting and Testing Conditional Multinormal Partial Credit Models
Hessen, David J.
2012-01-01
A multinormal partial credit model for factor analysis of polytomously scored items with ordered response categories is derived using an extension of the Dutch Identity (Holland in "Psychometrika" 55:5-18, 1990). In the model, latent variables are assumed to have a multivariate normal distribution conditional on unweighted sums of item…
Directory of Open Access Journals (Sweden)
Ibrahim Mohd Tarmizi
2017-01-01
Full Text Available Theories are developed to explain an observed phenomenon in an effort to understand why and how things happen. Theories thus, use latent variables to estimate conceptual parameters. The level of abstraction depends, partly on the complexity of the theoretical model explaining the phenomenon. The conjugation of directly-measured variables leads to a formation of a first-order factor. A combination of theoretical underpinnings supporting an existence of a higher-order components, and statistical evidence pointing to such presence adds advantage for the researchers to investigate a phenomenon both at an aggregated and disjointed dimensions. As partial least square (PLS gains its tractions in theory development, behavioural accounting discipline in general should exploit the flexibility of PLS to work with the higher-order factors. However, technical guides are scarcely available. Therefore, this article presents a PLS approach to validate a higher-order factor on a statistical ground using accounting information system dataset.
Testing the generalized partial credit model
Glas, Cornelis A.W.
1996-01-01
The partial credit model (PCM) (G.N. Masters, 1982) can be viewed as a generalization of the Rasch model for dichotomous items to the case of polytomous items. In many cases, the PCM is too restrictive to fit the data. Several generalizations of the PCM have been proposed. In this paper, a
Some Considerations on the Partial Credit Model
H.H.F.M. Verstralen; N.D. Verhelst
2008-01-01
The Partial Credit Model (PCM) is sometimes interpreted as a model for stepwise solution of polytomously scored items, where the item parameters are interpreted as di culties of the steps. It is argued that this interpretation is not justi ed. A model for stepwise solution is discussed. It is shown that the PCM is suited to model sums of binary responses which are not supposed to be stochastically independent. As a practical result, a statistical test of sto...
Response Styles in the Partial Credit Model
Tutz, Gerhard; Schauberger, Gunther; Berger, Moritz
2016-01-01
In the modelling of ordinal responses in psychological measurement and survey- based research, response styles that represent specific answering patterns of respondents are typically ignored. One consequence is that estimates of item parameters can be poor and considerably biased. The focus here is on the modelling of a tendency to extreme or middle categories. An extension of the Partial Credit Model is proposed that explicitly accounts for this specific response style. In contrast to exi...
DEFF Research Database (Denmark)
Siersma, Volkert; Kreiner, Svend
2009-01-01
Goodman and Kruskal's gamma coefficient measuring monotone association and its partial variants are useful for the analysis of multiway contingency tables containing ordinal variables. When the categories of a variable are only partly ordered and the variable is treated as a nominal variable......, information in the ordering of the categories and statistical power is lost. The authors suggest a (P)gamma measure that is the maximum of the ordinary gamma coefficients obtained by permuting the categories of nominal or partially ordered variables, while leaving the partial ordering intact. When...... of the (P)gamma coefficient are investigated in a simulation study and its use illustrated in two data sets....
Partial chord diagrams and matrix models
DEFF Research Database (Denmark)
Andersen, Jørgen Ellegaard; Fuji, Hiroyuki; Manabe, Masahide
In this article, the enumeration of partial chord diagrams is discussed via matrix model techniques. In addition to the basic data such as the number of backbones and chords, we also consider the Euler characteristic, the backbone spectrum, the boundary point spectrum, and the boundary length spe...
2010-04-08
... DEPARTMENT OF THE INTERIOR Bureau of Land Management [LLCA930000; CACA 7817] Public Land Order No. 7736; Partial Revocation of the Bureau of Reclamation Order Dated February 19, 1952; California AGENCY: Bureau of Land Management. ACTION: Correction. SUMMARY: The Bureau of Land Management published a...
2010-06-24
... DEPARTMENT OF THE INTERIOR Bureau of Land Management [LLCA930000, L14300000.ER0000; CACA 7059, CACA 7060, CACA 7101, CACA 7102, and CACA 7239] Public Land Order No. 7743; Partial Revocation of Five Secretarial Orders for Reclamation Project Purposes on the Colorado River, California. AGENCY: Bureau of Land...
Some Considerations on the Partial Credit Model
Directory of Open Access Journals (Sweden)
H.H.F.M. Verstralen
2008-01-01
Full Text Available The Partial Credit Model (PCM is sometimes interpreted as a model for stepwise solution of polytomously scored items, where the item parameters are interpreted as di culties of the steps. It is argued that this interpretation is not justi ed. A model for stepwise solution is discussed. It is shown that the PCM is suited to model sums of binary responses which are not supposed to be stochastically independent. As a practical result, a statistical test of stochastic independence in the Rasch model is derived
High-order fractional partial differential equation transform for molecular surface construction.
Hu, Langhua; Chen, Duan; Wei, Guo-Wei
2013-01-01
Fractional derivative or fractional calculus plays a significant role in theoretical modeling of scientific and engineering problems. However, only relatively low order fractional derivatives are used at present. In general, it is not obvious what role a high fractional derivative can play and how to make use of arbitrarily high-order fractional derivatives. This work introduces arbitrarily high-order fractional partial differential equations (PDEs) to describe fractional hyperdiffusions. The fractional PDEs are constructed via fractional variational principle. A fast fractional Fourier transform (FFFT) is proposed to numerically integrate the high-order fractional PDEs so as to avoid stringent stability constraints in solving high-order evolution PDEs. The proposed high-order fractional PDEs are applied to the surface generation of proteins. We first validate the proposed method with a variety of test examples in two and three-dimensional settings. The impact of high-order fractional derivatives to surface analysis is examined. We also construct fractional PDE transform based on arbitrarily high-order fractional PDEs. We demonstrate that the use of arbitrarily high-order derivatives gives rise to time-frequency localization, the control of the spectral distribution, and the regulation of the spatial resolution in the fractional PDE transform. Consequently, the fractional PDE transform enables the mode decomposition of images, signals, and surfaces. The effect of the propagation time on the quality of resulting molecular surfaces is also studied. Computational efficiency of the present surface generation method is compared with the MSMS approach in Cartesian representation. We further validate the present method by examining some benchmark indicators of macromolecular surfaces, i.e., surface area, surface enclosed volume, surface electrostatic potential and solvation free energy. Extensive numerical experiments and comparison with an established surface model
Testing the generalized partial credit model
Glas, Cornelis A.W.
1996-01-01
The partial credit model (PCM) (G.N. Masters, 1982) can be viewed as a generalization of the Rasch model for dichotomous items to the case of polytomous items. In many cases, the PCM is too restrictive to fit the data. Several generalizations of the PCM have been proposed. In this paper, a generalization of the PCM (GPCM), a further generalization of the one-parameter logistic model, is discussed. The model is defined and the conditional maximum likelihood procedure for the method is describe...
On nonlinear reduced order modeling
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.
2011-01-01
When applied to a model that receives n input parameters and predicts m output responses, a reduced order model estimates the variations in the m outputs of the original model resulting from variations in its n inputs. While direct execution of the forward model could provide these variations, reduced order modeling plays an indispensable role for most real-world complex models. This follows because the solutions of complex models are expensive in terms of required computational overhead, thus rendering their repeated execution computationally infeasible. To overcome this problem, reduced order modeling determines a relationship (often referred to as a surrogate model) between the input and output variations that is much cheaper to evaluate than the original model. While it is desirable to seek highly accurate surrogates, the computational overhead becomes quickly intractable especially for high dimensional model, n ≫ 10. In this manuscript, we demonstrate a novel reduced order modeling method for building a surrogate model that employs only 'local first-order' derivatives and a new tensor-free expansion to efficiently identify all the important features of the original model to reach a predetermined level of accuracy. This is achieved via a hybrid approach in which local first-order derivatives (i.e., gradient) of a pseudo response (a pseudo response represents a random linear combination of original model’s responses) are randomly sampled utilizing a tensor-free expansion around some reference point, with the resulting gradient information aggregated in a subspace (denoted by the active subspace) of dimension much less than the dimension of the input parameters space. The active subspace is then sampled employing the state-of-the-art techniques for global sampling methods. The proposed method hybridizes the use of global sampling methods for uncertainty quantification and local variational methods for sensitivity analysis. In a similar manner to
Exploiting partial knowledge for efficient model analysis
Macedo, Nuno; Cunha, Alcino; Pessoa, Eduardo José Dias
2017-01-01
The advancement of constraint solvers and model checkers has enabled the effective analysis of high-level formal specification languages. However, these typically handle a specification in an opaque manner, amalgamating all its constraints in a single monolithic verification task, which often proves to be a performance bottleneck. This paper addresses this issue by proposing a solving strategy that exploits user-provided partial knowledge, namely by assigning symbolic bounds to the problem’s ...
Optimal inventory management and order book modeling
Baradel, Nicolas
2018-02-16
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.
RECTC/RECTCF, 2. Order Elliptical Partial Differential Equation, Arbitrary Boundary Conditions
International Nuclear Information System (INIS)
Hackbusch, W.
1983-01-01
1 - Description of problem or function: A general linear elliptical second order partial differential equation on a rectangle with arbitrary boundary conditions is solved. 2 - Method of solution: Multi-grid iteration
Partially ordered sets, transfinite topology and the dimension of Cantorian-fractal spacetime
Energy Technology Data Exchange (ETDEWEB)
Marek-Crnjac, L. [Institute of Mathematics and Physics, University of Maribor (Slovenia)], E-mail: leila.marek@guest.arnes.si
2009-11-15
We introduce partially ordered sets and relate them to random Cantor sets of E-infinity theory. Subsequently we derive the dimensionality of Cantorian-fractal spacetime using posets and E-infinity transfinite Cantor sets.
Parameter Estimation of Partial Differential Equation Models.
Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab
2013-01-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.
Partial differential equation models in macroeconomics.
Achdou, Yves; Buera, Francisco J; Lasry, Jean-Michel; Lions, Pierre-Louis; Moll, Benjamin
2014-11-13
The purpose of this article is to get mathematicians interested in studying a number of partial differential equations (PDEs) that naturally arise in macroeconomics. These PDEs come from models designed to study some of the most important questions in economics. At the same time, they are highly interesting for mathematicians because their structure is often quite difficult. We present a number of examples of such PDEs, discuss what is known about their properties, and list some open questions for future research. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Semi-algebraic function rings and reflectors of partially ordered rings
Schwartz, Niels
1999-01-01
The book lays algebraic foundations for real geometry through a systematic investigation of partially ordered rings of semi-algebraic functions. Real spectra serve as primary geometric objects, the maps between them are determined by rings of functions associated with the spectra. The many different possible choices for these rings of functions are studied via reflections of partially ordered rings. Readers should feel comfortable using basic algebraic and categorical concepts. As motivational background some familiarity with real geometry will be helpful. The book aims at researchers and graduate students with an interest in real algebra and geometry, ordered algebraic structures, topology and rings of continuous functions.
A combined QSAR and partial order ranking approach to risk assessment.
Carlsen, L
2006-04-01
QSAR generated data appear as an attractive alternative to experimental data as foreseen in the proposed new chemicals legislation REACH. A preliminary risk assessment for the aquatic environment can be based on few factors, i.e. the octanol-water partition coefficient (Kow), the vapour pressure (VP) and the potential biodegradability of the compound in combination with the predicted no-effect concentration (PNEC) and the actual tonnage in which the substance is produced. Application of partial order ranking, allowing simultaneous inclusion of several parameters leads to a mutual prioritisation of the investigated substances, the prioritisation possibly being further analysed through the concept of linear extensions and average ranks. The ranking uses endpoint values (log Kow and log VP) derived from strictly linear 'noise-deficient' QSAR models as input parameters. Biodegradation estimates were adopted from the BioWin module of the EPI Suite. The population growth impairment of Tetrahymena pyriformis was used as a surrogate for fish lethality.
Rusyaman, E.; Parmikanti, K.; Chaerani, D.; Asefan; Irianingsih, I.
2018-03-01
One of the application of fractional ordinary differential equation is related to the viscoelasticity, i.e., a correlation between the viscosity of fluids and the elasticity of solids. If the solution function develops into function with two or more variables, then its differential equation must be changed into fractional partial differential equation. As the preliminary study for two variables viscoelasticity problem, this paper discusses about convergence analysis of function sequence which is the solution of the homogenous fractional partial differential equation. The method used to solve the problem is Homotopy Analysis Method. The results show that if given two real number sequences (αn) and (βn) which converge to α and β respectively, then the solution function sequences of fractional partial differential equation with order (αn, βn) will also converge to the solution function of fractional partial differential equation with order (α, β).
Global Attractivity Results for Mixed-Monotone Mappings in Partially Ordered Complete Metric Spaces
Directory of Open Access Journals (Sweden)
Kalabušić S
2009-01-01
Full Text Available We prove fixed point theorems for mixed-monotone mappings in partially ordered complete metric spaces which satisfy a weaker contraction condition than the classical Banach contraction condition for all points that are related by given ordering. We also give a global attractivity result for all solutions of the difference equation , where satisfies mixed-monotone conditions with respect to the given ordering.
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Directory of Open Access Journals (Sweden)
Yunjiao Bai
2015-01-01
Full Text Available The traditional fourth-order nonlinear diffusion denoising model suffers the isolated speckles and the loss of fine details in the processed image. For this reason, a new fourth-order partial differential equation based on the patch similarity modulus and the difference curvature is proposed for image denoising. First, based on the intensity similarity of neighbor pixels, this paper presents a new edge indicator called patch similarity modulus, which is strongly robust to noise. Furthermore, the difference curvature which can effectively distinguish between edges and noise is incorporated into the denoising algorithm to determine the diffusion process by adaptively adjusting the size of the diffusion coefficient. The experimental results show that the proposed algorithm can not only preserve edges and texture details, but also avoid isolated speckles and staircase effect while filtering out noise. And the proposed algorithm has a better performance for the images with abundant details. Additionally, the subjective visual quality and objective evaluation index of the denoised image obtained by the proposed algorithm are higher than the ones from the related methods.
International Nuclear Information System (INIS)
Dowell, F.
1987-01-01
A summary of results from a unique statistical-physics theory to predict and explain competing interactions and resulting microstructures in some partially-ordered [in this case, liquid-crystalline (LC)] phases is presented. The static aspects of both partial orientational and partial positional ordering of the molecules into various microstructures in these phases (including the incommensurate smectic-Ad phase) can be understood in terms of various competing interactions (both entropic and energetic) involved in the packing together of the different molecular sub-units at given pressures and temperatures. These microstructures are predicted and explained (using no ad hoc or arbitrarily adjustable parameter) as a function of molecule chemical structure [including lengths and shapes (from bond lengths and angles), intramolecular rotations, site-site polarizabilities and pair potentials, dipole moments, etc]. Theoretical results are presented for the nematic, re-entrant nematic, smectic-Ad, and smectic-Al LC phases and the isotropic phase
2011-05-02
...] Public Land Order No. 7765; Partial Revocation Jupiter Inlet Lighthouse Withdrawal; Florida AGENCY... as part of the Jupiter Inlet Lighthouse Outstanding Natural Area. DATES: Effective Date: May 2, 2011... U.S.C. 1787), which created the Jupiter Inlet Lighthouse Outstanding Natural Area, and which...
Directory of Open Access Journals (Sweden)
Xiangbing Zhou
2012-01-01
Full Text Available We generalize a fixed point theorem in partially ordered complete metric spaces in the study of A. Amini-Harandi and H. Emami (2010. We also give an application on the existence and uniqueness of the positive solution of a multipoint boundary value problem with fractional derivatives.
Oscillation of certain higher-order neutral partial functional differential equations.
Li, Wei Nian; Sheng, Weihong
2016-01-01
In this paper, we study the oscillation of certain higher-order neutral partial functional differential equations with the Robin boundary conditions. Some oscillation criteria are established. Two examples are given to illustrate the main results in the end of this paper.
M. Denche; A. L. Marhoune
2003-01-01
In this paper, we study a mixed problem with integral boundary conditions for a high order partial differential equation of mixed type. We prove the existence and uniqueness of the solution. The proof is based on energy inequality, and on the density of the range of the operator generated by the considered problem.
Thomas, CK; Nelson, G; Than, L; Zijdewind, Inge
The activation order of motor units during electrically evoked contractions of paralyzed or partially paralyzed thenar muscles was determined in seven subjects with chronic cervical spinal cord injury. The median nerve was stimulated percutaneously with pulses of graded intensity to produce
International Nuclear Information System (INIS)
LaChapelle, J.
2004-01-01
A path integral is presented that solves a general class of linear second order partial differential equations with Dirichlet/Neumann boundary conditions. Elementary kernels are constructed for both Dirichlet and Neumann boundary conditions. The general solution can be specialized to solve elliptic, parabolic, and hyperbolic partial differential equations with boundary conditions. This extends the well-known path integral solution of the Schroedinger/diffusion equation in unbounded space. The construction is based on a framework for functional integration introduced by Cartier/DeWitt-Morette
Tang, Chen; Han, Lin; Ren, Hongwei; Zhou, Dongjian; Chang, Yiming; Wang, Xiaohang; Cui, Xiaolong
2008-10-01
We derive the second-order oriented partial-differential equations (PDEs) for denoising in electronic-speckle-pattern interferometry fringe patterns from two points of view. The first is based on variational methods, and the second is based on controlling diffusion direction. Our oriented PDE models make the diffusion along only the fringe orientation. The main advantage of our filtering method, based on oriented PDE models, is that it is very easy to implement compared with the published filtering methods along the fringe orientation. We demonstrate the performance of our oriented PDE models via application to two computer-simulated and experimentally obtained speckle fringes and compare with related PDE models.
Pretreatment of wastewater: Optimal coagulant selection using Partial Order Scaling Analysis (POSA)
International Nuclear Information System (INIS)
Tzfati, Eran; Sein, Maya; Rubinov, Angelika; Raveh, Adi; Bick, Amos
2011-01-01
Jar-test is a well-known tool for chemical selection for physical-chemical wastewater treatment. Jar test results show the treatment efficiency in terms of suspended matter and organic matter removal. However, in spite of having all these results, coagulant selection is not an easy task because one coagulant can remove efficiently the suspended solids but at the same time increase the conductivity. This makes the final selection of coagulants very dependent on the relative importance assigned to each measured parameter. In this paper, the use of Partial Order Scaling Analysis (POSA) and multi-criteria decision analysis is proposed to help the selection of the coagulant and its concentration in a sequencing batch reactor (SBR). Therefore, starting from the parameters fixed by the jar-test results, these techniques will allow to weight these parameters, according to the judgments of wastewater experts, and to establish priorities among coagulants. An evaluation of two commonly used coagulation/flocculation aids (Alum and Ferric Chloride) was conducted and based on jar tests and POSA model, Ferric Chloride (100 ppm) was the best choice. The results obtained show that POSA and multi-criteria techniques are useful tools to select the optimal chemicals for the physical-technical treatment.
Mathematical Modelling of Intraretinal Oxygen Partial Pressure
African Journals Online (AJOL)
Erah
oxygen availability) is required for retinal oxidative metabolism. .... retina was described using Hill's equation and Fick's law. ... ganglion cell / nerve fiber layer and the superficial ..... parameter values producing the best. Figure 2: Partial ...
International Nuclear Information System (INIS)
Glatter, O.; Gruber, K.
1993-01-01
Indirect Fourier transformation is a widely used technique for the desmearing of instrumental broadening effects, for data smoothing and for Fourier transformation of small-angle scattering data. This technique, however, can only be applied to scattering curves with a band-limited Fourier transform, i.e. separated and noninteracting scattering centers. It can therefore not be used for scattering data from partially ordered systems. In this paper, a modified technique for partially ordered systems working in reciprocal space is presented. A peak-recognition technique allows its application to scattering functions with narrow peaks, such as the scattering functions of layered systems like lamellar stacks or strongly interacting particles. Arbitrary geometry effects and wavelength effects can be corrected. Examples of simulations show the merits and limits of this new method. One example shows its applicability to real data. (orig.)
Bounding the Resource Availability of Partially Ordered Events with Constant Resource Impact
Frank, Jeremy
2004-01-01
We compare existing techniques to bound the resource availability of partially ordered events. We first show that, contrary to intuition, two existing techniques, one due to Laborie and one due to Muscettola, are not strictly comparable in terms of the size of the search trees generated under chronological search with a fixed heuristic. We describe a generalization of these techniques called the Flow Balance Constraint to tightly bound the amount of available resource for a set of partially ordered events with piecewise constant resource impact We prove that the new technique generates smaller proof trees under chronological search with a fixed heuristic, at little increase in computational expense. We then show how to construct tighter resource bounds but at increased computational cost.
Directory of Open Access Journals (Sweden)
Veyis Turut
2013-01-01
Full Text Available Two tecHniques were implemented, the Adomian decomposition method (ADM and multivariate Padé approximation (MPA, for solving nonlinear partial differential equations of fractional order. The fractional derivatives are described in Caputo sense. First, the fractional differential equation has been solved and converted to power series by Adomian decomposition method (ADM, then power series solution of fractional differential equation was put into multivariate Padé series. Finally, numerical results were compared and presented in tables and figures.
International Nuclear Information System (INIS)
Li Xicheng; Xu Mingyu; Wang Shaowei
2008-01-01
In this paper, we give similarity solutions of partial differential equations of fractional order with a moving boundary condition. The solutions are given in terms of a generalized Wright function. The time-fractional Caputo derivative and two types of space-fractional derivatives are considered. The scale-invariant variable and the form of the solution of the moving boundary are obtained by the Lie group analysis. A comparison between the solutions corresponding to two types of fractional derivative is also given
Energy Technology Data Exchange (ETDEWEB)
El-Sayed, A.M.A. [Faculty of Science University of Alexandria (Egypt)]. E-mail: amasyed@hotmail.com; Gaber, M. [Faculty of Education Al-Arish, Suez Canal University (Egypt)]. E-mail: mghf408@hotmail.com
2006-11-20
The Adomian decomposition method has been successively used to find the explicit and numerical solutions of the time fractional partial differential equations. A different examples of special interest with fractional time and space derivatives of order {alpha}, 0<{alpha}=<1 are considered and solved by means of Adomian decomposition method. The behaviour of Adomian solutions and the effects of different values of {alpha} are shown graphically for some examples.
A drift-ordered short mean-free path description of a partially ionized magnetized plasma
International Nuclear Information System (INIS)
Simakov, Andrei N
2009-01-01
Neutral particles that are present at the edge of plasma magnetic confinement devices can play an important role in energy and momentum transport, and their effects should be accounted for. This work uses the drift ordering to derive a closed fluid description for a collisional, magnetized, partially ionized plasma. Charge-exchange, ionization and recombination processes are taken into account. It is assumed that electron distribution function is unaffected by atomic processes, so that electron-ion momentum and energy exchange are described by the usual expressions for a fully ionized plasma, and that neutral-neutral collisions are unimportant. The collisional fluid equations derived herein generalize the drift-ordered description of a fully ionized collisional plasma (Catto P J et al 2004 Phys. Plasmas 11 90), agree with the MHD-ordered description of a partially ionized plasma (Helander P et al 1994 Phys. Plasmas 1 3174) in the large-flow limit and can be used to describe both turbulent and collisional behavior of a partially ionized plasma.
Calatroni, Luca
2013-08-01
We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the H -1-gradient flow of the total variation and represents a prototype of higher-order equations of similar type which are popular in imaging for denoising, deblurring and inpainting problems. The efficient numerical solution of this equation is very challenging due to the stiffness of most numerical schemes. We show that the combination of directional splitting schemes with implicit time-stepping provides a stable and computationally cheap numerical realisation of the equation.
Calatroni, Luca; Dü ring, Bertram; Schö nlieb, Carola-Bibiane
2013-01-01
We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the H -1-gradient flow of the total variation and represents a prototype of higher-order equations of similar type which are popular in imaging for denoising, deblurring and inpainting problems. The efficient numerical solution of this equation is very challenging due to the stiffness of most numerical schemes. We show that the combination of directional splitting schemes with implicit time-stepping provides a stable and computationally cheap numerical realisation of the equation.
Directory of Open Access Journals (Sweden)
Heinz Toparkus
2014-04-01
Full Text Available In this paper we consider first-order systems with constant coefficients for two real-valued functions of two real variables. This is both a problem in itself, as well as an alternative view of the classical linear partial differential equations of second order with constant coefficients. The classification of the systems is done using elementary methods of linear algebra. Each type presents its special canonical form in the associated characteristic coordinate system. Then you can formulate initial value problems in appropriate basic areas, and you can try to achieve a solution of these problems by means of transform methods.
A Generalized Partial Credit Model: Application of an EM Algorithm.
Muraki, Eiji
1992-01-01
The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)
International Nuclear Information System (INIS)
Li, Huihua
1992-01-01
The traditional generalization methods such as FIKE's macro-operator learning and Explanation-Based Learning (EBL) deal with totally ordered plans. They generalize only the plan operators and the conditions under which the generalized plan can be applied in its initial total order, but not the partial order among operators in which the generalized plan can be successfully executed. In this paper, we extend the notion of the EBL on the partial order of plans. A new method is presented for learning, from a totally or partially ordered plan, partially ordered macro-operators (generalized plans) each of which requires a set of the weakest conditions for its reuse. It is also valuable for generalizing partially ordered plans. The operators are generalized in the FIKE's triangle table. We introduce the domain axioms to generate the constraints for the consistency of generalized states. After completing the triangle table with the information concerning the operator destructions (interactions), we obtain the global explanation of the partial order on the operators. Then, we represent all the necessary ordering relations by a directed graph. The exploitation of this graph permits to explicate the dependence between the partial orders and the constraints among the parameters of generalized operators, and allows all the solutions to be obtained. (author) [fr
Nam, Sungsik; Alouini, Mohamed-Slim; Yang, Hongchuan
2010-01-01
Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs
Melt migration modeling in partially molten upper mantle
Ghods, Abdolreza
beneath the observed neo-volcanic zone. My models consist of three parts; lithosphere, asthenosphere and a melt extraction region. It is shown that melt migrates vertically within the asthenosphere, and forms a high melt fraction layer beneath the sloping base of the impermeable lithosphere. Within the sloping high melt fraction layer, melt migrates laterally towards the ridge. In order to simulate melt migration via crustal fractures and cracks, melt is extracted from a melt extraction region extending to the base of the crust. Performance of the melt focusing mechanism is not significantly sensitive to the size of melt extraction region, melt extraction threshold and spreading rate. In all of the models, about half of the total melt production freezes beneath the cooling base of the lithosphere, and the rest is effectively focused towards the ridge and forms the crust. To meet the computational demand for a precise tracing of the deforming upwelling plume and including the chemical buoyancy of the partially molten zone in my models, a new numerical method is developed to solve the related pure advection equations. The numerical method is based on Second Moment numerical method of Egan and Mahoney [1972] which is improved to maintain a high numerical accuracy in shear and rotational flow fields. In comparison with previous numerical methods, my numerical method is a cost-effective, non-diffusive and shape preserving method, and it can also be used to trace a deforming body in compressible flow fields.
Modeling of chromosome intermingling by partially overlapping uniform random polygons.
Blackstone, T; Scharein, R; Borgo, B; Varela, R; Diao, Y; Arsuaga, J
2011-03-01
During the early phase of the cell cycle the eukaryotic genome is organized into chromosome territories. The geometry of the interface between any two chromosomes remains a matter of debate and may have important functional consequences. The Interchromosomal Network model (introduced by Branco and Pombo) proposes that territories intermingle along their periphery. In order to partially quantify this concept we here investigate the probability that two chromosomes form an unsplittable link. We use the uniform random polygon as a crude model for chromosome territories and we model the interchromosomal network as the common spatial region of two overlapping uniform random polygons. This simple model allows us to derive some rigorous mathematical results as well as to perform computer simulations easily. We find that the probability that one uniform random polygon of length n that partially overlaps a fixed polygon is bounded below by 1 − O(1/√n). We use numerical simulations to estimate the dependence of the linking probability of two uniform random polygons (of lengths n and m, respectively) on the amount of overlapping. The degree of overlapping is parametrized by a parameter [Formula: see text] such that [Formula: see text] indicates no overlapping and [Formula: see text] indicates total overlapping. We propose that this dependence relation may be modeled as f (ε, m, n) = [Formula: see text]. Numerical evidence shows that this model works well when [Formula: see text] is relatively large (ε ≥ 0.5). We then use these results to model the data published by Branco and Pombo and observe that for the amount of overlapping observed experimentally the URPs have a non-zero probability of forming an unsplittable link.
Directory of Open Access Journals (Sweden)
Akira Shirai
2015-01-01
Full Text Available In this paper, we study the following nonlinear first order partial differential equation: \\[f(t,x,u,\\partial_t u,\\partial_x u=0\\quad\\text{with}\\quad u(0,x\\equiv 0.\\] The purpose of this paper is to determine the estimate of Gevrey order under the condition that the equation is singular of a totally characteristic type. The Gevrey order is indicated by the rate of divergence of a formal power series. This paper is a continuation of the previous papers [Convergence of formal solutions of singular first order nonlinear partial differential equations of totally characteristic type, Funkcial. Ekvac. 45 (2002, 187-208] and [Maillet type theorem for singular first order nonlinear partial differential equations of totally characteristic type, Surikaiseki Kenkyujo Kokyuroku, Kyoto University 1431 (2005, 94-106]. Especially the last-mentioned paper is regarded as part I of this paper.
Teaching Modeling with Partial Differential Equations: Several Successful Approaches
Myers, Joseph; Trubatch, David; Winkel, Brian
2008-01-01
We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…
Generalized Reduced Order Model Generation, Phase I
National Aeronautics and Space Administration — M4 Engineering proposes to develop a generalized reduced order model generation method. This method will allow for creation of reduced order aeroservoelastic state...
Partial differential equation models in the socio-economic sciences
Burger, Martin; Caffarelli, Luis; Markowich, Peter A.
2014-01-01
Mathematical models based on partial differential equations (PDEs) have become an integral part of quantitative analysis in most branches of science and engineering, recently expanding also towards biomedicine and socio-economic sciences
Partial differential equations of first order and their applications to physics
López, Gustavo
2012-01-01
This book tries to point out the mathematical importance of the Partial Differential Equations of First Order (PDEFO) in Physics and Applied Sciences. The intention is to provide mathematicians with a wide view of the applications of this branch in physics, and to give physicists and applied scientists a powerful tool for solving some problems appearing in Classical Mechanics, Quantum Mechanics, Optics, and General Relativity. This book is intended for senior or first year graduate students in mathematics, physics, or engineering curricula. This book is unique in the sense that it covers the applications of PDEFO in several branches of applied mathematics, and fills the theoretical gap between the formal mathematical presentation of the theory and the pure applied tool to physical problems that are contained in other books. Improvements made in this second edition include corrected typographical errors; rewritten text to improve the flow and enrich the material; added exercises in all chapters; new applicati...
Mathematical Modelling of Intraretinal Oxygen Partial Pressure
African Journals Online (AJOL)
Erah
The system of non-linear differential equations was solved numerically using Runge-kutta. Nystroms method. ... artery occlusion. Keywords: Mathematical modeling, Intraretinal oxygen pressure, Retinal capillaries, Oxygen ..... Mass transfer,.
Bayesian mixture models for partially verified data
DEFF Research Database (Denmark)
Kostoulas, Polychronis; Browne, William J.; Nielsen, Søren Saxmose
2013-01-01
for some individuals, in order to minimize this loss in the discriminatory power. The distribution of the continuous antibody response against MAP has been obtained for healthy, MAP-infected and MAP-infectious cows of different age groups. The overall power of the milk-ELISA to discriminate between healthy...... and MAP-infected cows was extremely poor but was high between healthy and MAP-infectious. The discriminatory ability increased with increasing age. The great overlap between the distributions of the different infection stages would have hampered our ability to discriminate between the different infection...
Partially natural Two Higgs Doublet Models
Energy Technology Data Exchange (ETDEWEB)
Draper, Patrick [Department of Physics, University of California,Broida Hall, Santa Barbara, CA 93106 (United States); Haber, Howard E. [Santa Cruz Institute for Particle Physics, University of California,1156 High Street, Santa Cruz, CA 95064 (United States); Kavli Institute for Theoretical Physics, University of California,Kohn Hall, Santa Barbara, CA 93106 (United States); Ruderman, Joshua T. [Center for Cosmology and Particle Physics, Department of Physics, New York University,4 Washington Pl. New York, NY 10003 (United States)
2016-06-21
It is possible that the electroweak scale is low due to the fine-tuning of microscopic parameters, which can result from selection effects. The experimental discovery of new light fundamental scalars other than the Standard Model Higgs boson would seem to disfavor this possibility, since generically such states imply parametrically worse fine-tuning with no compelling connection to selection effects. We discuss counterexamples where the Higgs boson is light because of fine-tuning, and a second scalar doublet is light because a discrete symmetry relates its mass to the mass of the Standard Model Higgs boson. Our examples require new vectorlike fermions at the electroweak scale, and the models possess a rich electroweak vacuum structure. The mechanism that we discuss does not protect a small CP-odd Higgs mass in split or high-scale supersymmetry-breaking scenarios of the MSSM due to an incompatibility between the discrete symmetries and holomorphy.
International Nuclear Information System (INIS)
Leaf, G.K.; Minkoff, M.
1982-01-01
1 - Description of problem or function: DISPL1 is a software package for solving second-order nonlinear systems of partial differential equations including parabolic, elliptic, hyperbolic, and some mixed types. The package is designed primarily for chemical kinetics- diffusion problems, although not limited to these problems. Fairly general nonlinear boundary conditions are allowed as well as inter- face conditions for problems in an inhomogeneous medium. The spatial domain is one- or two-dimensional with rectangular Cartesian, cylindrical, or spherical (in one dimension only) geometry. 2 - Method of solution: The numerical method is based on the use of Galerkin's procedure combined with the use of B-Splines (C.W.R. de-Boor's B-spline package) to generate a system of ordinary differential equations. These equations are solved by a sophisticated ODE software package which is a modified version of Hindmarsh's GEAR package, NESC Abstract 592. 3 - Restrictions on the complexity of the problem: The spatial domain must be rectangular with sides parallel to the coordinate geometry. Cross derivative terms are not permitted in the PDE. The order of the B-Splines is at most 12. Other parameters such as the number of mesh points in each coordinate direction, the number of PDE's etc. are set in a macro table used by the MORTRAn2 preprocessor in generating the object code
Variance Function Partially Linear Single-Index Models1.
Lian, Heng; Liang, Hua; Carroll, Raymond J
2015-01-01
We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.
Pirnapasov, Sardor; Karimov, Erkinjon
2017-01-01
In the present work we discuss higher order multi-term partial differential equation (PDE) with the Caputo-Fabrizio fractional derivative in time. We investigate a boundary value problem for fractional heat equation involving higher order Caputo-Fabrizio derivatives in time-variable. Using method of separation of variables and integration by parts, we reduce fractional order PDE to the integer order. We represent explicit solution of formulated problem in particular case by Fourier series.
Application of Stochastic Partial Differential Equations to Reservoir Property Modelling
Potsepaev, R.
2010-09-06
Existing algorithms of geostatistics for stochastic modelling of reservoir parameters require a mapping (the \\'uvt-transform\\') into the parametric space and reconstruction of a stratigraphic co-ordinate system. The parametric space can be considered to represent a pre-deformed and pre-faulted depositional environment. Existing approximations of this mapping in many cases cause significant distortions to the correlation distances. In this work we propose a coordinate free approach for modelling stochastic textures through the application of stochastic partial differential equations. By avoiding the construction of a uvt-transform and stratigraphic coordinates, one can generate realizations directly in the physical space in the presence of deformations and faults. In particular the solution of the modified Helmholtz equation driven by Gaussian white noise is a zero mean Gaussian stationary random field with exponential correlation function (in 3-D). This equation can be used to generate realizations in parametric space. In order to sample in physical space we introduce a stochastic elliptic PDE with tensor coefficients, where the tensor is related to correlation anisotropy and its variation is physical space.
Study and optimization of the partial discharges in capacitor model ...
African Journals Online (AJOL)
Page 1 ... experiments methodology for the study of such processes, in view of their modeling and optimization. The obtained result is a mathematical model capable to identify the parameters and the interactions between .... 5mn; the next landing is situated in 200 V over the voltage of partial discharges appearance and.
Understanding Rasch Measurement: Partial Credit Model and Pivot Anchoring.
Bode, Rita K.
2001-01-01
Describes the Rasch measurement partial credit model, what it is, how it differs from other Rasch models, and when and how to use it. Also describes the calibration of instruments with increasingly complex items. Explains pivot anchoring and illustrates its use and describes the effect of pivot anchoring on step calibrations, item hierarchy, and…
Carlsen, Lars; Bruggemann, Rainer
2018-06-03
In chemistry there is a long tradition in classification. Usually methods are adopted from the wide field of cluster analysis. Here, based on the example of 21 alkyl anilines we show that also concepts taken out from the mathematical discipline of partially ordered sets may also be applied. The chemical compounds are described by a multi-indicator system. For the present study four indicators, mainly taken from the field of environmental chemistry were applied and a Hasse diagram was constructed. A Hasse diagram is an acyclic, transitively reduced, triangle free graph that may have several components. The crucial question is, whether or not the Hasse diagram can be interpreted from a structural chemical point of view. This is indeed the case, but it must be clearly stated that a guarantee for meaningful results in general cannot be given. For that further theoretical work is needed. Two cluster analysis methods are applied (K-means and a hierarchical cluster method). In both cases the partitioning of the set of 21 compounds by the component structure of the Hasse diagram appears to be better interpretable. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
The Interplay between QSAR/QSPR Studiesand Partial Order Ranking and Formal Concept Analyses
Directory of Open Access Journals (Sweden)
Lars Carlsen
2009-04-01
Full Text Available The often observed scarcity of physical-chemical and well as toxicological data hampers the assessment of potentially hazardous chemicals released to the environment. In such cases Quantitative Structure-Activity Relationships/Quantitative Structure-Property Relationships (QSAR/QSPR constitute an obvious alternative for rapidly, effectively and inexpensively generatng missing experimental values. However, typically further treatment of the data appears necessary, e.g., to elucidate the possible relations between the single compounds as well as implications and associations between the various parameters used for the combined characterization of the compounds under investigation. In the present paper the application of QSAR/QSPR in combination with Partial Order Ranking (POR methodologies will be reviewed and new aspects using Formal Concept Analysis (FCA will be introduced. Where POR constitutes an attractive method for, e.g., prioritizing a series of chemical substances based on a simultaneous inclusion of a range of parameters, FCA gives important information on the implications associations between the parameters. The combined approach thus constitutes an attractive method to a preliminary assessment of the impact on environmental and human health by primary pollutants or possibly by a primary pollutant well as a possible suite of transformation subsequent products that may be both persistent in and bioaccumulating and toxic.The present review focus on the environmental – and human health impact by residuals of the rocket fuel 1,1-dimethyl- hydrazine (heptyl and its transformation products as an illustrative example.
International Nuclear Information System (INIS)
Rassafi, A.M.; Vaziri, M.
2006-01-01
This study attempts to characterize national passenger and freight transportation sustainability. Based on the indicator that measures the conformity of the growths of all sectors with transportation, the Islamic countries are comparatively studied. The proposed measure, elasticity for each pair of variables indicates the extent to which the two variables have been changing consistently. The study database consisted of key aspects of transportation sustainability in the form of national variables including transportation, economic, social and environmental categories for the period 1980-1995. Firstly, the elasticity of social, environmental and economic variables with respect to passenger and freight transportation variables was developed. Using individual elasticities, composite passengers and freight sustainability indices were suggested. Then, utilizing partial order theory and Hasse Diagram Technique (HDT), two composite indices were employed to visualize the comparative situation of the countries. Based on comparative appraisal achieved by HDT, country ranking were developed. The methodology may be applied to any other time and geographic area for addressing pertinent issues for balancing and sustainable development of transportation systems. (author)
High-order asynchrony-tolerant finite difference schemes for partial differential equations
Aditya, Konduri; Donzis, Diego A.
2017-12-01
Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalability of scientific applications. We have recently proposed a method based on finite-difference schemes to solve partial differential equations in an asynchronous fashion - synchronization between PEs is relaxed at a mathematical level. While standard schemes can maintain their stability in the presence of asynchrony, their accuracy is drastically affected. In this work, we present a general methodology to derive asynchrony-tolerant (AT) finite difference schemes of arbitrary order of accuracy, which can maintain their accuracy when synchronizations are relaxed. We show that there are several choices available in selecting a stencil to derive these schemes and discuss their effect on numerical and computational performance. We provide a simple classification of schemes based on the stencil and derive schemes that are representative of different classes. Their numerical error is rigorously analyzed within a statistical framework to obtain the overall accuracy of the solution. Results from numerical experiments are used to validate the performance of the schemes.
Optimal inventory management and order book modeling
Baradel, Nicolas; Bouchard, Bruno; Evangelista, David; Mounjid, Othmane
2018-01-01
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic
Fractional Order Models of Industrial Pneumatic Controllers
Directory of Open Access Journals (Sweden)
Abolhassan Razminia
2014-01-01
Full Text Available This paper addresses a new approach for modeling of versatile controllers in industrial automation and process control systems such as pneumatic controllers. Some fractional order dynamical models are developed for pressure and pneumatic systems with bellows-nozzle-flapper configuration. In the light of fractional calculus, a fractional order derivative-derivative (FrDD controller and integral-derivative (FrID are remodeled. Numerical simulations illustrate the application of the obtained theoretical results in simple examples.
Directory of Open Access Journals (Sweden)
Woosang Lim
Full Text Available Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical areas. In this paper, we present a new method that discovers hierarchical structures of macaque brain networks by using partial information of pairwise hierarchical relationships. Our method uses a graph-based manifold learning to exploit inherent relationship, and computes pseudo distances of hierarchical levels for every pair of cortical areas. Then, we compute hierarchy levels of all cortical areas by minimizing the sum of squared hierarchical distance errors with the hierarchical information of few cortical areas. We evaluate our method on the macaque brain data sets whose true hierarchical levels are known as the FV91 model. The experimental results show that hierarchy levels computed by our method are similar to the FV91 model, and its errors are much smaller than the errors of hierarchical clustering approaches.
Owolabi, Kolade M.
2017-03-01
In this paper, some nonlinear space-fractional order reaction-diffusion equations (SFORDE) on a finite but large spatial domain x ∈ [0, L], x = x(x , y , z) and t ∈ [0, T] are considered. Also in this work, the standard reaction-diffusion system with boundary conditions is generalized by replacing the second-order spatial derivatives with Riemann-Liouville space-fractional derivatives of order α, for 0 Fourier spectral method is introduced as a better alternative to existing low order schemes for the integration of fractional in space reaction-diffusion problems in conjunction with an adaptive exponential time differencing method, and solve a range of one-, two- and three-components SFORDE numerically to obtain patterns in one- and two-dimensions with a straight forward extension to three spatial dimensions in a sub-diffusive (0 reaction-diffusion case. With application to models in biology and physics, different spatiotemporal dynamics are observed and displayed.
Thangam, A.
2015-06-01
In today's fast marketing over the Internet or online, many retailers want to trade at the same time and change their marketing strategy to attract more customers. Some of the customers may decide to cancel their orders partially with a retailer due to various reasons such as increase in customer's waiting time, loss of customer's goodwill on retailer's business, attractive promotional schemes offered by other retailers etc. Even though there is a lag in trading and order cancelation, this paper attempts to develop the retailer's inventory model with the effect of order cancelations during advance sales period. The retailer announces a price discount program during advance sales period to promote his sales and also he offers trade credit financing during the sales periods. The retailer availing trade credit period from his supplier offers a permissible delay period to his customers. The customer who gets an item has allowed paying on or before the permissible delay period which is accounted from the buying time rather than the start period of inventory sales. This accounts for significant changes in the calculations of interest payable and interest earned by the retailer. The retailer's total cost is minimized so as to find out the optimal replenishment cycle time and price discount policies through a solution procedure. The results derived in mathematical theorems are implemented in numerical examples and sensitivity analyses on several inventory parameters are obtained.
Thangam, A.
2014-02-01
In today's fast marketing over the Internet or online, many retailers want to trade at the same time and change their marketing strategy to attract more customers. Some of the customers may decide to cancel their orders partially with a retailer due to various reasons such as increase in customer's waiting time, loss of customer's goodwill on retailer's business, and attractive promotional schemes offered by other retailers. Even though there is a lag in trading and order cancellation, this paper attempts to develop the retailer's inventory model with the effect of order cancellations during advance sales period. The retailer announces a price discount program during advance sales period to promote his sales and also offers trade credit financing during the sales periods. The retailer availing trade credit period from his supplier offers a permissible delay period to his customers. The customer who gets an item is allowed to pay on or before the permissible delay period which is accounted from the buying time rather than from the start period of inventory sales. This accounts for significant changes in the calculations of interest payable and interest earned by the retailer. The retailer's total cost is minimized so as to find out the optimal replenishment cycle time and price discount policies through a solution procedure. The results derived in mathematical theorems are implemented in numerical examples, and sensitivity analyses on several inventory parameters are obtained.
Centrifuge modeling of LNAPL transport in partially saturated sand
Esposito, G.; Allersma, H.G.B.; Selvadurai, A.P.S.
1999-01-01
Model tests were performed at the Geotechnical Centrifuge Facility of Delft University of Technology, The Netherlands, to examine the mechanics of light nonaqueous phase liquid (LNAPL) movement in a partially saturated porous granular medium. The experiment simulated a 2D spill of LNAPL in an
Detecting Math Anxiety with a Mixture Partial Credit Model
Ölmez, Ibrahim Burak; Cohen, Allan S.
2017-01-01
The purpose of this study was to investigate a new methodology for detection of differences in middle grades students' math anxiety. A mixture partial credit model analysis revealed two distinct latent classes based on homogeneities in response patterns within each latent class. Students in Class 1 had less anxiety about apprehension of math…
XY model with higher-order exchange.
Žukovič, Milan; Kalagov, Georgii
2017-08-01
An XY model, generalized by inclusion of up to an infinite number of higher-order pairwise interactions with an exponentially decreasing strength, is studied by spin-wave theory and Monte Carlo simulations. At low temperatures the model displays a quasi-long-range-order phase characterized by an algebraically decaying correlation function with the exponent η=T/[2πJ(p,α)], nonlinearly dependent on the parameters p and α that control the number of the higher-order terms and the decay rate of their intensity, respectively. At higher temperatures the system shows a crossover from the continuous Berezinskii-Kosterlitz-Thouless to the first-order transition for the parameter values corresponding to a highly nonlinear shape of the potential well. The role of topological excitations (vortices) in changing the nature of the transition is discussed.
Taylor, Lawrence W., Jr.; Rajiyah, H.
1991-01-01
Partial differential equations for modeling the structural dynamics and control systems of flexible spacecraft are applied here in order to facilitate systems analysis and optimization of these spacecraft. Example applications are given, including the structural dynamics of SCOLE, the Solar Array Flight Experiment, the Mini-MAST truss, and the LACE satellite. The development of related software is briefly addressed.
Optimal Designs for the Generalized Partial Credit Model
Bürkner, Paul-Christian; Schwabe, Rainer; Holling, Heinz
2018-01-01
Analyzing ordinal data becomes increasingly important in psychology, especially in the context of item response theory. The generalized partial credit model (GPCM) is probably the most widely used ordinal model and finds application in many large scale educational assessment studies such as PISA. In the present paper, optimal test designs are investigated for estimating persons' abilities with the GPCM for calibrated tests when item parameters are known from previous studies. We will derive t...
DEFF Research Database (Denmark)
Øjelund, Henrik; Sadegh, Payman
2000-01-01
be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....
Dynamical models of happiness with fractional order
Song, Lei; Xu, Shiyun; Yang, Jianying
2010-03-01
This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.
Hybrid reduced order modeling for assembly calculations
International Nuclear Information System (INIS)
Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; Mertyurek, Ugur
2015-01-01
Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.
Hybrid reduced order modeling for assembly calculations
Energy Technology Data Exchange (ETDEWEB)
Bang, Youngsuk, E-mail: ysbang00@fnctech.com [FNC Technology, Co. Ltd., Yongin-si (Korea, Republic of); Abdel-Khalik, Hany S., E-mail: abdelkhalik@purdue.edu [Purdue University, West Lafayette, IN (United States); Jessee, Matthew A., E-mail: jesseema@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States); Mertyurek, Ugur, E-mail: mertyurek@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States)
2015-12-15
Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.
Nam, Sungsik
2010-11-01
Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks(Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels. © 2006 IEEE.
Reduced-order modelling of wind turbines
Elkington, K.; Slootweg, J.G.; Ghandhari, M.; Kling, W.L.; Ackermann, T.
2012-01-01
In this chapter power system dynamics simulation(PSDS) isused to study the dynamics of large-scale power systems. It is necessary to incorporate models of wind turbine generating systems into PSDS software packages in order to analyse the impact of high wind power penetration on electrical power
International Nuclear Information System (INIS)
Tran Duc Van
1994-01-01
The notion of global quasi-classical solutions of the Cauchy problems for first-order nonlinear partial differential equations is presented, some uniqueness theorems and a stability result are established by the method based on the theory of differential inclusions. In particular, the answer to an open problem of S.N. Kruzhkov is given. (author). 10 refs, 1 fig
Denche, M.; Marhoune, A. L.
2001-01-01
We study a mixed problem with integral boundary conditions for a third-order partial differential equation of mixed type. We prove the existence and uniqueness of the solution. The proof is based on two-sided a priori estimates and on the density of the range of the operator generated by the considered problem.
Declarative Modeling for Production Order Portfolio Scheduling
Directory of Open Access Journals (Sweden)
Banaszak Zbigniew
2014-12-01
Full Text Available A declarative framework enabling to determine conditions as well as to develop decision-making software supporting small- and medium-sized enterprises aimed at unique, multi-project-like and mass customized oriented production is discussed. A set of unique production orders grouped into portfolio orders is considered. Operations executed along different production orders share available resources following a mutual exclusion protocol. A unique product or production batch is completed while following a given activity’s network order. The problem concerns scheduling a newly inserted project portfolio subject to constraints imposed by a multi-project environment The answers sought are: Can a given project portfolio specified by its cost and completion time be completed within the assumed time period in a manufacturing system in hand? Which manufacturing system capability guarantees the completion of a given project portfolio ordered under assumed cost and time constraints? The considered problems regard finding a computationally effective approach aimed at simultaneous routing and allocation as well as batching and scheduling of a newly ordered project portfolio subject to constraints imposed by a multi-project environment. The main objective is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi-project-like and mass customized oriented production scheduling. Multiple illustrative examples are discussed.
Zheng, Guo; Wang, Jue; Wang, Lin; Zhou, Muchun; Xin, Yu; Song, Minmin
2017-11-15
The general formulae for second-order moments of Schell-model beams with various correlation functions in atmospheric turbulence are derived and validated by the Bessel-Gaussian Schell-model beams and cosine-Gaussian-correlated Schell-model beams. Our finding shows that the second-order moments of partially coherent Schell-model beams are related to the second-order partial derivatives of source spectral degree of coherence at the origin. The formulae we provide are much more convenient to analyze and research propagation problems in turbulence.
Estimating varying coefficients for partial differential equation models.
Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J
2017-09-01
Partial differential equations (PDEs) are used to model complex dynamical systems in multiple dimensions, and their parameters often have important scientific interpretations. In some applications, PDE parameters are not constant but can change depending on the values of covariates, a feature that we call varying coefficients. We propose a parameter cascading method to estimate varying coefficients in PDE models from noisy data. Our estimates of the varying coefficients are shown to be consistent and asymptotically normally distributed. The performance of our method is evaluated by a simulation study and by an empirical study estimating three varying coefficients in a PDE model arising from LIDAR data. © 2017, The International Biometric Society.
Xing, Yanyuan; Yan, Yubin
2018-03-01
Gao et al. [11] (2014) introduced a numerical scheme to approximate the Caputo fractional derivative with the convergence rate O (k 3 - α), 0 equation is sufficiently smooth, Lv and Xu [20] (2016) proved by using energy method that the corresponding numerical method for solving time fractional partial differential equation has the convergence rate O (k 3 - α), 0 equation has low regularity and in this case the numerical method fails to have the convergence rate O (k 3 - α), 0 quadratic interpolation polynomials. Based on this scheme, we introduce a time discretization scheme to approximate the time fractional partial differential equation and show by using Laplace transform methods that the time discretization scheme has the convergence rate O (k 3 - α), 0 0 for smooth and nonsmooth data in both homogeneous and inhomogeneous cases. Numerical examples are given to show that the theoretical results are consistent with the numerical results.
Hybrid reduced order modeling for assembly calculations
Energy Technology Data Exchange (ETDEWEB)
Bang, Y.; Abdel-Khalik, H. S. [North Carolina State University, Raleigh, NC (United States); Jessee, M. A.; Mertyurek, U. [Oak Ridge National Laboratory, Oak Ridge, TN (United States)
2013-07-01
While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system. (authors)
Emulating facial biomechanics using multivariate partial least squares surrogate models.
Wu, Tim; Martens, Harald; Hunter, Peter; Mithraratne, Kumar
2014-11-01
A detailed biomechanical model of the human face driven by a network of muscles is a useful tool in relating the muscle activities to facial deformations. However, lengthy computational times often hinder its applications in practical settings. The objective of this study is to replace precise but computationally demanding biomechanical model by a much faster multivariate meta-model (surrogate model), such that a significant speedup (to real-time interactive speed) can be achieved. Using a multilevel fractional factorial design, the parameter space of the biomechanical system was probed from a set of sample points chosen to satisfy maximal rank optimality and volume filling. The input-output relationship at these sampled points was then statistically emulated using linear and nonlinear, cross-validated, partial least squares regression models. It was demonstrated that these surrogate models can mimic facial biomechanics efficiently and reliably in real-time. Copyright © 2014 John Wiley & Sons, Ltd.
semPLS: Structural Equation Modeling Using Partial Least Squares
Directory of Open Access Journals (Sweden)
Armin Monecke
2012-05-01
Full Text Available Structural equation models (SEM are very popular in many disciplines. The partial least squares (PLS approach to SEM offers an alternative to covariance-based SEM, which is especially suited for situations when data is not normally distributed. PLS path modelling is referred to as soft-modeling-technique with minimum demands regarding mea- surement scales, sample sizes and residual distributions. The semPLS package provides the capability to estimate PLS path models within the R programming environment. Different setups for the estimation of factor scores can be used. Furthermore it contains modular methods for computation of bootstrap confidence intervals, model parameters and several quality indices. Various plot functions help to evaluate the model. The well known mobile phone dataset from marketing research is used to demonstrate the features of the package.
Hidden physics models: Machine learning of nonlinear partial differential equations
Raissi, Maziar; Karniadakis, George Em
2018-03-01
While there is currently a lot of enthusiasm about "big data", useful data is usually "small" and expensive to acquire. In this paper, we present a new paradigm of learning partial differential equations from small data. In particular, we introduce hidden physics models, which are essentially data-efficient learning machines capable of leveraging the underlying laws of physics, expressed by time dependent and nonlinear partial differential equations, to extract patterns from high-dimensional data generated from experiments. The proposed methodology may be applied to the problem of learning, system identification, or data-driven discovery of partial differential equations. Our framework relies on Gaussian processes, a powerful tool for probabilistic inference over functions, that enables us to strike a balance between model complexity and data fitting. The effectiveness of the proposed approach is demonstrated through a variety of canonical problems, spanning a number of scientific domains, including the Navier-Stokes, Schrödinger, Kuramoto-Sivashinsky, and time dependent linear fractional equations. The methodology provides a promising new direction for harnessing the long-standing developments of classical methods in applied mathematics and mathematical physics to design learning machines with the ability to operate in complex domains without requiring large quantities of data.
A Measure of the Conformity of a Parameter Set to a Trend: The Partially Ordered Case.
1983-05-01
A-A3214 A MEASURE OF THE CONFORMIYO QAPARAMEfERSETO QA / TREND: THE PARTIAL .U) IOWA UNIV IOWA CIT DEPT OF ......STATISTICS AND ACTURIAL SCIENCE.T...and j with i o j. Such a vector 0 = (Oi,0j,.... 0k is said to be isotone (with respect to _). In studying such inference procedures it is helpful to...noticed that none of the measures studied here are applicable in alIl the situations considered. In studying locat ion pa rameter- wlhich are not
Reduced order methods for modeling and computational reduction
Rozza, Gianluigi
2014-01-01
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics. Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...
Optimal Retail Price Model for Partial Consignment to Multiple Retailers
Directory of Open Access Journals (Sweden)
Po-Yu Chen
2017-01-01
Full Text Available This paper investigates the product pricing decision-making problem under a consignment stock policy in a two-level supply chain composed of one supplier and multiple retailers. The effects of the supplier’s wholesale prices and its partial inventory cost absorption of the retail prices of retailers with different market shares are investigated. In the partial product consignment model this paper proposes, the seller and the retailers each absorb part of the inventory costs. This model also provides general solutions for the complete product consignment and the traditional policy that adopts no product consignment. In other words, both the complete consignment and nonconsignment models are extensions of the proposed model (i.e., special cases. Research results indicated that the optimal retail price must be between 1/2 (50% and 2/3 (66.67% times the upper limit of the gross profit. This study also explored the results and influence of parameter variations on optimal retail price in the model.
Reduced Order Modeling in General Relativity
Tiglio, Manuel
2014-03-01
Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).
Directory of Open Access Journals (Sweden)
Brian Godsey
Full Text Available MicroRNAs (miRs are known to play an important role in mRNA regulation, often by binding to complementary sequences in "target" mRNAs. Recently, several methods have been developed by which existing sequence-based target predictions can be combined with miR and mRNA expression data to infer true miR-mRNA targeting relationships. It has been shown that the combination of these two approaches gives more reliable results than either by itself. While a few such algorithms give excellent results, none fully addresses expression data sets with a natural ordering of the samples. If the samples in an experiment can be ordered or partially ordered by their expected similarity to one another, such as for time-series or studies of development processes, stages, or types, (e.g. cell type, disease, growth, aging, there are unique opportunities to infer miR-mRNA interactions that may be specific to the underlying processes, and existing methods do not exploit this. We propose an algorithm which specifically addresses [partially] ordered expression data and takes advantage of sample similarities based on the ordering structure. This is done within a Bayesian framework which specifies posterior distributions and therefore statistical significance for each model parameter and latent variable. We apply our model to a previously published expression data set of paired miR and mRNA arrays in five partially ordered conditions, with biological replicates, related to multiple myeloma, and we show how considering potential orderings can improve the inference of miR-mRNA interactions, as measured by existing knowledge about the involved transcripts.
MODEL PENSKORAN PARTIAL CREDIT PADA BUTIR MULTIPLE TRUE-FALSE BIDANG FISIKA
Directory of Open Access Journals (Sweden)
Wasis Wasis
2013-01-01
Full Text Available Tujuan penelitian ini menghasilkan model penskoran politomus untuk respons butir multiple true-false, sehingga dapat mengestimasi secara lebih akurat kemampuan di bidang fisika. Pengembangan penskoran menggunakan Four-D model dan diuji akurasinya melalui penelitian empiris dan simulasi. Penelitian empiris menggunakan 15 butir multiple true-false yang diambil dari soal UMPTN tahun 1996-2006 dan dikenakan pada 410 mahasiswa baru FMIPA Universitas Negeri Surabaya angkatan tahun 2007. Respons peserta tes diskor dengan tiga model partial credit (PCM I; II; dan III dan secara dikotomus. Hasil penskoran dianalisis dengan program Quest untuk mendapat-kan estimasi tingkat kesukaran butir (δ dan estimasi ke-mampuan peserta (θ untuk menentukan nilai fungsi informasi tes dan kesalahan baku estimasi. Penelitian simulasi mengguna-kan data bangkitan berdasarkan parameter empiris (δ dan θ memakai program statistik SAS dan akurasi estimasinya di-analisis dengan metode root mean squared error (RMSE. Hasil penelitian ini menunjukkan: (i Penskoran PCM dengan pem-bobotan mampu mengestimasi kemampuan lebih akurat di-bandingkan tanpa pembobotan maupun secara dikotomus; (ii Semakin banyak jumlah kategori dalam penskoran partial credit, semakin akurat. Kata kunci: model penskoran partial credit, butir multiple true-false ____________________________________________________________ THE PARTIAL CREDIT SCORING MODEL FOR THE MULTIPLE TRUE-FALSE BUTIRS IN PHYSICS Abstract This study is an attempt to overcome the weaknesses. This study aims to produce a polytomous scoring model for responses to multiple true-false butirs in order to get a more accurate estimation of abilities in physics. It adopts the Four-D model and its accuracy is assessed through empirical and simulation studies. The empirical study employed 15 multiple true-false butirs taken from the New Students Entrance Test of State University the year of 1996–2006. It administered to 410 new students enrolled
International Nuclear Information System (INIS)
Jarnicki, R.; Sobiesiak, A.
2002-01-01
In order to solve the averaged conservation equations for turbulent reacting flow one is faced with a task of specifying the averaged chemical reaction rate. This is due to turbulence influence on the mean reaction rates that appear in the species concentration Reynolds-averaged equation. In order to investigate the Partially Stirred Reactor (PaSR) combustion model capabilities, a CFD modeling using KIVA3V Code with the PaSR model of two very different combustion processes, was performed. Experimental results were compared with modeling
Bayesian Plackett-Luce Mixture Models for Partially Ranked Data.
Mollica, Cristina; Tardella, Luca
2017-06-01
The elicitation of an ordinal judgment on multiple alternatives is often required in many psychological and behavioral experiments to investigate preference/choice orientation of a specific population. The Plackett-Luce model is one of the most popular and frequently applied parametric distributions to analyze rankings of a finite set of items. The present work introduces a Bayesian finite mixture of Plackett-Luce models to account for unobserved sample heterogeneity of partially ranked data. We describe an efficient way to incorporate the latent group structure in the data augmentation approach and the derivation of existing maximum likelihood procedures as special instances of the proposed Bayesian method. Inference can be conducted with the combination of the Expectation-Maximization algorithm for maximum a posteriori estimation and the Gibbs sampling iterative procedure. We additionally investigate several Bayesian criteria for selecting the optimal mixture configuration and describe diagnostic tools for assessing the fitness of ranking distributions conditionally and unconditionally on the number of ranked items. The utility of the novel Bayesian parametric Plackett-Luce mixture for characterizing sample heterogeneity is illustrated with several applications to simulated and real preference ranked data. We compare our method with the frequentist approach and a Bayesian nonparametric mixture model both assuming the Plackett-Luce model as a mixture component. Our analysis on real datasets reveals the importance of an accurate diagnostic check for an appropriate in-depth understanding of the heterogenous nature of the partial ranking data.
Empirical Reduced-Order Modeling for Boundary Feedback Flow Control
Directory of Open Access Journals (Sweden)
Seddik M. Djouadi
2008-01-01
Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.
Are Quantum Models for Order Effects Quantum?
Moreira, Catarina; Wichert, Andreas
2017-12-01
The application of principles of Quantum Mechanics in areas outside of physics has been getting increasing attention in the scientific community in an emergent disciplined called Quantum Cognition. These principles have been applied to explain paradoxical situations that cannot be easily explained through classical theory. In quantum probability, events are characterised by a superposition state, which is represented by a state vector in a N-dimensional vector space. The probability of an event is given by the squared magnitude of the projection of this superposition state into the desired subspace. This geometric approach is very useful to explain paradoxical findings that involve order effects, but do we really need quantum principles for models that only involve projections? This work has two main goals. First, it is still not clear in the literature if a quantum projection model has any advantage towards a classical projection. We compared both models and concluded that the Quantum Projection model achieves the same results as its classical counterpart, because the quantum interference effects play no role in the computation of the probabilities. Second, it intends to propose an alternative relativistic interpretation for rotation parameters that are involved in both classical and quantum models. In the end, instead of interpreting these parameters as a similarity measure between questions, we propose that they emerge due to the lack of knowledge concerned with a personal basis state and also due to uncertainties towards the state of world and towards the context of the questions.
Estimation and variable selection for generalized additive partial linear models
Wang, Li
2011-08-01
We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.
Partial differential equation models in the socio-economic sciences.
Burger, Martin; Caffarelli, Luis; Markowich, Peter A
2014-11-13
Mathematical models based on partial differential equations (PDEs) have become an integral part of quantitative analysis in most branches of science and engineering, recently expanding also towards biomedicine and socio-economic sciences. The application of PDEs in the latter is a promising field, but widely quite open and leading to a variety of novel mathematical challenges. In this introductory article of the Theme Issue, we will provide an overview of the field and its recent boosting topics. Moreover, we will put the contributions to the Theme Issue in an appropriate perspective. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Partial differential equation models in the socio-economic sciences
Burger, Martin
2014-10-06
Mathematical models based on partial differential equations (PDEs) have become an integral part of quantitative analysis in most branches of science and engineering, recently expanding also towards biomedicine and socio-economic sciences. The application of PDEs in the latter is a promising field, but widely quite open and leading to a variety of novel mathematical challenges. In this introductory article of the Theme Issue, we will provide an overview of the field and its recent boosting topics. Moreover, we will put the contributions to the Theme Issue in an appropriate perspective.
A Model Fit Statistic for Generalized Partial Credit Model
Liang, Tie; Wells, Craig S.
2009-01-01
Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…
Consistent Partial Least Squares Path Modeling via Regularization.
Jung, Sunho; Park, JaeHong
2018-01-01
Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.
Driving Forces of the Self-Assembly of Supramolecular Systems: Partially Ordered Mesophases
Shcherbina, M. A.; Chvalun, S. N.
2018-06-01
The main aspects are considered of the self-organization of a new class of liquid crystalline compounds, rigid sector-shaped and cone-shaped dendrons. Theoretical approaches to the self-assembly of different amphiphilic compounds (lipids, bolaamphiphiles, block copolymers, and polyelectrolytes) are described. Particular attention is given to the mesophase structures that emerge during the self-organization of mesophases characterized by intermediate degrees of ordering, e.g., plastic crystals, the rotation-crystalline phase in polymers, ordered and disordered two-dimensional columnar phases, and bicontinuous cubic phases of different symmetry.
Modeling Ability Differentiation in the Second-Order Factor Model
Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.
2011-01-01
In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…
Czech Academy of Sciences Publication Activity Database
Escudero, C.; Gazzola, F.; Hakl, Robert; Torres, P.J.
2015-01-01
Roč. 140, č. 4 (2015), s. 385-393 ISSN 0862-7959 Institutional support: RVO:67985840 Keywords : higher order parabolic equation * existence of solution * blow-up in finite time Subject RIV: BA - General Mathematics http://hdl.handle.net/10338.dmlcz/144457
OUTLIER DETECTION IN PARTIAL ERRORS-IN-VARIABLES MODEL
Directory of Open Access Journals (Sweden)
JUN ZHAO
Full Text Available The weighed total least square (WTLS estimate is very sensitive to the outliers in the partial EIV model. A new procedure for detecting outliers based on the data-snooping is presented in this paper. Firstly, a two-step iterated method of computing the WTLS estimates for the partial EIV model based on the standard LS theory is proposed. Secondly, the corresponding w-test statistics are constructed to detect outliers while the observations and coefficient matrix are contaminated with outliers, and a specific algorithm for detecting outliers is suggested. When the variance factor is unknown, it may be estimated by the least median squares (LMS method. At last, the simulated data and real data about two-dimensional affine transformation are analyzed. The numerical results show that the new test procedure is able to judge that the outliers locate in x component, y component or both components in coordinates while the observations and coefficient matrix are contaminated with outliers
Analysis of the radial distribution curves of partially ordered condensed carbon films
International Nuclear Information System (INIS)
Palatnik, L.S.; Derevyanchenko, A.S.; Nechitajlo, A.A.; Stetsenko, A.N.; Gorbenko, N.I.
1977-01-01
The Fourier analysis of the electron scattering curves has been carried out to determine the short-range order structure of carbon condensates. The intensity curves for carbon films condensed in a approximately 10 -6 Torr vacuum upon a substrate heated up to 600 deg C were obtained by diffraction techniques with filtration of the inelastic scattered electron background. The radial distribution curve errors were analyzed and quantified with the aid of a computer to determine the short-range order of the condensed carbon. It has been shown that carbon films consist of regions measuring approximately 20 A formed by parallelly packed graphite nets with azimuthal orientation different from that in ideal graphite crystals
Synthesis of partially graphitic ordered mesoporous carbons with high surface areas
Energy Technology Data Exchange (ETDEWEB)
Gao, Wenjun; Wan, Ying [Department of Chemistry, Key Laboratory of Resource Chemistry of Ministry of Education, Shanghai Normal University, Shanghai 200234 (China); Dou, Yuqian; Zhao, Dongyuan [Department of Chemistry, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Fudan University, Shanghai 200433 (China)
2011-01-01
Graphitic carbons with ordered mesostructure and high surface areas (of great interest in applications such as energy storage) have been synthesized by a direct triblock-copolymer-templating method. Pluronic F127 is used as a structure-directing agent, with a low-molecular-weight phenolic resol as a carbon source, ferric oxide as a catalyst, and silica as an additive. Inorganic oxides can be completely eliminated from the carbon. Small-angle XRD and N{sub 2} sorption analysis show that the resultant carbon materials possess an ordered 2D hexagonal mesostructure, uniform bimodal mesopores (about 1.5 and 6 nm), high surface area ({proportional_to}1300 m{sup 2}/g), and large pore volumes ({proportional_to}1.50 cm{sup 3}/g) after low-temperature pyrolysis (900 C). All surface areas come from mesopores. Wide-angle XRD patterns demonstrate that the presence of the ferric oxide catalyst and the silica additive lead to a marked enhancement of graphitic ordering in the framework. Raman spectra provide evidence of the increased content of graphitic sp{sup 2} carbon structures. Transmission electron microscopy images confirm that numerous domains in the ordered mesostructures are composed of characteristic graphitic carbon nanostructures. The evolution of the graphitic structure is dependent on the temperature and the concentrations of the silica additive, and ferric oxide catalyst. Electrochemical measurements performed on this graphitic mesoporous carbon when used as an electrode material for an electrochemical double layer capacitor shows rectangular-shaped cyclic voltammetry curves over a wide range of scan rates, even up to 200 mV/s, with a large capacitance of 155 F/g in KOH electrolyte. This method can be widely applied to the synthesis of graphitized carbon nanostructures. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Optimization Method of Fusing Model Tree into Partial Least Squares
Directory of Open Access Journals (Sweden)
Yu Fang
2017-01-01
Full Text Available Partial Least Square (PLS can’t adapt to the characteristics of the data of many fields due to its own features multiple independent variables, multi-dependent variables and non-linear. However, Model Tree (MT has a good adaptability to nonlinear function, which is made up of many multiple linear segments. Based on this, a new method combining PLS and MT to analysis and predict the data is proposed, which build MT through the main ingredient and the explanatory variables(the dependent variable extracted from PLS, and extract residual information constantly to build Model Tree until well-pleased accuracy condition is satisfied. Using the data of the maxingshigan decoction of the monarch drug to treat the asthma or cough and two sample sets in the UCI Machine Learning Repository, the experimental results show that, the ability of explanation and predicting get improved in the new method.
Modeling tree crown dynamics with 3D partial differential equations.
Beyer, Robert; Letort, Véronique; Cournède, Paul-Henry
2014-01-01
We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth toward light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
An XFEM Model for Hydraulic Fracturing in Partially Saturated Rocks
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Salimzadeh Saeed
2016-01-01
Full Text Available Hydraulic fracturing is a complex multi-physics phenomenon. Numerous analytical and numerical models of hydraulic fracturing processes have been proposed. Analytical solutions commonly are able to model the growth of a single hydraulic fracture into an initially intact, homogeneous rock mass. Numerical models are able to analyse complex problems such as multiple hydraulic fractures and fracturing in heterogeneous media. However, majority of available models are restricted to single-phase flow through fracture and permeable porous rock. This is not compatible with actual field conditions where the injected fluid does not have similar properties as the host fluid. In this study we present a fully coupled hydro-poroelastic model which incorporates two fluids i.e. fracturing fluid and host fluid. Flow through fracture is defined based on lubrication assumption, while flow through matrix is defined as Darcy flow. The fracture discontinuity in the mechanical model is captured using eXtended Finite Element Method (XFEM while the fracture propagation criterion is defined through cohesive fracture model. The discontinuous matrix fluid velocity across fracture is modelled using leak-off loading which couples fracture flow and matrix flow. The proposed model has been discretised using standard Galerkin method, implemented in Matlab and verified against several published solutions. Multiple hydraulic fracturing simulations are performed to show the model robustness and to illustrate how problem parameters such as injection rate and rock permeability affect the hydraulic fracturing variables i.e. injection pressure, fracture aperture and fracture length. The results show the impact of partial saturation on leak-off and the fact that single-phase models may underestimate the leak-off.
Probabilistic error bounds for reduced order modeling
Energy Technology Data Exchange (ETDEWEB)
Abdo, M.G.; Wang, C.; Abdel-Khalik, H.S., E-mail: abdo@purdue.edu, E-mail: wang1730@purdue.edu, E-mail: abdelkhalik@purdue.edu [Purdue Univ., School of Nuclear Engineering, West Lafayette, IN (United States)
2015-07-01
Reduced order modeling has proven to be an effective tool when repeated execution of reactor analysis codes is required. ROM operates on the assumption that the intrinsic dimensionality of the associated reactor physics models is sufficiently small when compared to the nominal dimensionality of the input and output data streams. By employing a truncation technique with roots in linear algebra matrix decomposition theory, ROM effectively discards all components of the input and output data that have negligible impact on reactor attributes of interest. This manuscript introduces a mathematical approach to quantify the errors resulting from the discarded ROM components. As supported by numerical experiments, the introduced analysis proves that the contribution of the discarded components could be upper-bounded with an overwhelmingly high probability. The reverse of this statement implies that the ROM algorithm can self-adapt to determine the level of the reduction needed such that the maximum resulting reduction error is below a given tolerance limit that is set by the user. (author)
The chemical energy unit partial oxidation reactor operation simulation modeling
Mrakin, A. N.; Selivanov, A. A.; Batrakov, P. A.; Sotnikov, D. G.
2018-01-01
The chemical energy unit scheme for synthesis gas, electric and heat energy production which is possible to be used both for the chemical industry on-site facilities and under field conditions is represented in the paper. The partial oxidation reactor gasification process mathematical model is described and reaction products composition and temperature determining algorithm flow diagram is shown. The developed software product verification showed good convergence of the experimental values and calculations according to the other programmes: the temperature determining relative discrepancy amounted from 4 to 5 %, while the absolute composition discrepancy ranged from 1 to 3%. The synthesis gas composition was found out practically not to depend on the supplied into the partial oxidation reactor (POR) water vapour enthalpy and compressor air pressure increase ratio. Moreover, air consumption coefficient α increase from 0.7 to 0.9 was found out to decrease synthesis gas target components (carbon and hydrogen oxides) specific yield by nearly 2 times and synthesis gas target components required ratio was revealed to be seen in the water vapour specific consumption area (from 5 to 6 kg/kg of fuel).
Generalized Reduced Order Modeling of Aeroservoelastic Systems
Gariffo, James Michael
Transonic aeroelastic and aeroservoelastic (ASE) modeling presents a significant technical and computational challenge. Flow fields with a mixture of subsonic and supersonic flow, as well as moving shock waves, can only be captured through high-fidelity CFD analysis. With modern computing power, it is realtively straightforward to determine the flutter boundary for a single structural configuration at a single flight condition, but problems of larger scope remain quite costly. Some such problems include characterizing a vehicle's flutter boundary over its full flight envelope, optimizing its structural weight subject to aeroelastic constraints, and designing control laws for flutter suppression. For all of these applications, reduced-order models (ROMs) offer substantial computational savings. ROM techniques in general have existed for decades, and the methodology presented in this dissertation builds on successful previous techniques to create a powerful new scheme for modeling aeroelastic systems, and predicting and interpolating their transonic flutter boundaries. In this method, linear ASE state-space models are constructed from modal structural and actuator models coupled to state-space models of the linearized aerodynamic forces through feedback loops. Flutter predictions can be made from these models through simple eigenvalue analysis of their state-transition matrices for an appropriate set of dynamic pressures. Moreover, this analysis returns the frequency and damping trend of every aeroelastic branch. In contrast, determining the critical dynamic pressure by direct time-marching CFD requires a separate run for every dynamic pressure being analyzed simply to obtain the trend for the critical branch. The present ROM methodology also includes a new model interpolation technique that greatly enhances the benefits of these ROMs. This enables predictions of the dynamic behavior of the system for flight conditions where CFD analysis has not been explicitly
Modular Implementation of Programming Languages and a Partial-Order Approach to Infinitary Rewriting
DEFF Research Database (Denmark)
Bahr, Patrick
2012-01-01
In this dissertation we investigate two independent areas of research. In the first part, we develop techniques for implementing programming languages in a modular fashion. Within this problem domain, we focus on operations on typed abstract syntax trees with the goal of developing a framework...... that facilitates the definition, manipulation and composition of such operations. The result of our work is a comprehensive combinator library that provides these facilities. What sets our approach apart is the use of recursion schemes derived from tree automata in order to implement operations on abstract syntax...... trees. The second part is concerned with infinitary rewriting, a field that studies transfinite rewrite sequences. We extend the established theory of infinitary rewriting in two ways: (1) a novel approach to convergence in infinitary rewriting that replaces convergence in a metric space with the limit...
Directory of Open Access Journals (Sweden)
Fukang Yin
2013-01-01
Full Text Available A numerical method is presented to obtain the approximate solutions of the fractional partial differential equations (FPDEs. The basic idea of this method is to achieve the approximate solutions in a generalized expansion form of two-dimensional fractional-order Legendre functions (2D-FLFs. The operational matrices of integration and derivative for 2D-FLFs are first derived. Then, by these matrices, a system of algebraic equations is obtained from FPDEs. Hence, by solving this system, the unknown 2D-FLFs coefficients can be computed. Three examples are discussed to demonstrate the validity and applicability of the proposed method.
Cortes, Adriano Mauricio; Vignal, Philippe; Sarmiento, Adel; Garcí a, Daniel O.; Collier, Nathan; Dalcin, Lisandro; Calo, Victor M.
2014-01-01
In this paper we present PetIGA, a high-performance implementation of Isogeometric Analysis built on top of PETSc. We show its use in solving nonlinear and time-dependent problems, such as phase-field models, by taking advantage of the high-continuity of the basis functions granted by the isogeometric framework. In this work, we focus on the Cahn-Hilliard equation and the phase-field crystal equation.
Structure of C60: Partial orientational order in the room-temperature modification of C60
International Nuclear Information System (INIS)
Buergi, H.B.; Restori, R.; Schwarzenbach, D.
1993-01-01
Using published synchrotron X-ray data, the room-temperature scattering density distribution of pure C 60 has been parametrized in terms of a combination of eight oriented symmetry-related images of the molecule, and of a freely spinning molecule. Corresponding populations are 61 and 39%. The oriented part of the model is obtained, in good approximation, by imposing m anti 3m symmetry on the energetically more favourable major orientation in the low-temperature structure of C 60 . The model was refined using angle restraints to impose the icosahedral molecular symmetry and displacement-factor restraints to restrict thermal movements to rigid-body translations and librations. Translational displacement factors are in the range 0.017-0.023 A 2 . The orientational probability density distribution obtained from the model shows maxima for C 60 orientations possessing anti 3m crystallographic site symmetry. It is also relatively large for the C 60 orientations with cubic site symmetry m anti 3. The smallest energy barrier for reorientation between different anti 3m orientations via an m anti 3 orientation appears to be less than 2 kJ mol -1 . On average, 75% of the intermolecular contacts of the oriented molecules are longer than those observed in the low-temperature structure, the other 25% are less favourable. The second orientation of C 60 found in the low-temperature structure could not be identified at room temperature. (orig.)
Partial differential equations in action from modelling to theory
Salsa, Sandro
2016-01-01
The book is intended as an advanced undergraduate or first-year graduate course for students from various disciplines, including applied mathematics, physics and engineering. It has evolved from courses offered on partial differential equations (PDEs) over the last several years at the Politecnico di Milano. These courses had a twofold purpose: on the one hand, to teach students to appreciate the interplay between theory and modeling in problems arising in the applied sciences, and on the other to provide them with a solid theoretical background in numerical methods, such as finite elements. Accordingly, this textbook is divided into two parts. The first part, chapters 2 to 5, is more elementary in nature and focuses on developing and studying basic problems from the macro-areas of diffusion, propagation and transport, waves and vibrations. In turn the second part, chapters 6 to 11, concentrates on the development of Hilbert spaces methods for the variational formulation and the analysis of (mainly) linear bo...
Risk and Management Control: A Partial Least Square Modelling Approach
DEFF Research Database (Denmark)
Nielsen, Steen; Pontoppidan, Iens Christian
Risk and economic theory goes many year back (e.g. to Keynes & Knight 1921) and risk/uncertainty belong to one of the explanations for the existence of the firm (Coarse, 1937). The present financial crisis going on in the past years have re-accentuated risk and the need of coherence...... and interrelations between risk and areas within management accounting. The idea is that management accounting should be able to conduct a valid feed forward but also predictions for decision making including risk. This study reports the test of a theoretical model using partial least squares (PLS) on survey data...... and a external attitude dimension. The results have important implications for both management control research and for the management control systems design for the way accountants consider the element of risk in their different tasks, both operational and strategic. Specifically, it seems that different risk...
Optimal difference-based estimation for partially linear models
Zhou, Yuejin; Cheng, Yebin; Dai, Wenlin; Tong, Tiejun
2017-01-01
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
Partial differential equations in action from modelling to theory
Salsa, Sandro
2015-01-01
The book is intended as an advanced undergraduate or first-year graduate course for students from various disciplines, including applied mathematics, physics and engineering. It has evolved from courses offered on partial differential equations (PDEs) over the last several years at the Politecnico di Milano. These courses had a twofold purpose: on the one hand, to teach students to appreciate the interplay between theory and modeling in problems arising in the applied sciences, and on the other to provide them with a solid theoretical background in numerical methods, such as finite elements. Accordingly, this textbook is divided into two parts. The first part, chapters 2 to 5, is more elementary in nature and focuses on developing and studying basic problems from the macro-areas of diffusion, propagation and transport, waves and vibrations. In turn the second part, chapters 6 to 11, concentrates on the development of Hilbert spaces methods for the variational formulation and the analysis of (mainly) linear bo...
Optimal difference-based estimation for partially linear models
Zhou, Yuejin
2017-12-16
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
PERMINTAAN BERAS DI PROVINSI JAMBI (Penerapan Partial Adjustment Model
Directory of Open Access Journals (Sweden)
Wasi Riyanto
2013-07-01
Full Text Available The purpose of this study is to determine the effect of price of rice, flour prices, population, income of population and demand of rice for a year earlier on rice demand, demand rice elasticity and rice demand prediction in Jambi Province. This study uses secondary data, including time series data for 22 years from 1988 until 2009. The study used some variables, consist of rice demand (Qdt, the price of rice (Hb, the price of wheat flour (Hg, population (Jp, the income of the population (PDRB and demand for rice the previous year (Qdt-1. The make of this study are multiple regression and dynamic analysis a Partial Adjustment Model, where the demand for rice is the dependent variable and the price of rice, flour prices, population, income population and demand of rice last year was the independent variable. Partial Adjustment Model analysis results showed that the effect of changes in prices of rice and flour are not significant to changes in demand for rice. The population and demand of rice the previous year has positive and significant impact on demand for rice, while revenues have negative and significant population of rice demand. Variable price of rice, earning population and the price of flour is inelastic the demand of rice, because rice is not a normal good but as a necessity so that there is no substitution of goods (replacement of rice with other commodities in Jambi Province. Based on the analysis, it is recommended to the government to be able to control the rate of population increase given the variable number of people as one of the factors that affect demand for rice.It is expected that the government also began to socialize in a lifestyle of non-rice food consumption to control the increasing amount of demand for rice. Last suggestion, the government developed a diversification of staple foods other than rice.
Reduced order model of draft tube flow
International Nuclear Information System (INIS)
Rudolf, P; Štefan, D
2014-01-01
Swirling flow with compact coherent structures is very good candidate for proper orthogonal decomposition (POD), i.e. for decomposition into eigenmodes, which are the cornerstones of the flow field. Present paper focuses on POD of steady flows, which correspond to different operating points of Francis turbine draft tube flow. Set of eigenmodes is built using a limited number of snapshots from computational simulations. Resulting reduced order model (ROM) describes whole operating range of the draft tube. ROM enables to interpolate in between the operating points exploiting the knowledge about significance of particular eigenmodes and thus reconstruct the velocity field in any operating point within the given range. Practical example, which employs axisymmetric simulations of the draft tube flow, illustrates accuracy of ROM in regions without vortex breakdown together with need for higher resolution of the snapshot database close to location of sudden flow changes (e.g. vortex breakdown). ROM based on POD interpolation is very suitable tool for insight into flow physics of the draft tube flows (especially energy transfers in between different operating points), for supply of data for subsequent stability analysis or as an initialization database for advanced flow simulations
Mathematical analysis of partial differential equations modeling electrostatic MEMS
Esposito, Pierpaolo; Guo, Yujin
2010-01-01
Micro- and nanoelectromechanical systems (MEMS and NEMS), which combine electronics with miniature-size mechanical devices, are essential components of modern technology. It is the mathematical model describing "electrostatically actuated" MEMS that is addressed in this monograph. Even the simplified models that the authors deal with still lead to very interesting second- and fourth-order nonlinear elliptic equations (in the stationary case) and to nonlinear parabolic equations (in the dynamic case). While nonlinear eigenvalue problems-where the stationary MEMS models fit-are a well-developed
Directory of Open Access Journals (Sweden)
Ren-Qian Zhang
2016-01-01
Full Text Available Many inventory models with partial backordering assume that the backordered demand must be filled instantly after stockout restoration. In practice, however, the backordered customers may successively revisit the store because of the purchase delay behavior, producing a limited backorder demand rate and resulting in an extra inventory holding cost. Hence, in this paper we formulate the inventory model with partial backordering considering the purchase delay of the backordered customers and assuming that the backorder demand rate is proportional to the remaining backordered demand. Particularly, we model the problem by introducing a new inventory cost component of holding the backordered items, which has not been considered in the existing models. We propose an algorithm with a two-layer structure based on Lipschitz Optimization (LO to minimize the total inventory cost. Numerical experiments show that the proposed algorithm outperforms two benchmarks in both optimality and efficiency. We also observe that the earlier the backordered customer revisits the store, the smaller the inventory cost and the fill rate are, but the longer the order cycle is. In addition, if the backordered customers revisit the store without too much delay, the basic EOQ with partial backordering approximates our model very well.
Consistent Partial Least Squares Path Modeling via Regularization
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Sunho Jung
2018-02-01
Full Text Available Partial least squares (PLS path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc, designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.
Modeling of termokinetic oscillations at partial oxidation of methane
Arutyunov, A. V.; Belyaev, A. A.; Inovenkov, I. N.; Nefedov, V. V.
2017-12-01
Partial oxidation of natural gas at moderate temperatures below 1500 K has significant interest for a number of industrial applications. But such processes can proceed at different unstable regimes including oscillating modes. Nonlinear phenomena at partial oxidation of methane were observed at different conditions. The investigation of the complex nonlinear system of equations that describes this process is a real method to insure its stability at industrial conditions and, at the same time, is an effective tool for its further enhancement. Numerical analysis of methane oxidation kinetics in the continuous stirred-tank reactor, with the use of detailed kinetic model has shown the possibility of the appearance of oscillating modes in the appropriate range of reaction parameters that characterize the composition, pressure, reagents flow, thermophysical features of the system, and geometry of the reactor. The appearance of oscillating modes is connected both with the reaction kinetics, heat release and sink and reagents introduction and removing. At that, oscillations appear only at a limited range of parameters, but can be accompanied by significant change in the yield of products. We have determined the range of initial temperature and pressure at which oscillations can be observed, if all other parameters remained fixed. The boundaries of existence of oscillations on the phase plane were calculated. It was shown that depending on the position inside the oscillation region the oscillations have different frequency and amplitude. It was reviled the role of heat exchange with the environment: at the absence of heat exchange the oscillating modes are impossible. In the vicinity of the boundary of phase range, where oscillations exist, significant change of concentration of some products were observed, for example, that of CO2, which in this case one of the principal products is. At that, insignificant increase in pressure not only change the character of CO2 behaving
International Nuclear Information System (INIS)
Basnarkov, Lasko; Urumov, Viktor
2009-01-01
We consider an analytically solvable version of the Winfree model of synchronization of phase oscillators (proposed by Ariaratnam and Strogatz 2001 Phys. Rev. Lett. 86 4278). It is obtained that the transition from incoherence to a partial death state is characterized by third-order or higher phase transitions according to the Ehrenfest classification. The order of the transition depends on the shape of the distribution function for natural frequencies of oscillators in the vicinity of their lowest frequency. The corresponding critical exponents are found analytically and verified with numerical simulations of equations of motion. We also consider the generalized Winfree model with the interaction strength proportional to a power of the Kuramoto order parameter and find the domain where the critical exponent remains unchanged by this modification
Groundwater flow modelling of an abandoned partially open repository
Energy Technology Data Exchange (ETDEWEB)
Bockgaard, Niclas (Golder Associates AB (Sweden))
2010-12-15
As a part of the license application, according to the nuclear activities act, for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different hydraulic conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. The modelling study presented here serves as an input for analyses of so-called future human actions that may affect the repository. The objective of the work was to investigate the hydraulic influence of an abandoned partially open repository. The intention was to illustrate a pessimistic scenario of the effect of open tunnels in comparison to the reference closure of the repository. The effects of open tunnels were studied for two situations with different boundary conditions: A 'temperate' case with present-day boundary conditions and a generic future 'glacial' case with an ice sheet covering the repository. The results were summarized in the form of analyses of flow in and out from open tunnels, the effect on hydraulic head and flow in the surrounding rock volume, and transport performance measures of flow paths from the repository to surface
Groundwater flow modelling of an abandoned partially open repository
International Nuclear Information System (INIS)
Bockgaard, Niclas
2010-12-01
As a part of the license application, according to the nuclear activities act, for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different hydraulic conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. The modelling study presented here serves as an input for analyses of so-called future human actions that may affect the repository. The objective of the work was to investigate the hydraulic influence of an abandoned partially open repository. The intention was to illustrate a pessimistic scenario of the effect of open tunnels in comparison to the reference closure of the repository. The effects of open tunnels were studied for two situations with different boundary conditions: A 'temperate' case with present-day boundary conditions and a generic future 'glacial' case with an ice sheet covering the repository. The results were summarized in the form of analyses of flow in and out from open tunnels, the effect on hydraulic head and flow in the surrounding rock volume, and transport performance measures of flow paths from the repository to surface
Permintaan Beras di Provinsi Jambi (Penerapan Partial Adjustment Model
Directory of Open Access Journals (Sweden)
Wasi Riyanto
2013-07-01
Full Text Available The purpose of this study is to determine the effect of price of rice, flour prices, population, income of population and demand of rice for a year earlier on rice demand, demand rice elasticity and rice demand prediction in Jambi Province. This study uses secondary data, including time series data for 22 years from 1988 until 2009. The study used some variables, consist of rice demand (Qdt, the price of rice (Hb, the price of wheat flour (Hg, population (Jp, the income of the population (PDRB and demand for rice the previous year (Qdt-1. The make of this study are multiple regression and dynamic analysis a Partial Adjustment Model, where the demand for rice is the dependent variable and the price of rice, flour prices, population, income population and demand of rice last year was the independent variable. Partial Adjustment Model analysis results showed that the effect of changes in prices of rice and flour are not significant to changes in demand for rice. The population and demand of rice the previous year has positive and significant impact on demand for rice, while revenues have negative and significant population of rice demand. Variable price of rice, earning population and the price of flour is inelastic the demand of rice, because rice is not a normal good but as a necessity so that there is no substitution of goods (replacement of rice with other commodities in Jambi Province. Based on the analysis, it is recommended to the government to be able to control the rate of population increase given the variable number of people as one of the factors that affect demand for rice.It is expected that the government also began to socialize in a lifestyle of non-rice food consumption to control the increasing amount of demand for rice. Last suggestion, the government developed a diversification of staple foods other than rice. Keywords: Demand, Rice, Income Population
Microstrip natural wave spectrum mathematical model using partial inversion method
International Nuclear Information System (INIS)
Pogarsky, S.A.; Litvinenko, L.N.; Prosvirnin, S.L.
1995-01-01
It is generally agreed that both microstrip lines itself and different discontinuities based on microstrips are the most difficult problem for accurate electrodynamic analysis. Over the last years much has been published about principles and accurate (or full wave) methods of microstrip lines investigations. The growing interest for this problem may be explained by the microstrip application in the millimeter-wave range for purpose of realizing interconnects and a variety of passive components. At these higher operating rating frequencies accurate component modeling becomes more critical. A creation, examination and experimental verification of the accurate method for planar electrodynamical structures natural wave spectrum investigations are the objects of this manuscript. The moment method with partial inversion operator method using may be considered as a basical way for solving this problem. This method is outlook for accurate analysis of different planar discontinuities in microstrip: such as step discontinuities, microstrip turns, Y- and X-junctions and etc., substrate space steps dielectric constants and other anisotropy types
Directory of Open Access Journals (Sweden)
M. Morzfeld
2012-06-01
Full Text Available Implicit particle filtering is a sequential Monte Carlo method for data assimilation, designed to keep the number of particles manageable by focussing attention on regions of large probability. These regions are found by minimizing, for each particle, a scalar function F of the state variables. Some previous implementations of the implicit filter rely on finding the Hessians of these functions. The calculation of the Hessians can be cumbersome if the state dimension is large or if the underlying physics are such that derivatives of F are difficult to calculate, as happens in many geophysical applications, in particular in models with partial noise, i.e. with a singular state covariance matrix. Examples of models with partial noise include models where uncertain dynamic equations are supplemented by conservation laws with zero uncertainty, or with higher order (in time stochastic partial differential equations (PDE or with PDEs driven by spatially smooth noise processes. We make the implicit particle filter applicable to such situations by combining gradient descent minimization with random maps and show that the filter is efficient, accurate and reliable because it operates in a subspace of the state space. As an example, we consider a system of nonlinear stochastic PDEs that is of importance in geomagnetic data assimilation.
Carlsen, Lars; Bruggemann, Rainer; Kenessov, Bulat
2018-01-01
Urban air pollution with benzene, toluene, ethyl benzene and xylenes (BTEX) is a common phenomenon in major cities where the pollution mainly originates from traffic as well as from residential heating. An attempt to rank cities according to their BTEX air pollution is not necessarily straight forward as we are faced with several individual pollutants simultaneously. A typical procedure is based on aggregation of data for the single compounds, a process that not only hides important information but is also subject to compensation effects. The present study applies a series of partial ordering tools to circumvent the aggregation. Based on partial ordering, most important indicators are disclosed, and an average ranking of the cities included in the study is derived. Since air pollution measurements are often subject to significant uncertainties, special attention has been given to the possible effect of uncertainty and/or data noise. Finally, the effect of introducing weight regimes is studied. In a concluding section the gross national income per person (GNI) is brought into play, demonstrating a positive correlation between BTEX air pollution and GNI. The results are discussed in terms of the ability/willingness to combat air pollution in the cities studied. The present study focuses on Almaty, the largest city in Kazakhstan and compares the data from Almaty to another 19 major cities around the world. It is found that the benzene for Almaty appears peculiar high. Overall Almaty appears ranked as the 8th most BTEX polluted city among the 20 cities included in the study. Copyright © 2017 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Gershgorin, B.; Majda, A.J.
2011-01-01
A statistically exactly solvable model for passive tracers is introduced as a test model for the authors' Nonlinear Extended Kalman Filter (NEKF) as well as other filtering algorithms. The model involves a Gaussian velocity field and a passive tracer governed by the advection-diffusion equation with an imposed mean gradient. The model has direct relevance to engineering problems such as the spread of pollutants in the air or contaminants in the water as well as climate change problems concerning the transport of greenhouse gases such as carbon dioxide with strongly intermittent probability distributions consistent with the actual observations of the atmosphere. One of the attractive properties of the model is the existence of the exact statistical solution. In particular, this unique feature of the model provides an opportunity to design and test fast and efficient algorithms for real-time data assimilation based on rigorous mathematical theory for a turbulence model problem with many active spatiotemporal scales. Here, we extensively study the performance of the NEKF which uses the exact first and second order nonlinear statistics without any approximations due to linearization. The role of partial and sparse observations, the frequency of observations and the observation noise strength in recovering the true signal, its spectrum, and fat tail probability distribution are the central issues discussed here. The results of our study provide useful guidelines for filtering realistic turbulent systems with passive tracers through partial observations.
Study and optimization of the partial discharges in capacitor model ...
African Journals Online (AJOL)
The initial potential as well as the temperature are known to influence the partial discharge ... The development of electrostatic industry has ... the liquid impregnation. One of the ..... the Surface of Corona charged Uniforms layers of HIPS.
Reduction of static field equation of Faddeev model to first order PDE
International Nuclear Information System (INIS)
Hirayama, Minoru; Shi Changguang
2007-01-01
A method to solve the static field equation of the Faddeev model is presented. For a special combination of the concerned field, we adopt a form which is compatible with the field equation and involves two arbitrary complex functions. As a result, the static field equation is reduced to a set of first order partial differential equations
Reactor modeling and process analysis for partial oxidation of natural gas
Albrecht, B.A.
2004-01-01
This thesis analyses a novel process of partial oxidation of natural gas and develops a numerical tool for the partial oxidation reactor modeling. The proposed process generates syngas in an integrated plant of a partial oxidation reactor, a syngas turbine and an air separation unit. This is called
Ordering dynamics of microscopic models with nonconserved order parameter of continuous symmetry
DEFF Research Database (Denmark)
Zhang, Z.; Mouritsen, Ole G.; Zuckermann, Martin J.
1993-01-01
crystals. For both models, which have a nonconserved order parameter, it is found that the linear scale, R(t), of the evolving order, following quenches to below the transition temperature, grows at late times in an effectively algebraic fashion, R(t)∼tn, with exponent values which are strongly temperature......Numerical Monte Carlo temperature-quenching experiments have been performed on two three-dimensional classical lattice models with continuous ordering symmetry: the Lebwohl-Lasher model [Phys. Rev. A 6, 426 (1972)] and the ferromagnetic isotropic Heisenberg model. Both models describe a transition...... from a disordered phase to an orientationally ordered phase of continuous symmetry. The Lebwohl-Lasher model accounts for the orientational ordering properties of the nematic-isotropic transition in liquid crystals and the Heisenberg model for the ferromagnetic-paramagnetic transition in magnetic...
Davis, Brynmor; Kim, Edward; Piepmeier, Jeffrey; Hildebrand, Peter H. (Technical Monitor)
2001-01-01
Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.
Model selection criteria : how to evaluate order restrictions
Kuiper, R.M.
2012-01-01
Researchers often have ideas about the ordering of model parameters. They frequently have one or more theories about the ordering of the group means, in analysis of variance (ANOVA) models, or about the ordering of coefficients corresponding to the predictors, in regression models.A researcher might
Nam, Sungsik
2011-08-01
Spread spectrum receivers with generalized selection combining (GSC) RAKE reception were proposed and have been studied as alternatives to the classical two fundamental schemes: maximal ratio combining and selection combining because the number of diversity paths increases with the transmission bandwidth. Previous work on performance analyses of GSC RAKE receivers based on the signal to noise ratio focused on the development of methodologies to derive exact closed-form expressions for various performance measures. However, some open problems related to the performance evaluation of GSC RAKE receivers still remain to be solved such as the exact performance analysis of the capture probability and an exact assessment of the impact of self-interference on GSC RAKE receivers. The major difficulty in these problems is to derive some joint statistics of ordered exponential variates. With this motivation in mind, we capitalize in this paper on some new order statistics results to derive exact closed-form expressions for the capture probability and outage probability of GSC RAKE receivers subject to self-interference over independent and identically distributed Rayleigh fading channels, and compare it to that of partial RAKE receivers. © 2011 IEEE.
Bayesian inference for partially identified models exploring the limits of limited data
Gustafson, Paul
2015-01-01
Introduction Identification What Is against Us? What Is for Us? Some Simple Examples of Partially Identified ModelsThe Road Ahead The Structure of Inference in Partially Identified Models Bayesian Inference The Structure of Posterior Distributions in PIMs Computational Strategies Strength of Bayesian Updating, Revisited Posterior MomentsCredible Intervals Evaluating the Worth of Inference Partial Identification versus Model Misspecification The Siren Call of Identification Comp
Model Order Reduction for Non Linear Mechanics
Pinillo, Rubén
2017-01-01
Context: Automotive industry is moving towards a new generation of cars. Main idea: Cars are furnished with radars, cameras, sensors, etc… providing useful information about the environment surrounding the car. Goals: Provide an efficient model for the radar input/output. Reducing computational costs by means of big data techniques.
Reduced Order Modeling Methods for Turbomachinery Design
2009-03-01
and Ma- terials Conference, May 2006. [45] A. Gelman , J. B. Carlin, H. S. Stern, and D. B. Rubin, Bayesian Data Analysis. New York, NY: Chapman I& Hall...Macian- Juan , and R. Chawla, “A statistical methodology for quantif ca- tion of uncertainty in best estimate code physical models,” Annals of Nuclear En
Life time test of a partial model of HTGR helium-helium heat exchanger
International Nuclear Information System (INIS)
Kitagawa, Masaki; Hattori, Hiroshi; Ohtomo, Akira; Teramae, Tetsuo; Hamanaka, Junichi; Itoh, Mitsuyoshi; Urabe, Shigemi
1984-01-01
Authors had proposed a design guide for the HTGR components and applied it to the design and construction of the 1.5 Mwt helium heat exchanger test loop for the nuclear steel making under the financial support of the Japanese Ministry of International Trade and Industry. In order to assure that the design method covers all the conceivable failure mode and has enough safety margin, a series of life time tests of partial model may be needed. For this project, three types of model tests were performed. A life time test of a partial model of the center manifold pipe and eight heat exchanger tubes were described in this report. A damage criterion with a set of material constants and a simplified method for stress-strain analysis for stub tube under three dimensional load were newly developed and used to predict the lives of each tube. The predicted lives were compared with the experimental lives and good agreement was found between the two. The life time test model was evaluated according to the proposed design guide and it was found that the guide has a safety factor of approximately 200 in life for this particular model. (author)
Partially collisional model of the Titan hydrogen torus
International Nuclear Information System (INIS)
Hilton, D.A.
1987-01-01
A numerical model was developed for atomic hydrogen densities in the Titan hydrogen torus. The effects of occasional collisions were included in order to accurately simulate physical conditions inferred from the Voyager 1 and 2 Ultraviolet Spectrometer (UVS) results of Broadfoot et al. (1981) and Sandel et al. (1982). The model employed Lagrangian perturbation of orbital elements of hydrogen atoms launched from Titan and Monte Carlo simulation of collisions and loss mechanisms. The torus is found to be azimuthally symmetric with the density sharply peaked at Titan's orbit, and decreasing rapidly in the outward and perpendicular directions and more gradually inward from 17 to 5 R/sub s/. The energetic hydrogen atoms from Saturn's upper atmosphere, first predicted by Shemansky and Smith (1982), were also investigated. Collisions of these Saturnian atoms with the torus population do not contribute to the torus density, and will lead to a net loss of torus atoms if their launch speeds from Saturn extend above 40 km/sec. The Saturnian atoms produce a corona which was modeled using the theory of Chamberlain (1963)
Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B
2017-05-01
Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Model Order Reduction for Electronic Circuits:
DEFF Research Database (Denmark)
Hjorth, Poul G.; Shontz, Suzanne
Electronic circuits are ubiquitous; they are used in numerous industries including: the semiconductor, communication, robotics, auto, and music industries (among many others). As products become more and more complicated, their electronic circuits also grow in size and complexity. This increased...... in the semiconductor industry. Circuit simulation proceeds by using Maxwell’s equations to create a mathematical model of the circuit. The boundary element method is then used to discretize the equations, and the variational form of the equations are then solved on the graph network....
An Introduction to the Partial Credit Model for Developing Nursing Assessments.
Fox, Christine
1999-01-01
Demonstrates how the partial credit model, a variation of the Rasch Measurement Model, can be used to develop performance-based assessments for nursing education. Applies the model using the Practical Knowledge Inventory for Nurses. (SK)
Study and optimization of the partial discharges in capacitor model ...
African Journals Online (AJOL)
that the main cause of failure of these devices is the appearance of partial discharges initiated on edges of armatures. These devices can quickly slam if discharges occur continuously during the liquid impregnation. One of the criteria for selecting impregnating liquids is the behavior of gas bubbles when discharges occur.
Partial delegation in a model of currency crisis
Boinet, V
2002-01-01
Stressing the inßuence of expected devaluation on currency crises, this paper shows that, in a Þxed exchange-rate system with an escape clause, partial delegation of exchange-rate policy to an inßation-averse central banker reduces the probability of crisis.
Lerche, Dorte; Brüggemann, Rainer; Sørensen, Peter; Carlsen, Lars; Nielsen, Ole John
2002-01-01
An alternative to the often cumbersome and time-consuming risk assessments of chemical substances could be more reliable and advanced priority setting methods. An elaboration of the simple scoring methods is provided by Hasse Diagram Technique (HDT) and/or Multi-Criteria Analysis (MCA). The present study provides an in depth evaluation of HDT relative to three MCA techniques. The new and main methodological step in the comparison is the use of probability concepts based on mathematical tools such as linear extensions of partially ordered sets and Monte Carlo simulations. A data set consisting of 12 High Production Volume Chemicals (HPVCs) is used for illustration. It is a paradigm in this investigation to claim that the need of external input (often subjective weightings of criteria) should be minimized and that the transparency should be maximized in any multicriteria prioritisation. The study illustrates that the Hasse diagram technique (HDT) needs least external input, is most transparent and is least subjective. However, HDT has some weaknesses if there are criteria which exclude each other. Then weighting is needed. Multi-Criteria Analysis (i.e. Utility Function approach, PROMETHEE and concordance analysis) can deal with such mutual exclusions because their formalisms to quantify preferences allow participation e.g. weighting of criteria. Consequently MCA include more subjectivity and loose transparency. The recommendation which arises from this study is that the first step in decision making is to run HDT and as the second step possibly is to run one of the MCA algorithms.
Galindo-Israel, V.; Imbriale, W.; Shogen, K.; Mittra, R.
1990-01-01
In obtaining solutions to the first-order nonlinear partial differential equations (PDEs) for synthesizing offset dual-shaped reflectors, it is found that previously observed computational problems can be avoided if the integration of the PDEs is started from an inner projected perimeter and integrated outward rather than starting from an outer projected perimeter and integrating inward. This procedure, however, introduces a new parameter, the main reflector inner perimeter radius p(o), when given a subreflector inner angle 0(o). Furthermore, a desired outer projected perimeter (e.g., a circle) is no longer guaranteed. Stability of the integration is maintained if some of the initial parameters are determined first from an approximate solution to the PDEs. A one-, two-, or three-parameter optimization algorithm can then be used to obtain a best set of parameters yielding a close fit to the desired projected outer rim. Good low cross-polarization mapping functions are also obtained. These methods are illustrated by synthesis of a high-gain offset-shaped Cassegrainian antenna and a low-noise offset-shaped Gregorian antenna.
Skouri, K.; Konstantaras, I.
2009-01-01
An order level inventory model for seasonable/fashionable products subject to a period of increasing demand followed by a period of level demand and then by a period of decreasing demand rate (three branches ramp type demand rate) is considered. The unsatisfied demand is partially backlogged with a time dependent backlogging rate. In addition, the product deteriorates with a time dependent, namely, Weibull, deterioration rate. The model is studied under the following different replenishment p...
Partial-factor Energy Efficiency Model of Indonesia
Nugroho Fathul; Syaifudin Noor
2018-01-01
This study employs the partial-factor energy efficiency to reveal the relationships between energy efficiency and the consumption of both, the renewable energy and non-renewable energy in Indonesia. The findings confirm that consumption of non-renewable energy will increase the inefficiency in energy consumption. On the other side, the use of renewable energy will increase the energy efficiency in Indonesia. As the result, the Government of Indonesia may address this issue by providing more s...
Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.
Muraki, Eiji
1999-01-01
Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…
An Extension of the Partial Credit Model with an Application to the Measurement of Change.
Fischer, Gerhard H.; Ponocny, Ivo
1994-01-01
An extension to the partial credit model, the linear partial credit model, is considered under the assumption of a certain linear decomposition of the item x category parameters into basic parameters. A conditional maximum likelihood algorithm for estimating basic parameters is presented and illustrated with simulation and an empirical study. (SLD)
A simple one-step chemistry model for partially premixed hydrocarbon combustion
Energy Technology Data Exchange (ETDEWEB)
Fernandez-Tarrazo, Eduardo [Instituto Nacional de Tecnica Aeroespacial, Madrid (Spain); Sanchez, Antonio L. [Area de Mecanica de Fluidos, Universidad Carlos III de Madrid, Leganes 28911 (Spain); Linan, Amable [ETSI Aeronauticos, Pl. Cardenal Cisneros 3, Madrid 28040 (Spain); Williams, Forman A. [Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093-0411 (United States)
2006-10-15
This work explores the applicability of one-step irreversible Arrhenius kinetics with unity reaction order to the numerical description of partially premixed hydrocarbon combustion. Computations of planar premixed flames are used in the selection of the three model parameters: the heat of reaction q, the activation temperature T{sub a}, and the preexponential factor B. It is seen that changes in q with equivalence ratio f need to be introduced in fuel-rich combustion to describe the effect of partial fuel oxidation on the amount of heat released, leading to a universal linear variation q(f) for f>1 for all hydrocarbons. The model also employs a variable activation temperature T{sub a}(f) to mimic changes in the underlying chemistry in rich and very lean flames. The resulting chemistry description is able to reproduce propagation velocities of diluted and undiluted flames accurately over the whole flammability limit. Furthermore, computations of methane-air counterflow diffusion flames are used to test the proposed chemistry under nonpremixed conditions. The model not only predicts the critical strain rate at extinction accurately but also gives near-extinction flames with oxygen leakage, thereby overcoming known predictive limitations of one-step Arrhenius kinetics. (author)
A simple method for identifying parameter correlations in partially observed linear dynamic models.
Li, Pu; Vu, Quoc Dong
2015-12-14
Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a
New second order Mumford-Shah model based on Γ-convergence approximation for image processing
Duan, Jinming; Lu, Wenqi; Pan, Zhenkuan; Bai, Li
2016-05-01
In this paper, a second order variational model named the Mumford-Shah total generalized variation (MSTGV) is proposed for simultaneously image denoising and segmentation, which combines the original Γ-convergence approximated Mumford-Shah model with the second order total generalized variation (TGV). For image denoising, the proposed MSTGV can eliminate both the staircase artefact associated with the first order total variation and the edge blurring effect associated with the quadratic H1 regularization or the second order bounded Hessian regularization. For image segmentation, the MSTGV can obtain clear and continuous boundaries of objects in the image. To improve computational efficiency, the implementation of the MSTGV does not directly solve its high order nonlinear partial differential equations and instead exploits the efficient split Bregman algorithm. The algorithm benefits from the fast Fourier transform, analytical generalized soft thresholding equation, and Gauss-Seidel iteration. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of the proposed model.
A reduced order model of a quadruped walking system
International Nuclear Information System (INIS)
Sano, Akihito; Furusho, Junji; Naganuma, Nobuyuki
1990-01-01
Trot walking has recently been studied by several groups because of its stability and realizability. In the trot, diagonally opposed legs form pairs. While one pair of legs provides support, the other pair of legs swings forward in preparation for the next step. In this paper, we propose a reduced order model for the trot walking. The reduced order model is derived by using two dominant modes of the closed loop system in which the local feedback at each joint is implemented. It is shown by numerical examples that the obtained reduced order model can well approximate the original higher order model. (author)
Cheng, Guang; Zhou, Lan; Huang, Jianhua Z.
2014-01-01
We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based
International Nuclear Information System (INIS)
Harish, V.S.K.V.; Kumar, Arun
2016-01-01
Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.
Fractional-order in a macroeconomic dynamic model
David, S. A.; Quintino, D. D.; Soliani, J.
2013-10-01
In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.
Higher-order RANS turbulence models for separated flows
National Aeronautics and Space Administration — Higher-order Reynolds-averaged Navier-Stokes (RANS) models are developed to overcome the shortcomings of second-moment RANS models in predicting separated flows....
Data-Driven Model Order Reduction for Bayesian Inverse Problems
Cui, Tiangang; Youssef, Marzouk; Willcox, Karen
2014-01-01
One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce
The second-order decomposition model of nonlinear irregular waves
DEFF Research Database (Denmark)
Yang, Zhi Wen; Bingham, Harry B.; Li, Jin Xuan
2013-01-01
into the first- and the second-order super-harmonic as well as the second-order sub-harmonic components by transferring them into an identical Fourier frequency-space and using a Newton-Raphson iteration method. In order to evaluate the present model, a variety of monochromatic waves and the second...
Application of Stochastic Partial Differential Equations to Reservoir Property Modelling
Potsepaev, R.; Farmer, C.L.
2010-01-01
in parametric space. In order to sample in physical space we introduce a stochastic elliptic PDE with tensor coefficients, where the tensor is related to correlation anisotropy and its variation is physical space.
Spiking and bursting patterns of fractional-order Izhikevich model
Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha
2018-03-01
Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.
Partially linear varying coefficient models stratified by a functional covariate
Maity, Arnab; Huang, Jianhua Z.
2012-01-01
We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric
A Comparison of Graded Response and Rasch Partial Credit Models with Subjective Well-Being.
Baker, John G.; Rounds, James B.; Zevon, Michael A.
2000-01-01
Compared two multiple category item response theory models using a data set of 52 mood terms with 713 undergraduate psychology students. Comparative model fit for the Samejima (F. Samejima, 1966) logistic model for graded responses and the Masters (G. Masters, 1982) partial credit model favored the former model for this data set. (SLD)
Shi, Jinfei; Zhu, Songqing; Chen, Ruwen
2017-12-01
An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.
Tutorial on Online Partial Evaluation
Directory of Open Access Journals (Sweden)
William R. Cook
2011-09-01
Full Text Available This paper is a short tutorial introduction to online partial evaluation. We show how to write a simple online partial evaluator for a simple, pure, first-order, functional programming language. In particular, we show that the partial evaluator can be derived as a variation on a compositionally defined interpreter. We demonstrate the use of the resulting partial evaluator for program optimization in the context of model-driven development.
Investigation of Effectiveness of Order Review and Release Models in Make to Order Supply Chain
Directory of Open Access Journals (Sweden)
Kundu Kaustav
2016-01-01
Full Text Available Nowadays customisation becomes more common due to vast requirement from the customers for which industries are trying to use make-to-order (MTO strategy. Due to high variation in the process, workload control models are extensively used for jobshop companies which usually adapt MTO strategy. Some authors tried to implement workload control models, order review and release systems, in non-repetitive manufacturing companies, where there is a dominant flow in production. Those models are better in shop floor but their performances are never been investigated in high variation situations like MTO supply chain. This paper starts with the introduction of particular issues in MTO companies and a general overview of order review and release systems widely used in the industries. Two order review and release systems, the Limited and Balanced models, particularly suitable for flow shop system are applied to MTO supply chain, where the processing times are difficult to estimate due to high variation. Simulation results show that the Balanced model performs much better than the Limited model if the processing times can be estimated preciously.
A comparison of zero-order, first-order, and Monod biotransformation models
International Nuclear Information System (INIS)
Bekins, B.A.; Warren, E.; Godsy, E.M.
1998-01-01
Under some conditions, a first-order kinetic model is a poor representation of biodegradation in contaminated aquifers. Although it is well known that the assumption of first-order kinetics is valid only when substrate concentration, S, is much less than the half-saturation constant, K S , this assumption is often made without verification of this condition. The authors present a formal error analysis showing that the relative error in the first-order approximation is S/K S and in the zero-order approximation the error is K S /S. They then examine the problems that arise when the first-order approximation is used outside the range for which it is valid. A series of numerical simulations comparing results of first- and zero-order rate approximations to Monod kinetics for a real data set illustrates that if concentrations observed in the field are higher than K S , it may be better to model degradation using a zero-order rate expression. Compared with Monod kinetics, extrapolation of a first-order rate to lower concentrations under-predicts the biotransformation potential, while extrapolation to higher concentrations may grossly over-predict the transformation rate. A summary of solubilities and Monod parameters for aerobic benzene, toluene, and xylene (BTX) degradation shows that the a priori assumption of first-order degradation kinetics at sites contaminated with these compounds is not valid. In particular, out of six published values of K S for toluene, only one is greater than 2 mg/L, indicating that when toluene is present in concentrations greater than about a part per million, the assumption of first-order kinetics may be invalid. Finally, the authors apply an existing analytical solution for steady-state one-dimensional advective transport with Monod degradation kinetics to a field data set
Model order reduction techniques with applications in finite element analysis
Qu, Zu-Qing
2004-01-01
Despite the continued rapid advance in computing speed and memory the increase in the complexity of models used by engineers persists in outpacing them. Even where there is access to the latest hardware, simulations are often extremely computationally intensive and time-consuming when full-blown models are under consideration. The need to reduce the computational cost involved when dealing with high-order/many-degree-of-freedom models can be offset by adroit computation. In this light, model-reduction methods have become a major goal of simulation and modeling research. Model reduction can also ameliorate problems in the correlation of widely used finite-element analyses and test analysis models produced by excessive system complexity. Model Order Reduction Techniques explains and compares such methods focusing mainly on recent work in dynamic condensation techniques: - Compares the effectiveness of static, exact, dynamic, SEREP and iterative-dynamic condensation techniques in producing valid reduced-order mo...
REGIONAL FIRST ORDER PERIODIC AUTOREGRESSIVE MODELS FOR MONTHLY FLOWS
Directory of Open Access Journals (Sweden)
Ceyhun ÖZÇELİK
2008-01-01
Full Text Available First order periodic autoregressive models is of mostly used models in modeling of time dependency of hydrological flow processes. In these models, periodicity of the correlogram is preserved as well as time dependency of processes. However, the parameters of these models, namely, inter-monthly lag-1 autocorrelation coefficients may be often estimated erroneously from short samples, since they are statistics of high order moments. Therefore, to constitute a regional model may be a solution that can produce more reliable and decisive estimates, and derive models and model parameters in any required point of the basin considered. In this study, definitions of homogeneous region for lag-1 autocorrelation coefficients are made; five parametric and non parametric models are proposed to set regional models of lag-1 autocorrelation coefficients. Regional models are applied on 30 stream flow gauging stations in Seyhan and Ceyhan basins, and tested by criteria of relative absolute bias, simple and relative root of mean square errors.
Stochastic partial differential equations a modeling, white noise functional approach
Holden, Helge; Ubøe, Jan; Zhang, Tusheng
1996-01-01
This book is based on research that, to a large extent, started around 1990, when a research project on fluid flow in stochastic reservoirs was initiated by a group including some of us with the support of VISTA, a research coopera tion between the Norwegian Academy of Science and Letters and Den norske stats oljeselskap A.S. (Statoil). The purpose of the project was to use stochastic partial differential equations (SPDEs) to describe the flow of fluid in a medium where some of the parameters, e.g., the permeability, were stochastic or "noisy". We soon realized that the theory of SPDEs at the time was insufficient to handle such equations. Therefore it became our aim to develop a new mathematically rigorous theory that satisfied the following conditions. 1) The theory should be physically meaningful and realistic, and the corre sponding solutions should make sense physically and should be useful in applications. 2) The theory should be general enough to handle many of the interesting SPDEs that occur in r...
Growth modeling of Cryptomeria japonica by partial trunk analysis
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Vinícius Morais Coutinho
2017-06-01
Full Text Available This study aimed to evaluate the growth pattern of Cryptomeria japonica increment (L. F. D. Don. and to describe the probability distribution in stands stablished at the municipality of Rio Negro, Paraná State. Twenty trees were sampled in a 34 years-old stand, with 3 m x 2 m spacing. Wood disks were taken from each tree at 1.3 m above the ground (DBH to perform partial stem analysis. Diameter growth series without bark were used to generate the average cumulative growth curves for DBH (cm, mean annual increment (MAI and current annual increment (CAI. From the increment data, the frequency distribution was evaluated by means of probability density functions (pdfs. The mean annual increment for DBH was 0.78 cm year-1 and the age of intersection of CAI and MAI curves was between the 7th and 8th years. It was found that near 43% of the species increments are concentrated bellow 0.5 cm. The results are useful to define appropriate management strategies for the species for sites similar to the studying regions, defining for example ages of silvicultural intervention, such as thinning.
International Nuclear Information System (INIS)
Vidal-Codina, F.; Nguyen, N.C.; Giles, M.B.; Peraire, J.
2015-01-01
We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method
Nam, Sungsik; Yang, Hongchuan; Alouini, Mohamed-Slim; Kim, Dongin
2014-01-01
framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE
Partially linear varying coefficient models stratified by a functional covariate
Maity, Arnab
2012-10-01
We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.
Hemdan, A.
2016-07-01
Three simple, selective, and accurate spectrophotometric methods have been developed and then validated for the analysis of Benazepril (BENZ) and Amlodipine (AML) in bulk powder and pharmaceutical dosage form. The first method is the absorption factor (AF) for zero order and amplitude factor (P-F) for first order spectrum, where both BENZ and AML can be measured from their resolved zero order spectra at 238 nm or from their first order spectra at 253 nm. The second method is the constant multiplication coupled with constant subtraction (CM-CS) for zero order and successive derivative subtraction-constant multiplication (SDS-CM) for first order spectrum, where both BENZ and AML can be measured from their resolved zero order spectra at 240 nm and 238 nm, respectively, or from their first order spectra at 214 nm and 253 nm for Benazepril and Amlodipine respectively. The third method is the novel constant multiplication coupled with derivative zero crossing (CM-DZC) which is a stability indicating assay method for determination of Benazepril and Amlodipine in presence of the main degradation product of Benazepril which is Benazeprilate (BENZT). The three methods were validated as per the ICH guidelines and the standard curves were found to be linear in the range of 5-60 μg/mL for Benazepril and 5-30 for Amlodipine, with well accepted mean correlation coefficient for each analyte. The intra-day and inter-day precision and accuracy results were well within the acceptable limits.
Emulating facial biomechanics using multivariate partial least squares surrogate models
Martens, Harald; Wu, Tim; Hunter, Peter; Mithraratne, Kumar
2014-01-01
This is the author’s final, accepted and refereed manuscript to the article. Locked until 2015-05-06 A detailed biomechanical model of the human face driven by a network of muscles is a useful tool in relating the muscle activities to facial deformations. However, lengthy computational times often hinder its applications in practical settings. The objective of this study is to replace precise but computationally demanding biomechanical model by a much faster multivariate meta-mode...
Multi-Criteria Model for Determining Order Size
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Katarzyna Jakowska-Suwalska
2013-01-01
Full Text Available A multi-criteria model for determining the order size for materials used in production has been presented. It was assumed that the consumption rate of each material is a random variable with a known probability distribution. Using such a model, in which the purchase cost of materials ordered is limited, three criteria were considered: order size, probability of a lack of materials in the production process, and deviations in the order size from the consumption rate in past periods. Based on an example, it has been shown how to use the model to determine the order sizes for polyurethane adhesive and wood in a hard-coal mine. (original abstract
Directory of Open Access Journals (Sweden)
K. Skouri
2009-01-01
Full Text Available An order level inventory model for seasonable/fashionable products subject to a period of increasing demand followed by a period of level demand and then by a period of decreasing demand rate (three branches ramp type demand rate is considered. The unsatisfied demand is partially backlogged with a time dependent backlogging rate. In addition, the product deteriorates with a time dependent, namely, Weibull, deterioration rate. The model is studied under the following different replenishment policies: (a starting with no shortages and (b starting with shortages. The optimal replenishment policy for the model is derived for both the above mentioned policies.
the Modeling of Hydraulic Jump Generated Partially on Sloping Apron
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Shaker Abdulatif Jalil
2017-12-01
Full Text Available Modeling aims to characterize system behavior and achieve simulation close as possible of the reality. The rapid energy exchange in supercritical flow to generate quiet or subcritical flow in hydraulic jump phenomenon is important in design of hydraulic structures. Experimental and numerical modeling is done on type B hydraulic jump which starts first on sloping bed and its end on horizontal bed. Four different apron slopes are used, for each one of these slopes the jump is generated on different locations by controlling the tail water depth. Modelling validation is based on 120 experimental runs which they show that there is reliability. The air volume fraction which creates in through hydraulic jump varied between 0.18 and 0.28. While the energy exchanges process take place within 6.6, 6.1, 5.8, 5.5 of the average relative jump height for apron slopes of 0.18, 0.14, 0.10, 0.07 respectively. Within the limitations of this study, mathematical prediction model for relative hydraulic jump height is suggested.The model having an acceptable coefficient of determination.
A variable-order fractal derivative model for anomalous diffusion
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Liu Xiaoting
2017-01-01
Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.
Yan, Luchun; Liu, Jiemin; Qu, Chen; Gu, Xingye; Zhao, Xia
2015-01-28
In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.
Anisotropic Third-Order Regularization for Sparse Digital Elevation Models
Lellmann, Jan; Morel, Jean-Michel; Schö nlieb, Carola-Bibiane
2013-01-01
features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE
A simplified parsimonious higher order multivariate Markov chain model
Wang, Chao; Yang, Chuan-sheng
2017-09-01
In this paper, a simplified parsimonious higher-order multivariate Markov chain model (SPHOMMCM) is presented. Moreover, parameter estimation method of TPHOMMCM is give. Numerical experiments shows the effectiveness of TPHOMMCM.
A tridiagonal parsimonious higher order multivariate Markov chain model
Wang, Chao; Yang, Chuan-sheng
2017-09-01
In this paper, we present a tridiagonal parsimonious higher-order multivariate Markov chain model (TPHOMMCM). Moreover, estimation method of the parameters in TPHOMMCM is give. Numerical experiments illustrate the effectiveness of TPHOMMCM.
First-order regional seismotectonic model for South Africa
CSIR Research Space (South Africa)
Singh, M
2011-10-01
Full Text Available A first-order seismotectonic model was created for South Africa. This was done using four logical steps: geoscientific data collection, characterisation, assimilation and zonation. Through the definition of subunits of concentrations of earthquake...
A discrete model of a modified Burgers' partial differential equation
Mickens, R. E.; Shoosmith, J. N.
1990-01-01
A new finite-difference scheme is constructed for a modified Burger's equation. Three special cases of the equation are considered, and the 'exact' difference schemes for the space- and time-independent forms of the equation are presented, along with the diffusion-free case of Burger's equation modeled by a difference equation. The desired difference scheme is then obtained by imposing on any difference model of the initial equation the requirement that, in the appropriate limits, its difference scheme must reduce the results of the obtained equations.
Mechanical model for filament buckling and growth by phase ordering.
Rey, Alejandro D; Abukhdeir, Nasser M
2008-02-05
A mechanical model of open filament shape and growth driven by phase ordering is formulated. For a given phase-ordering driving force, the model output is the filament shape evolution and the filament end-point kinematics. The linearized model for the slope of the filament is the Cahn-Hilliard model of spinodal decomposition, where the buckling corresponds to concentration fluctuations. Two modes are predicted: (i) sequential growth and buckling and (ii) simultaneous buckling and growth. The relation among the maximum buckling rate, filament tension, and matrix viscosity is given. These results contribute to ongoing work in smectic A filament buckling.
Models & Searches of CPT Violation: a personal, very partial, list
Mavromatos, Nick E.
2018-01-01
In this talk, first I motivate theoretically, and then I review the phenomenology of, some models entailing CPT Violation (CPTV). The latter is argued to be responsible for the observed matter-antimatter asymmetry in the Cosmos, and may owe its origin to either Lorentz-violating background geometries, whose effects are strong in early epochs of the Universe but very weak today, being temperature dependent in general, or to an ill-defined CPT generator in some quantum gravity models entailing decoherence of quantum matter as a result of quantum degrees of freedom in the gravity sector that are inaccessible to the low-energy observers. In particular, for the latter category of CPTV, I argue that entangled states of neutral mesons (Kaons or B-systems), of central relevance to KLOE-2 experiment, can provide smoking-gun sensitive tests or even falsify some of these models. If CPT is ill-defined one may also encounter violations of the spin-statistics theorem, with possible consequences for the Pauli Exclusion Principle, which I only briefly touch upon.
Models & Searches of CPT Violation: a personal, very partial, list
Directory of Open Access Journals (Sweden)
Mavromatos Nick E.
2018-01-01
Full Text Available In this talk, first I motivate theoretically, and then I review the phenomenology of, some models entailing CPT Violation (CPTV. The latter is argued to be responsible for the observed matter-antimatter asymmetry in the Cosmos, and may owe its origin to either Lorentz-violating background geometries, whose effects are strong in early epochs of the Universe but very weak today, being temperature dependent in general, or to an ill-defined CPT generator in some quantum gravity models entailing decoherence of quantum matter as a result of quantum degrees of freedom in the gravity sector that are inaccessible to the low-energy observers. In particular, for the latter category of CPTV, I argue that entangled states of neutral mesons (Kaons or B-systems, of central relevance to KLOE-2 experiment, can provide smoking-gun sensitive tests or even falsify some of these models. If CPT is ill-defined one may also encounter violations of the spin-statistics theorem, with possible consequences for the Pauli Exclusion Principle, which I only briefly touch upon.
Fractional-Order Nonlinear Systems Modeling, Analysis and Simulation
Petráš, Ivo
2011-01-01
"Fractional-Order Nonlinear Systems: Modeling, Analysis and Simulation" presents a study of fractional-order chaotic systems accompanied by Matlab programs for simulating their state space trajectories, which are shown in the illustrations in the book. Description of the chaotic systems is clearly presented and their analysis and numerical solution are done in an easy-to-follow manner. Simulink models for the selected fractional-order systems are also presented. The readers will understand the fundamentals of the fractional calculus, how real dynamical systems can be described using fractional derivatives and fractional differential equations, how such equations can be solved, and how to simulate and explore chaotic systems of fractional order. The book addresses to mathematicians, physicists, engineers, and other scientists interested in chaos phenomena or in fractional-order systems. It can be used in courses on dynamical systems, control theory, and applied mathematics at graduate or postgraduate level. ...
Lagrangian generic second order traffic flow models for node
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Asma Khelifi
2018-02-01
Full Text Available This study sheds light on higher order macroscopic traffic flow modeling on road networks, thanks to the generic second order models (GSOM family which embeds a myriad of traffic models. It has been demonstrated that such higher order models are easily solved in Lagrangian coordinates which are compatible with both microscopic and macroscopic descriptions. The generalized GSOM model is reformulated in the Lagrangian coordinate system to develop a more efficient numerical method. The difficulty in applying this approach on networks basically resides in dealing with node dynamics. Traffic flow characteristics at node are different from that on homogeneous links. Different geometry features can lead to different critical research issues. For instance, discontinuity in traffic stream can be an important issue for traffic signal operations, while capacity drop may be crucial for lane-merges. The current paper aims to establish and analyze a new adapted node model for macroscopic traffic flow models by applying upstream and downstream boundary conditions on the Lagrangian coordinates in order to perform simulations on networks of roads, and accompanying numerical method. The internal node dynamics between upstream and downstream links are taken into account of the node model. Therefore, a numerical example is provided to underscore the efficiency of this approach. Simulations show that the discretized node model yields accurate results. Additional kinematic waves and contact discontinuities are induced by the variation of the driver attribute.
International Nuclear Information System (INIS)
Fu, Y; Xu, O; Yang, W; Zhou, L; Wang, J
2017-01-01
To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately. (paper)
Multi-skyrmion solutions of a sixth order Skyrme model
International Nuclear Information System (INIS)
Floratos, I.
2001-08-01
In this thesis, we study some of the classical properties of an extension of the Skyrme model defined by adding a sixth order derivative term to the Lagrangian. In chapter 1, we review the physical as well as the mathematical motivation behind the study of the Skyrme model and in chapter 2, we give a brief summary of various extended Skyrme models that have been proposed over the last few years. We then define a new sixth order Skyrme model by introducing a dimensionless parameter λ that denotes the mixing between the two higher order terms, the Skyrme term and the sixth order term. In chapter 3 we compute numerically the multi-skyrmion solutions of this extended model and show that they have the same symmetries with the usual skyrmion solutions. In addition, we analyse the dependence of the energy and radius of these classical solutions with respect to the coupling constant λ. We compare our results with experimental data and determine whether this modified model can provide us with better theoretical predictions than the original one. In chapter 4, we use the rational map ansatz, introduced by Houghton, Manton and Sutcliffe, to approximate minimum energy multi-skyrmion solutions with B ≤ 9 of the SU(2) model and with B ≤ 6 of the SU(3) model. We compare our results with the ones obtained numerically and show that the rational map ansatz works just as well for the generalised model as for the pure Skyrme model, at least for B ≤ 5. In chapter 5, we use a generalisation of the rational map ansatz, introduced by loannidou, Piette and Zakrzewski, to construct analytically some topologically non-trivial solutions of the extended model in SU(3). These solutions are spherically symmetric and some of them can be interpreted as bound states of skyrmions. Finally, we use the same ansatz to construct low energy configurations of the SU(N) sixth order Skyrme model. (author)
A simple procedure to model water level fluctuations in partially inundated wetlands
Spieksma, JFM; Schouwenaars, JM
When modelling groundwater behaviour in wetlands, there are specific problems related to the presence of open water in small-sized mosaic patterns. A simple quasi two-dimensional model to predict water level fluctuations in partially inundated wetlands is presented. In this model, the ratio between
Calculus for cognitive scientists partial differential equation models
Peterson, James K
2016-01-01
This book shows cognitive scientists in training how mathematics, computer science and science can be usefully and seamlessly intertwined. It is a follow-up to the first two volumes on mathematics for cognitive scientists, and includes the mathematics and computational tools needed to understand how to compute the terms in the Fourier series expansions that solve the cable equation. The latter is derived from first principles by going back to cellular biology and the relevant biophysics. A detailed discussion of ion movement through cellular membranes, and an explanation of how the equations that govern such ion movement leading to the standard transient cable equation are included. There are also solutions for the cable model using separation of variables, as well an explanation of why Fourier series converge and a description of the implementation of MatLab tools to compute the solutions. Finally, the standard Hodgkin - Huxley model is developed for an excitable neuron and is solved using MatLab.
Deletion of the App-Runx1 region in mice models human partial monosomy 21
Directory of Open Access Journals (Sweden)
Thomas Arbogast
2015-06-01
Full Text Available Partial monosomy 21 (PM21 is a rare chromosomal abnormality that is characterized by the loss of a variable segment along human chromosome 21 (Hsa21. The clinical phenotypes of this loss are heterogeneous and range from mild alterations to lethal consequences, depending on the affected region of Hsa21. The most common features include intellectual disabilities, craniofacial dysmorphology, short stature, and muscular and cardiac defects. As a complement to human genetic approaches, our team has developed new monosomic mouse models that carry deletions on Hsa21 syntenic regions in order to identify the dosage-sensitive genes that are responsible for the symptoms. We focus here on the Ms5Yah mouse model, in which a 7.7-Mb region has been deleted from the App to Runx1 genes. Ms5Yah mice display high postnatal lethality, with a few surviving individuals showing growth retardation, motor coordination deficits, and spatial learning and memory impairments. Further studies confirmed a gene dosage effect in the Ms5Yah hippocampus, and pinpointed disruptions of pathways related to cell adhesion (involving App, Cntnap5b, Lgals3bp, Mag, Mcam, Npnt, Pcdhb2, Pcdhb3, Pcdhb4, Pcdhb6, Pcdhb7, Pcdhb8, Pcdhb16 and Vwf. Our PM21 mouse model is the first to display morphological abnormalities and behavioural phenotypes similar to those found in affected humans, and it therefore demonstrates the major contribution that the App-Runx1 region has in the pathophysiology of PM21.
Kang, Hyeon-Ah; Su, Ya-Hui; Chang, Hua-Hua
2018-03-08
A monotone relationship between a true score (τ) and a latent trait level (θ) has been a key assumption for many psychometric applications. The monotonicity property in dichotomous response models is evident as a result of a transformation via a test characteristic curve. Monotonicity in polytomous models, in contrast, is not immediately obvious because item response functions are determined by a set of response category curves, which are conceivably non-monotonic in θ. The purpose of the present note is to demonstrate strict monotonicity in ordered polytomous item response models. Five models that are widely used in operational assessments are considered for proof: the generalized partial credit model (Muraki, 1992, Applied Psychological Measurement, 16, 159), the nominal model (Bock, 1972, Psychometrika, 37, 29), the partial credit model (Masters, 1982, Psychometrika, 47, 147), the rating scale model (Andrich, 1978, Psychometrika, 43, 561), and the graded response model (Samejima, 1972, A general model for free-response data (Psychometric Monograph no. 18). Psychometric Society, Richmond). The study asserts that the item response functions in these models strictly increase in θ and thus there exists strict monotonicity between τ and θ under certain specified conditions. This conclusion validates the practice of customarily using τ in place of θ in applied settings and provides theoretical grounds for one-to-one transformations between the two scales. © 2018 The British Psychological Society.
Average inactivity time model, associated orderings and reliability properties
Kayid, M.; Izadkhah, S.; Abouammoh, A. M.
2018-02-01
In this paper, we introduce and study a new model called 'average inactivity time model'. This new model is specifically applicable to handle the heterogeneity of the time of the failure of a system in which some inactive items exist. We provide some bounds for the mean average inactivity time of a lifespan unit. In addition, we discuss some dependence structures between the average variable and the mixing variable in the model when original random variable possesses some aging behaviors. Based on the conception of the new model, we introduce and study a new stochastic order. Finally, to illustrate the concept of the model, some interesting reliability problems are reserved.
International Nuclear Information System (INIS)
McLoughlin, R.F.; Ryan, M.V.; Heuston, P.M.; McCoy, C.T.; Masterson, J.B.
1992-01-01
The purpose of this study was to construct and evaluate a statistical model for the quantitative analysis of computed tomographic brain images. Data were derived from standard sections in 34 normal studies. A model representing the intercranial pure tissue and partial volume areas, with allowance for beam hardening, was developed. The average percentage error in estimation of areas, derived from phantom tests using the model, was 28.47%. We conclude that our model is not sufficiently accurate to be of clinical use, even though allowance was made for partial volume and beam hardening effects. (author)
Testing static tradeoff theiry against pecking order models of capital ...
African Journals Online (AJOL)
We test two models with the purpose of finding the best empirical explanation for corporate financing choice of a cross section of 27 Nigerian quoted companies. The models were developed to represent the Static tradeoff Theory and the Pecking order Theory of capital structure with a view to make comparison between ...
Data-Driven Model Order Reduction for Bayesian Inverse Problems
Cui, Tiangang
2014-01-06
One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.
Next-to-leading order corrections to the valon model
Indian Academy of Sciences (India)
A seminumerical solution to the valon model at next-to-leading order (NLO) in the Laguerre polynomials is presented. We used the valon model to generate the structure of proton with respect to the Laguerre polynomials method. The results are compared with H1 data and other parametrizations.
Error propagation of partial least squares for parameters optimization in NIR modeling.
Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng
2018-03-05
A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.
Error propagation of partial least squares for parameters optimization in NIR modeling
Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng
2018-03-01
A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.
Various verifying tests using full size partial models of PCCV
International Nuclear Information System (INIS)
Nagata, Kaoru; Fukihara, Masaaki; Takemoto, Yasushi.
1987-01-01
The prestressed concrete containment vessel (PCCV) for Tsuruga No.2 plant of Japan Atomic Power Co. was adopted for the first time in Japan, and the necessity of experimental verification was pointed out about a number of items in the design and construction. In this report, the various tests carried out with full size models are described. The tendon system adopted for this PCCV is BBRV type, in which PC wires are bundled in parallel to make cables, and involves many matters inexperienced in Japan, such as the stretching capacity is as large as 1000 t class, the longest cable is 160 m, and it is the unbonded system of injecting rust inhibitor. It was demanded to confirm by testing the propriety of the small coefficient of friction at the time of stretching tendons. For the tests, the materials, equipment and their size were prepared all as those for actual works. The test works became the rehearsal of the actual prestressing works. Besides, by utilizing these full size test beds, the workability test on concrete at the time of their construction, the confirmation test on tendon strength and the safety of concrete at fixing part at the time of friction test, thereafter, greasing test, the simulation test of in-service inspection, and the thermal loading test on liners were carried out. The results of these tests are briefly reported. (Kako, I.)
A new Bayesian model applied to cytogenetic partial body irradiation estimation
International Nuclear Information System (INIS)
Higueras, Manuel; Puig, Pedro; Ainsbury, Elizabeth A.; Vinnikov, Volodymyr A.; Rothkamm, Kai
2016-01-01
A new zero-inflated Poisson model is introduced for the estimation of partial body irradiation dose and fraction of body irradiated. The Bayes factors are introduced as tools to help determine whether a data set of chromosomal aberrations obtained from a blood sample reflects partial or whole body irradiation. Two examples of simulated cytogenetic radiation exposure data are presented to demonstrate the usefulness of this methodology in cytogenetic biological dosimetry. (authors)
International Nuclear Information System (INIS)
Mancarella, Pierluigi; Chicco, Gianfranco
2009-01-01
Small-scale distributed cogeneration technologies represent a key resource to increase generation efficiency and reduce greenhouse gas emissions with respect to conventional separate production means. However, the diffusion of distributed cogeneration within urban areas, where air quality standards are quite stringent, brings about environmental concerns on a local level. In addition, partial-load emission worsening is often overlooked, which could lead to biased evaluations of the energy system environmental performance. In this paper, a comprehensive emission assessment framework suitable for addressing distributed cogeneration systems is formulated. Local and global emission impact models are presented to identify upper and lower boundary values of the environmental pressure from pollutants that would be emitted from reference technologies, to be compared to the actual emissions from distributed cogeneration. This provides synthetic information on the relative environmental impact from small-scale CHP sources, useful for general indicative and non-site-specific studies. The emission models are formulated according to an electrical output-based emission factor approach, through which off-design operation and relevant performance are easily accounted for. In particular, in order to address the issues that could arise under off-design operation, an equivalent load model is incorporated within the proposed framework, by exploiting the duration curve of the cogenerator loading and the emissions associated to each loading level. In this way, it is possible to quantify the contribution to the emissions from cogeneration systems that might operate at partial loads for a significant portion of their operation time, as for instance in load-tracking applications. Suitability of the proposed methodology is discussed with respect to hazardous air pollutants such as NO x and CO, as well as to greenhouse gases such as CO 2 . Two case study applications based on the emission
Nam, Sungsik; Hasna, Mazen Omar; Alouini, Mohamed-Slim
2011-01-01
-interference on GSC RAKE receivers. The major difficulty in these problems is to derive some joint statistics of ordered exponential variates. With this motivation in mind, we capitalize in this paper on some new order statistics results to derive exact closed
Modeling Human Behaviour with Higher Order Logic: Insider Threats
DEFF Research Database (Denmark)
Boender, Jaap; Ivanova, Marieta Georgieva; Kammuller, Florian
2014-01-01
it to the sociological process of logical explanation. As a case study on modeling human behaviour, we present the modeling and analysis of insider threats as a Higher Order Logic theory in Isabelle/HOL. We show how each of the three step process of sociological explanation can be seen in our modeling of insider’s state......, its context within an organisation and the effects on security as outcomes of a theorem proving analysis....
Marginal and Interaction Effects in Ordered Response Models
Debdulal Mallick
2009-01-01
In discrete choice models the marginal effect of a variable of interest that is interacted with another variable differs from the marginal effect of a variable that is not interacted with any variable. The magnitude of the interaction effect is also not equal to the marginal effect of the interaction term. I present consistent estimators of both marginal and interaction effects in ordered response models. This procedure is general and can easily be extended to other discrete choice models. I ...
Partially nested designs in psychotherapy trials: A review of modeling developments.
Sterba, Sonya K
2017-07-01
Individually-randomized psychotherapy trials are often partially nested. For instance, individuals assigned to a treatment arm may be clustered into therapy groups for purposes of treatment administration, whereas individuals assigned to a wait-list control are unclustered. The past several years have seen rapid expansion and investigation of methods for analyzing partially nested data. Yet partial nesting often remains ignored in psychotherapy trials. This review integrates and disseminates developments in the analysis of partially nested data that are particularly relevant for psychotherapy researchers. First, we differentiate among alternative partially nested designs. Then, we present adaptations of multilevel model specifications that accommodate each design. Next, we address how moderation by treatment as well as mediation of the treatment effect can be investigated in partially nested designs. Model fitting results, annotated software syntax, and illustrative data sets are provided and key methodological issues are discussed. We emphasize that cluster-level variability in the treatment arm need not be considered a nuisance; it can be modeled to yield insights about the treatment process.
International Nuclear Information System (INIS)
Reynolds, Jacob G.
2013-01-01
Partial molar properties are the changes occurring when the fraction of one component is varied while the fractions of all other component mole fractions change proportionally. They have many practical and theoretical applications in chemical thermodynamics. Partial molar properties of chemical mixtures are difficult to measure because the component mole fractions must sum to one, so a change in fraction of one component must be offset with a change in one or more other components. Given that more than one component fraction is changing at a time, it is difficult to assign a change in measured response to a change in a single component. In this study, the Component Slope Linear Model (CSLM), a model previously published in the statistics literature, is shown to have coefficients that correspond to the intensive partial molar properties. If a measured property is plotted against the mole fraction of a component while keeping the proportions of all other components constant, the slope at any given point on a graph of this curve is the partial molar property for that constituent. Actually plotting this graph has been used to determine partial molar properties for many years. The CSLM directly includes this slope in a model that predicts properties as a function of the component mole fractions. This model is demonstrated by applying it to the constant pressure heat capacity data from the NaOH-NaAl(OH 4 H 2 O system, a system that simplifies Hanford nuclear waste. The partial molar properties of H 2 O, NaOH, and NaAl(OH) 4 are determined. The equivalence of the CSLM and the graphical method is verified by comparing results detennined by the two methods. The CSLM model has been previously used to predict the liquidus temperature of spinel crystals precipitated from Hanford waste glass. Those model coefficients are re-interpreted here as the partial molar spinel liquidus temperature of the glass components
A partial test of a hospital behavioral model.
Hornbrook, M C; Goldfarb, M G
1983-01-01
The influence of hospital and community characteristics on the behavior of five dimensions of hospital output is examined in this article. These dimensions are the level of emergency stand-by capacity, total admissions, the diagnosis-mix of admissions and the hospital's 'style of practice' with regard to ancillary services and length of stay. A simultaneous equations model is estimated with data from a sample of 63 New England short-term general hospitals for 1970. The findings suggest that various types of short-term general hospitals have distinctive preferences for emergency capacity, volume, case mix and style of practice, and that style of practice may be more appropriately viewed as a rate of resource use per day. Specific findings of interest include the positive interdependence between protection against running out of emergency beds and length of stay, and between length of stay and ancillary service use. Hospitals that admit greater numbers of patients tend to treat more severely ill patients, and sicker patients tend to go to larger hospitals. Hospitals that provide more ancillary services tend to attract the more acutely ill patients. Relationships among other elements of the hospital's utility function represent trade-offs, i.e. substitution, in a constrained world. Among the exogenous factors, patient preferences and ability to pay have strong associations with the types of care provided by hospitals. Highly educated, high income communities, for example, tend to prefer risk averse, service intensive hospital output. Teaching hospitals are shown to prefer higher protection levels, service-intensive patterns of care, and higher admissions levels. Self-paying patients tend to be admitted for more discretionary types of diagnoses and to receive longer diagnosis-specific lengths of stay. A relatively greater supply of physician specialists in the market area is associated with increased use of ancillary services in the hospital. If replicated, these
A chiral quark model for meson electroproduction in the S11 partial wave
International Nuclear Information System (INIS)
Golli, B.; Sirca, S.
2011-01-01
We calculate the meson scattering and electroproduction amplitudes in the S11 partial wave in a coupled-channel approach that incorporates quasi-bound quark-model states. Using the quark wave functions and the quark-meson interaction from the Cloudy Bag Model, we obtain a good overall agreement with the available experimental results for the partial widths of the N(1535) and the N(1650) resonances as well as for the pion, eta and kaon electroproduction amplitudes. Our model is consistent with the N(1535) resonance being dominantly a genuine three-quark state rather than a quasi-bound state of mesons and baryons. (orig.)
AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS
Energy Technology Data Exchange (ETDEWEB)
Mandelli, D.; Alfonsi, A.; Talbot, P.; Wang, C.; Maljovec, D.; Smith, C.; Rabiti, C.; Cogliati, J.
2016-10-01
The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, the overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).
Nam, Sungsik
2014-08-01
The joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distribution assumption may not be valid in several real-world applications. With this motivation in mind, we consider in this paper the more general case in which the random variables are independent but not necessarily identically distributed (i.n.d.). More specifically, we extend the previous analysis and introduce a new more general unified analytical framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE receivers operating over frequency-selective fading channels with a non-uniform power delay profile. © 1991-2012 IEEE.
Composite symmetry-protected topological order and effective models
Nietner, A.; Krumnow, C.; Bergholtz, E. J.; Eisert, J.
2017-12-01
Strongly correlated quantum many-body systems at low dimension exhibit a wealth of phenomena, ranging from features of geometric frustration to signatures of symmetry-protected topological order. In suitable descriptions of such systems, it can be helpful to resort to effective models, which focus on the essential degrees of freedom of the given model. In this work, we analyze how to determine the validity of an effective model by demanding it to be in the same phase as the original model. We focus our study on one-dimensional spin-1 /2 systems and explain how nontrivial symmetry-protected topologically ordered (SPT) phases of an effective spin-1 model can arise depending on the couplings in the original Hamiltonian. In this analysis, tensor network methods feature in two ways: on the one hand, we make use of recent techniques for the classification of SPT phases using matrix product states in order to identify the phases in the effective model with those in the underlying physical system, employing Künneth's theorem for cohomology. As an intuitive paradigmatic model we exemplify the developed methodology by investigating the bilayered Δ chain. For strong ferromagnetic interlayer couplings, we find the system to transit into exactly the same phase as an effective spin-1 model. However, for weak but finite coupling strength, we identify a symmetry broken phase differing from this effective spin-1 description. On the other hand, we underpin our argument with a numerical analysis making use of matrix product states.
SUN, D.; TONG, L.
2002-05-01
A detailed model for the beams with partially debonded active constraining damping (ACLD) treatment is presented. In this model, the transverse displacement of the constraining layer is considered to be non-identical to that of the host structure. In the perfect bonding region, the viscoelastic core is modelled to carry both peel and shear stresses, while in the debonding area, it is assumed that no peel and shear stresses be transferred between the host beam and the constraining layer. The adhesive layer between the piezoelectric sensor and the host beam is also considered in this model. In active control, the positive position feedback control is employed to control the first mode of the beam. Based on this model, the incompatibility of the transverse displacements of the active constraining layer and the host beam is investigated. The passive and active damping behaviors of the ACLD patch with different thicknesses, locations and lengths are examined. Moreover, the effects of debonding of the damping layer on both passive and active control are examined via a simulation example. The results show that the incompatibility of the transverse displacements is remarkable in the regions near the ends of the ACLD patch especially for the high order vibration modes. It is found that a thinner damping layer may lead to larger shear strain and consequently results in a larger passive and active damping. In addition to the thickness of the damping layer, its length and location are also key factors to the hybrid control. The numerical results unveil that edge debonding can lead to a reduction of both passive and active damping, and the hybrid damping may be more sensitive to the debonding of the damping layer than the passive damping.
A Comparison of Item Exposure Control Procedures with the Generalized Partial Credit Model
Sanchez, Edgar Isaac
2008-01-01
To enhance test security of high stakes tests, it is vital to understand the way various exposure control strategies function under various IRT models. To that end the present dissertation focused on the performance of several exposure control strategies under the generalized partial credit model with an item pool of 100 and 200 items. These…
Penfield, Randall D.; Myers, Nicholas D.; Wolfe, Edward W.
2008-01-01
Measurement invariance in the partial credit model (PCM) can be conceptualized in several different but compatible ways. In this article the authors distinguish between three forms of measurement invariance in the PCM: step invariance, item invariance, and threshold invariance. Approaches for modeling these three forms of invariance are proposed,…
Logical Specification and Analysis of Fault Tolerant Systems through Partial Model Checking
Gnesi, S.; Etalle, Sandro; Mukhopadhyay, S.; Lenzini, Gabriele; Lenzini, G.; Martinelli, F.; Roychoudhury, A.
2003-01-01
This paper presents a framework for a logical characterisation of fault tolerance and its formal analysis based on partial model checking techniques. The framework requires a fault tolerant system to be modelled using a formal calculus, here the CCS process algebra. To this aim we propose a uniform
Venus gravity and topography: 60th degree and order model
Konopliv, A. S.; Borderies, N. J.; Chodas, P. W.; Christensen, E. J.; Sjogren, W. L.; Williams, B. G.; Balmino, G.; Barriot, J. P.
1993-01-01
We have combined the most recent Pioneer Venus Orbiter (PVO) and Magellan (MGN) data with the earlier 1978-1982 PVO data set to obtain a new 60th degree and order spherical harmonic gravity model and a 120th degree and order spherical harmonic topography model. Free-air gravity maps are shown over regions where the most marked improvement has been obtained (Ishtar-Terra, Alpha, Bell and Artemis). Gravity versus topography relationships are presented as correlations per degree and axes orientation.
Reduced order modeling of flashing two-phase jets
Energy Technology Data Exchange (ETDEWEB)
Gurecky, William, E-mail: william.gurecky@utexas.edu; Schneider, Erich, E-mail: eschneider@mail.utexas.edu; Ballew, Davis, E-mail: davisballew@utexas.edu
2015-12-01
Highlights: • Accident simulation requires ability to quickly predict two-phase flashing jet's damage potential. • A reduced order modeling methodology informed by experimental or computational data is described. • Zone of influence volumes are calculated for jets of various upstream thermodynamic conditions. - Abstract: In the event of a Loss of Coolant Accident (LOCA) in a pressurized water reactor, the escaping coolant produces a highly energetic flashing jet with the potential to damage surrounding structures. In LOCA analysis, the goal is often to evaluate many break scenarios in a Monte Carlo style simulation to evaluate the resilience of a reactor design. Therefore, in order to quickly predict the damage potential of flashing jets, it is of interest to develop a reduced order model that relates the damage potential of a jet to the pressure and temperature upstream of the break and the distance from the break to a given object upon which the jet is impinging. This work presents framework for producing a Reduced Order Model (ROM) that may be informed by measured data, Computational Fluid Dynamics (CFD) simulations, or a combination of both. The model is constructed by performing regression analysis on the pressure field data, allowing the impingement pressure to be quickly reconstructed for any given upstream thermodynamic condition within the range of input data. The model is applicable to both free and fully impinging two-phase flashing jets.
Reverse time migration by Krylov subspace reduced order modeling
Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali
2018-04-01
Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.
International Nuclear Information System (INIS)
Suarez Antola, R.
2009-01-01
In the framework of an analytic or numerical model of a BWR power plant, this could imply first to find an suitable approximation to the solution manifold of the differential equations describing the stability behaviour of this nonlinear system, and then a classification of the different solution types concerning their relation with the operational safety of the power plant, by distributing the different solution types in relation with the exclusion region of the power-flow map. Then the goal is to obtain the best attainable qualitative and quantitative global picture of plant dynamics. To do this, the construction and the analysis of the so called reduced order models (Rom) seems a necessary step. A reduced order model results after the full system of coupled nonlinear partial differential equations of the plant is reduced to a system of coupled nonlinear ordinary differential equations
Impact of Physics Parameterization Ordering in a Global Atmosphere Model
Donahue, Aaron S.; Caldwell, Peter M.
2018-02-01
Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.
Modeling biological gradient formation: combining partial differential equations and Petri nets.
Bertens, Laura M F; Kleijn, Jetty; Hille, Sander C; Heiner, Monika; Koutny, Maciej; Verbeek, Fons J
2016-01-01
Both Petri nets and differential equations are important modeling tools for biological processes. In this paper we demonstrate how these two modeling techniques can be combined to describe biological gradient formation. Parameters derived from partial differential equation describing the process of gradient formation are incorporated in an abstract Petri net model. The quantitative aspects of the resulting model are validated through a case study of gradient formation in the fruit fly.
Bortolon, Catherine; Krikorian, Alicia; Carayol, Marion; Brouillet, Denis; Romieu, Gilles; Ninot, Gregory
2014-04-01
The aim of this study is to examine factors contributing to cancer-related fatigue (CRF) in breast cancer patients who have undergone surgery. Sixty women (mean age: 50.0) completed self-rated questionnaires assessing components of CRF, muscular and cognitive functions. Also, physiological and subjective data were gathered. Data were analyzed using partial least squares variance-based structural equation modeling in order to examine factors contributing to CRF after breast surgery. The tested model was robust in terms of its measurement quality (reliability and validity). According to the structural model results, emotional distress (β = 0.59; p accounting for 61% of the explained variance. Also, emotional distress (β = 0.41; p accounted for 41% of the explained variance. However, the relationship between low physical function and CRF was weak and nonsignificant (β = 0.01; p > 0.05). Emotional distress, altered vigilance capacity, and pain are associated with CRF in postsurgical breast cancer. In addition, emotional distress and pain are related to diminished physical function, which, in turn, has no significant impact on CRF. The current model should be examined in subsequent phases of the treatment (chemotherapy and/or radiotherapy) when side effects are more pronounced and may lead to increased intensity of CRF and low physical function. Copyright © 2013 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
Neeraj Kumar
2016-05-01
Full Text Available In the present study, the Economic Order Quantity (EOQ model of two-warehouse deals with non-instantaneous deteriorating items, the demand rate considered as stock dependent and model affected by inflation under the pattern of time value of money over a finite planning horizon. Shortages are allowed and partially backordered depending on the waiting time for the next replenishment. The main objective of this work is to minimize the total inventory cost and finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented.
Numerical Analysis of Fractional Order Epidemic Model of Childhood Diseases
Directory of Open Access Journals (Sweden)
Fazal Haq
2017-01-01
Full Text Available The fractional order Susceptible-Infected-Recovered (SIR epidemic model of childhood disease is considered. Laplace–Adomian Decomposition Method is used to compute an approximate solution of the system of nonlinear fractional differential equations. We obtain the solutions of fractional differential equations in the form of infinite series. The series solution of the proposed model converges rapidly to its exact value. The obtained results are compared with the classical case.
The Ising model coupled to 2d orders
Glaser, Lisa
2018-04-01
In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase diagram in terms of the Wick rotation parameter β and the Ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure. The couplings give rise to five different phases. The causal sets take on random or crystalline characteristics as described in Surya (2012 Class. Quantum Grav. 29 132001) and the Ising model can be correlated or uncorrelated on the random orders and correlated, uncorrelated or anti-correlated on the crystalline orders. We find that at least one new phase transition arises, in which the Ising spins push the causal set into the crystalline phase.
Robust simulation of buckled structures using reduced order modeling
International Nuclear Information System (INIS)
Wiebe, R.; Perez, R.A.; Spottswood, S.M.
2016-01-01
Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties. (paper)
Robust simulation of buckled structures using reduced order modeling
Wiebe, R.; Perez, R. A.; Spottswood, S. M.
2016-09-01
Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.
Czech Academy of Sciences Publication Activity Database
Kudrnovský, Josef; Drchal, Václav; Turek, Ilja
2015-01-01
Roč. 92, č. 22 (2015), "224421-1"-"224421-8" ISSN 1098-0121 R&D Projects: GA ČR GA15-13436S Institutional support: RVO:68378271 ; RVO:68081723 Keywords : anomalous Hall effect * anisotropis magnetoresistance * first-principles * effect of ordering Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 3.736, year: 2014
Park, Marcelo; Mendes, Pedro Vitale; Costa, Eduardo Leite Vieira; Barbosa, Edzangela Vasconcelos Santos; Hirota, Adriana Sayuri; Azevedo, Luciano Cesar Pontes
2016-01-01
The aim of this study was to explore the factors associated with blood oxygen partial pressure and carbon dioxide partial pressure. The factors associated with oxygen - and carbon dioxide regulation were investigated in an apneic pig model under veno-venous extracorporeal membrane oxygenation support. A predefined sequence of blood and sweep flows was tested. Oxygenation was mainly associated with extracorporeal membrane oxygenation blood flow (beta coefficient = 0.036mmHg/mL/min), cardiac output (beta coefficient = -11.970mmHg/L/min) and pulmonary shunting (beta coefficient = -0.232mmHg/%). Furthermore, the initial oxygen partial pressure and carbon dioxide partial pressure measurements were also associated with oxygenation, with beta coefficients of 0.160 and 0.442mmHg/mmHg, respectively. Carbon dioxide partial pressure was associated with cardiac output (beta coefficient = 3.578mmHg/L/min), sweep gas flow (beta coefficient = -2.635mmHg/L/min), temperature (beta coefficient = 4.514mmHg/ºC), initial pH (beta coefficient = -66.065mmHg/0.01 unit) and hemoglobin (beta coefficient = 6.635mmHg/g/dL). In conclusion, elevations in blood and sweep gas flows in an apneic veno-venous extracorporeal membrane oxygenation model resulted in an increase in oxygen partial pressure and a reduction in carbon dioxide partial pressure 2, respectively. Furthermore, without the possibility of causal inference, oxygen partial pressure was negatively associated with pulmonary shunting and cardiac output, and carbon dioxide partial pressure was positively associated with cardiac output, core temperature and initial hemoglobin.
Model order reduction for complex high-tech systems
Lutowska, A.; Hochstenbach, M.E.; Schilders, W.H.A.; Michielsen, B.; Poirier, J.R.
2012-01-01
This paper presents a computationally efficient model order reduction (MOR) technique for interconnected systems. This MOR technique preserves block structures and zero blocks and exploits separate MOR approximations for the individual sub-systems in combination with low rank approximations for the
Next-to-leading order corrections to the valon model
Indian Academy of Sciences (India)
Next-to-leading order corrections to the valon model. G R BOROUN. ∗ and E ESFANDYARI. Physics Department, Razi University, Kermanshah 67149, Iran. ∗. Corresponding author. E-mail: grboroun@gmail.com; boroun@razi.ac.ir. MS received 17 January 2014; revised 31 October 2014; accepted 21 November 2014.
Partial widths of boson resonances in the quark-gluon model of strong interactions
International Nuclear Information System (INIS)
Kaidalov, A.B.; Volkovitsky, P.E.
1981-01-01
The quark-gluon model of strong interactions based on the topological expansion and the string model ib used for the calculation of the partial widths of boson resonances in the channels with two pseudoscalar mesons. The partial widths of mesons with arbitrary spins lying on the vector and tensor Regge trajectories are expressed in terms of the only rho-meson width. The violation of SU(3) symmetry increases with the growth of the spin of the resonance. The theoretical predictions are in a good agreement with experimental data [ru
Bilinear reduced order approximate model of parabolic distributed solar collectors
Elmetennani, Shahrazed
2015-07-01
This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low dimensional bilinear state representation, enables the reproduction of the heat transfer dynamics along the collector tube for system analysis. Moreover, presented as a reduced order bilinear state space model, the well established control theory for this class of systems can be applied. The approximation efficiency has been proven by several simulation tests, which have been performed considering parameters of the Acurex field with real external working conditions. Model accuracy has been evaluated by comparison to the analytical solution of the hyperbolic distributed model and its semi discretized approximation highlighting the benefits of using the proposed numerical scheme. Furthermore, model sensitivity to the different parameters of the gaussian interpolation has been studied.
The Dif Identification in Constructed Response Items Using Partial Credit Model
Directory of Open Access Journals (Sweden)
Heri Retnawati
2017-10-01
Full Text Available The study was to identify the load, the type and the significance of differential item functioning (DIF in constructed response item using the partial credit model (PCM. The data in the study were the students’ instruments and the students’ responses toward the PISA-like test items that had been completed by 386 ninth grade students and 460 tenth grade students who had been about 15 years old in the Province of Yogyakarta Special Region in Indonesia. The analysis toward the item characteristics through the student categorization based on their class was conducted toward the PCM using CONQUEST software. Furthermore, by applying these items characteristics, the researcher draw the category response function (CRF graphic in order to identify whether the type of DIF content had been in uniform or non-uniform. The significance of DIF was identified by comparing the discrepancy between the difficulty level parameter and the error in the CONQUEST output results. The results of the analysis showed that from 18 items that had been analyzed there were 4 items which had not been identified load DIF, there were 5 items that had been identified containing DIF but not statistically significant and there were 9 items that had been identified containing DIF significantly. The causes of items containing DIF were discussed.
Integrable higher order deformations of Heisenberg supermagnetic model
International Nuclear Information System (INIS)
Guo Jiafeng; Yan Zhaowen; Wang Shikun; Wu Ke; Zhao Weizhong
2009-01-01
The Heisenberg supermagnet model is an integrable supersymmetric system and has a close relationship with the strong electron correlated Hubbard model. In this paper, we investigate the integrable higher order deformations of Heisenberg supermagnet models with two different constraints: (i) S 2 =3S-2I for S is an element of USPL(2/1)/S(U(2)xU(1)) and (ii) S 2 =S for S is an element of USPL(2/1)/S(L(1/1)xU(1)). In terms of the gauge transformation, their corresponding gauge equivalent counterparts are derived.
Accelerating transient simulation of linear reduced order models.
Energy Technology Data Exchange (ETDEWEB)
Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard; Bond, Brad
2011-10-01
Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.
Modeling and analysis of fractional order DC-DC converter.
Radwan, Ahmed G; Emira, Ahmed A; AbdelAty, Amr M; Azar, Ahmad Taher
2017-07-11
Due to the non-idealities of commercial inductors, the demand for a better model that accurately describe their dynamic response is elevated. So, the fractional order models of Buck, Boost and Buck-Boost DC-DC converters are presented in this paper. The detailed analysis is made for the two most common modes of converter operation: Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). Closed form time domain expressions are derived for inductor currents, voltage gain, average current, conduction time and power efficiency where the effect of the fractional order inductor is found to be strongly present. For example, the peak inductor current at steady state increases with decreasing the inductor order. Advanced Design Systems (ADS) circuit simulations are used to verify the derived formulas, where the fractional order inductor is simulated using Valsa Constant Phase Element (CPE) approximation and Generalized Impedance Converter (GIC). Different simulation results are introduced with good matching to the theoretical formulas for the three DC-DC converter topologies under different fractional orders. A comprehensive comparison with the recently published literature is presented to show the advantages and disadvantages of each approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Lyu, Jingyuan; Nakarmi, Ukash; Zhang, Chaoyi; Ying, Leslie
2016-05-01
This paper presents a new approach to highly accelerated dynamic parallel MRI using low rank matrix completion, partial separability (PS) model. In data acquisition, k-space data is moderately randomly undersampled at the center kspace navigator locations, but highly undersampled at the outer k-space for each temporal frame. In reconstruction, the navigator data is reconstructed from undersampled data using structured low-rank matrix completion. After all the unacquired navigator data is estimated, the partial separable model is used to obtain partial k-t data. Then the parallel imaging method is used to acquire the entire dynamic image series from highly undersampled data. The proposed method has shown to achieve high quality reconstructions with reduction factors up to 31, and temporal resolution of 29ms, when the conventional PS method fails.
Energy Technology Data Exchange (ETDEWEB)
MacAlpine, Sara; Deline, Chris
2015-09-15
It is often difficult to model the effects of partial shading conditions on PV array performance, as shade losses are nonlinear and depend heavily on a system's particular configuration. This work describes and implements a simple method for modeling shade loss: a database of shade impact results (loss percentages), generated using a validated, detailed simulation tool and encompassing a wide variety of shading scenarios. The database is intended to predict shading losses in crystalline silicon PV arrays and is accessed using basic inputs generally available in any PV simulation tool. Performance predictions using the database are within 1-2% of measured data for several partially shaded PV systems, and within 1% of those predicted by the full, detailed simulation tool on an annual basis. The shade loss database shows potential to considerably improve performance prediction for partially shaded PV systems.
Effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit
Peng Xi; Yan Li; Xiaojin Ge; Dandan Liu; Mingsan Miao
2018-01-01
Objective: Observing the effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit. Method: We prepared boiling water scalded rabbits with deep II degree scald models and applied high, medium and low doses of nano-silver hydrogel coating film for different time and area. Then we compared the difference of burned paper weight before administration and after administration model burns, burn local skin irritation points infection, skin crusting and scabs from th...
Low order physical models of vertical axis wind turbines
Craig, Anna; Dabiri, John; Koseff, Jeffrey
2016-11-01
In order to examine the ability of low-order physical models of vertical axis wind turbines to accurately reproduce key flow characteristics, experiments were conducted on rotating turbine models, rotating solid cylinders, and stationary porous flat plates (of both uniform and non-uniform porosities). From examination of the patterns of mean flow, the wake turbulence spectra, and several quantitative metrics, it was concluded that the rotating cylinders represent a reasonably accurate analog for the rotating turbines. In contrast, from examination of the patterns of mean flow, it was found that the porous flat plates represent only a limited analog for rotating turbines (for the parameters examined). These findings have implications for both laboratory experiments and numerical simulations, which have previously used analogous low order models in order to reduce experimental/computational costs. NSF GRF and SGF to A.C; ONR N000141211047 and the Gordon and Betty Moore Foundation Grant GBMF2645 to J.D.; and the Bob and Norma Street Environmental Fluid Mechanics Laboratory at Stanford University.
Aeroelastic simulation using CFD based reduced order models
International Nuclear Information System (INIS)
Zhang, W.; Ye, Z.; Li, H.; Yang, Q.
2005-01-01
This paper aims at providing an accurate and efficient method for aeroelastic simulation. System identification is used to get the reduced order models of unsteady aerodynamics. Unsteady Euler codes are used to compute the output signals while 3211 multistep input signals are utilized. LS(Least Squares) method is used to estimate the coefficients of the input-output difference model. The reduced order models are then used in place of the unsteady CFD code for aeroelastic simulation. The aeroelastic equations are marched by an improved 4th order Runge-Kutta method that only needs to compute the aerodynamic loads one time at every time step. The computed results agree well with that of the direct coupling CFD/CSD methods. The computational efficiency is improved 1∼2 orders while still retaining the high accuracy. A standard aeroelastic computing example (isogai wing) with S type flutter boundary is computed and analyzed. It is due to the system has more than one neutral points at the Mach range of 0.875∼0.9. (author)
Deletion of the App-Runx1 region in mice models human partial monosomy 21.
Arbogast, Thomas; Raveau, Matthieu; Chevalier, Claire; Nalesso, Valérie; Dembele, Doulaye; Jacobs, Hugues; Wendling, Olivia; Roux, Michel; Duchon, Arnaud; Herault, Yann
2015-06-01
Partial monosomy 21 (PM21) is a rare chromosomal abnormality that is characterized by the loss of a variable segment along human chromosome 21 (Hsa21). The clinical phenotypes of this loss are heterogeneous and range from mild alterations to lethal consequences, depending on the affected region of Hsa21. The most common features include intellectual disabilities, craniofacial dysmorphology, short stature, and muscular and cardiac defects. As a complement to human genetic approaches, our team has developed new monosomic mouse models that carry deletions on Hsa21 syntenic regions in order to identify the dosage-sensitive genes that are responsible for the symptoms. We focus here on the Ms5Yah mouse model, in which a 7.7-Mb region has been deleted from the App to Runx1 genes. Ms5Yah mice display high postnatal lethality, with a few surviving individuals showing growth retardation, motor coordination deficits, and spatial learning and memory impairments. Further studies confirmed a gene dosage effect in the Ms5Yah hippocampus, and pinpointed disruptions of pathways related to cell adhesion (involving App, Cntnap5b, Lgals3bp, Mag, Mcam, Npnt, Pcdhb2, Pcdhb3, Pcdhb4, Pcdhb6, Pcdhb7, Pcdhb8, Pcdhb16 and Vwf). Our PM21 mouse model is the first to display morphological abnormalities and behavioural phenotypes similar to those found in affected humans, and it therefore demonstrates the major contribution that the App-Runx1 region has in the pathophysiology of PM21. © 2015. Published by The Company of Biologists Ltd.
Anisotropic Third-Order Regularization for Sparse Digital Elevation Models
Lellmann, Jan
2013-01-01
We consider the problem of interpolating a surface based on sparse data such as individual points or level lines. We derive interpolators satisfying a list of desirable properties with an emphasis on preserving the geometry and characteristic features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data. © 2013 Springer-Verlag.
International Nuclear Information System (INIS)
Fakhar, K.; Kara, A. H.
2012-01-01
We study the symmetries, conservation laws and reduction of third-order equations that evolve from a prior reduction of models that arise in fluid phenomena. These could be the ordinary differential equations (ODEs) that are reductions of partial differential equations (PDEs) or, alternatively, PDEs related to given ODEs. In this class, the analysis includes the well-known Blasius, Chazy, and other associated third-order ODEs. (general)
Modelling the cooling and partial dismantling of the Febex in-situ test
International Nuclear Information System (INIS)
Sanchez, M.; Gens, A.; Guimaraes, L.
2010-01-01
predictions from analysis. The operation related to the partial dismantling included the demolition of the concrete plug and the removal of the sections of the barrier corresponding to 'Heater 1'. The objective was to carry out the partial dismantling causing minimum disturbance to the sections of test corresponding to the second heater, which remained in operation at all times. A new concrete plug was constructed immediately after excavation. A detailed description of the work performed during the partial dismantling of the in-situ test can be found in Huertas et al. (2006). This contribution focuses on the modelling of the cooling and partly dismantling of the FEBEX in-situ experiment. The finite element computer program CODE-BRIGHT has been used for the numerical analysis. CODE-BRIGHT is a program developed to handle coupled Thermo-Hydro- Mechanical and Geochemical problems in geological media. It has been observed a very good performance of the model to reproduce the evolution of the main THM variables of the tests, during the cooling of the Heater No.1, concrete demolition and excavation of the clay barrier. It is worth mentioning that these are a kind of 'blind model predictions', as the constitutive laws and model parameters adopted at the beginning of the heating were used in this analysis. (authors)
The lattice Boltzmann model for the second-order Benjamin–Ono equations
International Nuclear Information System (INIS)
Lai, Huilin; Ma, Changfeng
2010-01-01
In this paper, in order to extend the lattice Boltzmann method to deal with more complicated nonlinear equations, we propose a 1D lattice Boltzmann scheme with an amending function for the second-order (1 + 1)-dimensional Benjamin–Ono equation. With the Taylor expansion and the Chapman–Enskog expansion, the governing evolution equation is recovered correctly from the continuous Boltzmann equation. The equilibrium distribution function and the amending function are obtained. Numerical simulations are carried out for the 'good' Boussinesq equation and the 'bad' one to validate the proposed model. It is found that the numerical results agree well with the analytical solutions. The present model can be used to solve more kinds of nonlinear partial differential equations
Skew-t partially linear mixed-effects models for AIDS clinical studies.
Lu, Tao
2016-01-01
We propose partially linear mixed-effects models with asymmetry and missingness to investigate the relationship between two biomarkers in clinical studies. The proposed models take into account irregular time effects commonly observed in clinical studies under a semiparametric model framework. In addition, commonly assumed symmetric distributions for model errors are substituted by asymmetric distribution to account for skewness. Further, informative missing data mechanism is accounted for. A Bayesian approach is developed to perform parameter estimation simultaneously. The proposed model and method are applied to an AIDS dataset and comparisons with alternative models are performed.
Implementing The Automated Phases Of The Partially-Automated Digital Triage Process Model
Directory of Open Access Journals (Sweden)
Gary D Cantrell
2012-12-01
Full Text Available Digital triage is a pre-digital-forensic phase that sometimes takes place as a way of gathering quick intelligence. Although effort has been undertaken to model the digital forensics process, little has been done to date to model digital triage. This work discuses the further development of a model that does attempt to address digital triage the Partially-automated Crime Specific Digital Triage Process model. The model itself will be presented along with a description of how its automated functionality was implemented to facilitate model testing.
Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations
Mitry, Mina
Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.
Identification of the reduced order models of a BWR reactor
International Nuclear Information System (INIS)
Hernandez S, A.
2004-01-01
The present work has as objective to analyze the relative stability of a BWR type reactor. It is analyzed that so adaptive it turns out to identify the parameters of a model of reduced order so that this it reproduces a condition of given uncertainty. This will take of a real fact happened in the La Salle plant under certain operation conditions of power and flow of coolant. The parametric identification is carried out by means of an algorithm of recursive least square and an Output Error model (Output Error), measuring the output power of the reactor when the instability is present, and considering that it is produced by a change in the reactivity of the system in the same way that a sign of type step. Also it is carried out an analytic comparison of the relative stability, analyzing two types of answers: the original answer of the uncertainty of the reactor vs. the obtained response identifying the parameters of the model of reduced order, reaching the conclusion that it is very viable to adapt a model of reduced order to study the stability of a reactor, under the only condition to consider that the dynamics of the reactivity is of step type. (Author)
Advanced Fluid Reduced Order Models for Compressible Flow.
Energy Technology Data Exchange (ETDEWEB)
Tezaur, Irina Kalashnikova [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Fike, Jeffrey A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Barone, Matthew F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Maddix, Danielle [Stanford Univ., CA (United States); Mussoni, Erin E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Balajewicz, Maciej [Univ. of Illinois, Urbana-Champaign, IL (United States)
2017-09-01
This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly the POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.
Spatially explicit models for inference about density in unmarked or partially marked populations
Chandler, Richard B.; Royle, J. Andrew
2013-01-01
Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating
Modeling the self-assembly of ordered nanoporous materials
Energy Technology Data Exchange (ETDEWEB)
Monson, Peter [Univ. of Massachusetts, Amherst, MA (United States); Auerbach, Scott [Univ. of Massachusetts, Amherst, MA (United States)
2017-11-13
This report describes progress on a collaborative project on the multiscale modeling of the assembly processes in the synthesis of nanoporous materials. Such materials are of enormous importance in modern technology with application in the chemical process industries, biomedicine and biotechnology as well as microelectronics. The project focuses on two important classes of materials: i) microporous crystalline materials, such as zeolites, and ii) ordered mesoporous materials. In the first case the pores are part of the crystalline structure, while in the second the structures are amorphous on the atomistic length scale but where surfactant templating gives rise to order on the length scale of 2 - 20 nm. We have developed a modeling framework that encompasses both these kinds of materials. Our models focus on the assembly of corner sharing silica tetrahedra in the presence of structure directing agents. We emphasize a balance between sufficient realism in the models and computational tractibility given the complex many-body phenomena. We use both on-lattice and off-lattice models and the primary computational tools are Monte Carlo simulations with sampling techniques and ensembles appropriate to specific situations. Our modeling approach is the first to capture silica polymerization, nanopore crystallization, and mesopore formation through computer-simulated self assembly.
Inference in partially identified models with many moment inequalities using Lasso
DEFF Research Database (Denmark)
Bugni, Federico A.; Caner, Mehmet; Kock, Anders Bredahl
This paper considers the problem of inference in a partially identified moment (in)equality model with possibly many moment inequalities. Our contribution is to propose a novel two-step new inference method based on the combination of two ideas. On the one hand, our test statistic and critical...
Gomez, Rapson
2012-01-01
Objective: Generalized partial credit model, which is based on item response theory (IRT), was used to test differential item functioning (DIF) for the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed.), inattention (IA), and hyperactivity/impulsivity (HI) symptoms across boys and girls. Method: To accomplish this, parents completed…
New model reduction technique for a class of parabolic partial differential equations
Vajta, Miklos
1991-01-01
A model reduction (or lumping) technique for a class of parabolic-type partial differential equations is given, and its application is discussed. The frequency response of the temperature distribution in any multilayer solid is developed and given by a matrix expression. The distributed transfer
Penfield, Randall D.; Bergeron, Jennifer M.
2005-01-01
This article applies a weighted maximum likelihood (WML) latent trait estimator to the generalized partial credit model (GPCM). The relevant equations required to obtain the WML estimator using the Newton-Raphson algorithm are presented, and a simulation study is described that compared the properties of the WML estimator to those of the maximum…
On the Existence and Uniqueness of JML Estimates for the Partial Credit Model
Bertoli-Barsotti, Lucio
2005-01-01
A necessary and sufficient condition is given in this paper for the existence and uniqueness of the maximum likelihood (the so-called joint maximum likelihood) estimate of the parameters of the Partial Credit Model. This condition is stated in terms of a structural property of the pattern of the data matrix that can be easily verified on the basis…
Davis, Laurie Laughlin
2004-01-01
Choosing a strategy for controlling item exposure has become an integral part of test development for computerized adaptive testing (CAT). This study investigated the performance of six procedures for controlling item exposure in a series of simulated CATs under the generalized partial credit model. In addition to a no-exposure control baseline…
Roberts, James S.; Bao, Han; Huang, Chun-Wei; Gagne, Phill
Characteristic curve approaches for linking parameters from the generalized partial credit model were examined for cases in which common (anchor) items are calibrated separately in two groups. Three of these approaches are simple extensions of the test characteristic curve (TCC), item characteristic curve (ICC), and operating characteristic curve…
de Peinder, P.; Visser, T.; Wagemans, R.W.P.; Blomberg, J.; Chaabani, H.; Soulimani, F.; Weckhuysen, B.M.
2013-01-01
Research has been carried out to determine the feasibility of partial least-squares regression (PLS) modeling of infrared (IR) spectra of crude oils as a tool for fast sulfur speciation. The study is a continuation of a previously developed method to predict long and short residue properties of
HOKF: High Order Kalman Filter for Epilepsy Forecasting Modeling.
Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee
2017-08-01
Epilepsy forecasting has been extensively studied using high-order time series obtained from scalp-recorded electroencephalography (EEG). An accurate seizure prediction system would not only help significantly improve patients' quality of life, but would also facilitate new therapeutic strategies to manage epilepsy. This paper thus proposes an improved Kalman Filter (KF) algorithm to mine seizure forecasts from neural activity by modeling three properties in the high-order EEG time series: noise, temporal smoothness, and tensor structure. The proposed High-Order Kalman Filter (HOKF) is an extension of the standard Kalman filter, for which higher-order modeling is limited. The efficient dynamic of HOKF system preserves the tensor structure of the observations and latent states. As such, the proposed method offers two main advantages: (i) effectiveness with HOKF results in hidden variables that capture major evolving trends suitable to predict neural activity, even in the presence of missing values; and (ii) scalability in that the wall clock time of the HOKF is linear with respect to the number of time-slices of the sequence. The HOKF algorithm is examined in terms of its effectiveness and scalability by conducting forecasting and scalability experiments with a real epilepsy EEG dataset. The results of the simulation demonstrate the superiority of the proposed method over the original Kalman Filter and other existing methods. Copyright © 2017 Elsevier B.V. All rights reserved.
Fundamental Frequency and Model Order Estimation Using Spatial Filtering
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
extend this procedure to account for inharmonicity using unconstrained model order estimation. The simulations show that beamforming improves the performance of the joint estimates of fundamental frequency and the number of harmonics in low signal to interference (SIR) levels, and an experiment......In signal processing applications of harmonic-structured signals, estimates of the fundamental frequency and number of harmonics are often necessary. In real scenarios, a desired signal is contaminated by different levels of noise and interferers, which complicate the estimation of the signal...... parameters. In this paper, we present an estimation procedure for harmonic-structured signals in situations with strong interference using spatial filtering, or beamforming. We jointly estimate the fundamental frequency and the constrained model order through the output of the beamformers. Besides that, we...
Reduced order modeling in topology optimization of vibroacoustic problems
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas
2017-01-01
complex 3D parts. The optimization process can therefore become highly time consuming due to the need to solve a large system of equations at each iteration. Projection-based parametric Model Order Reduction (pMOR) methods have successfully been applied for reducing the computational cost of material......There is an interest in introducing topology optimization techniques in the design process of structural-acoustic systems. In topology optimization, the design space must be finely meshed in order to obtain an accurate design, which results in large numbers of degrees of freedom when designing...... or size optimization in large vibroacoustic models; however, new challenges are encountered when dealing with topology optimization. Since a design parameter per element is considered, the total number of design variables becomes very large; this poses a challenge to most existing pMOR techniques, which...
Energy Technology Data Exchange (ETDEWEB)
Olsson, Anna
2011-07-01
The overall objective of the thesis is to analyse the procurement competition for forest resources in Sweden. The thesis consists of an introductory part and two self-contained papers. In paper I a translog cost function approach is used to analyse the factor substitution in the sawmill industry, the pulp and paper industry and the heating industry in Sweden over the period 1970 to 2008. The estimated parameters are used to calculate the Allen and Morishima elasticities of substitution as well as the price elasticities of input demand. The utilisation of forest resources in the energy sector has been increasing and this increase is believed to continue. The increase is, to a large extent, caused by economic policies introduced to reduce the emission of greenhouse gases. Such policies could lead to an increase in the procurement competition between the forest industries and the energy sector. The calculated substitution elasticities indicate that it is easier for the heating industry to substitutes between by-products and logging residues than it is for the pulp and paper industry to substitute between by-products and roundwood. This suggests that the pulp and paper industry could suffer from an increase in the procurement competition. However, overall the substitutions elasticities estimated in our study are relatively low. This indicates that substitution possibilities could be rather limited due to rigidities in input prices. This result suggests that competition of forest resources also might be relatively limited. In paper II a partial equilibrium model is constructed in order to asses the effects an increasing utilisation of forest resources in the energy sector. The increasing utilisation of forest fuel is, to a large extent, caused by economic policies introduced to reduce the emission of greenhouse gases. In countries where forests already are highly utilised such policies will lead to an increase in the procurement competition between the forest sector and
Multivariable robust adaptive controller using reduced-order model
Directory of Open Access Journals (Sweden)
Wei Wang
1990-04-01
Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.
Model predictive control based on reduced order models applied to belt conveyor system.
Chen, Wei; Li, Xin
2016-11-01
In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Finite temperature CPN-1 model and long range Neel order
International Nuclear Information System (INIS)
Ichinose, Ikuo; Yamamoto, Hisashi.
1989-09-01
We study in d space-dimensions the finite temperature behavior of long range Neel order (LRNO) in CP N-1 model as a low energy effective field theory of the antiferromagnetic Heisenberg model. For d≤1, or d≤2 at any nonzero temperature, LRNO disappears, in agreement with Mermin-Wagner-Coleman's theorem. For d=3 in the weak coupling region, LRNO exists below the critical temperature T N (Neel temperature). T N decreases as the interlayer coupling becomes relatively weak compared with that within Cu-O layers. (author)
The order of chaos on a Bianch IX cosmological model
Energy Technology Data Exchange (ETDEWEB)
Bugalho, H; da Silva, A R; Ramos, J S
1986-12-01
The purpose of this paper is to analyze the chaotic behavior that can arise on a type-IX cosmological model using methods from dynamic systems theory and symbolic dynamics. Specifically, instead of the Belinski-Khalatnikov-Lifschitz model, we use the iterates of a monotonously increasing map of the circle with a discontinuity, and for the Hamiltonian dynamics of Misner's Mixmaster model we introduce the iterates of a noninvertible map. An equivalence between these two models can easily be brought upon by translating them in symbolic dynamical terms. The resulting symbolic orbits can be inserted in an ordered tree structure set, and so we can present an effective counting and referentation of all period orbits.
International Nuclear Information System (INIS)
Wu, Yuqian; Zhang, Yixin; Wang, Qiu; Hu, Zhengda
2016-01-01
For Gaussian beams with three different partially coherent models, including Gaussian-Schell model (GSM), Laguerre-Gaussian Schell-model (LGSM) and Bessel-Gaussian Schell-model (BGSM) beams propagating through a biological turbulent tissue, the expression of the spatial coherence radius of a spherical wave propagating in a turbulent biological tissue, and the average intensity and beam spreading for GSM, LGSM and BGSM beams are derived based on the fractal model of power spectrum of refractive-index variations in biological tissue. Effects of partially coherent model and parameters of biological turbulence on such beams are studied in numerical simulations. Our results reveal that the spreading of GSM beams is smaller than LGSM and BGSM beams on the same conditions, and the beam with larger source coherence width has smaller beam spreading than that with smaller coherence width. The results are useful for any applications involved light beam propagation through tissues, especially the cases where the average intensity and spreading properties of the light should be taken into account to evaluate the system performance and investigations in the structures of biological tissue. - Highlights: • Spatial coherence radius of a spherical wave propagating in a turbulent biological tissue is developed. • Expressions of average intensity and beam spreading for GSM, LGSM and BGSM beams in a turbulent biological tissue are derived. • The contrast for the three partially coherent model beams is shown in numerical simulations. • The results are useful for any applications involved light beam propagation through tissues.
Rudge, J. F.; Alisic Jewell, L.; Rhebergen, S.; Katz, R. F.; Wells, G. N.
2015-12-01
One of the fundamental components in any dynamical model of melt transport is the rheology of partially molten rock. This rheology is poorly understood, and one way in which a better understanding can be obtained is by comparing the results of laboratory deformation experiments to numerical models. Here we present a comparison between numerical models and the laboratory setup of Qi et al. 2013 (EPSL), where a cylinder of partially molten rock containing rigid spherical inclusions was placed under torsion. We have replicated this setup in a finite element model which solves the partial differential equations describing the mechanical process of compaction. These computationally-demanding 3D simulations are only possible due to the recent development of a new preconditioning method for the equations of magma dynamics. The experiments show a distinct pattern of melt-rich and melt-depleted regions around the inclusions. In our numerical models, the pattern of melt varies with key rheological parameters, such as the ratio of bulk to shear viscosity, and the porosity- and strain-rate-dependence of the shear viscosity. These observed melt patterns therefore have the potential to constrain rheological properties. While there are many similarities between the experiments and the numerical models, there are also important differences, which highlight the need for better models of the physics of two-phase mantle/magma dynamics. In particular, the laboratory experiments display more pervasive melt-rich bands than is seen in our numerics.
Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.
Lin, Huiming; Fu, Bo; Qin, Guoyou; Zhu, Zhongyi
2017-12-01
We develop a doubly robust estimation of generalized partial linear models for longitudinal data with dropouts. Our method extends the highly efficient aggregate unbiased estimating function approach proposed in Qu et al. (2010) to a doubly robust one in the sense that under missing at random (MAR), our estimator is consistent when either the linear conditional mean condition is satisfied or a model for the dropout process is correctly specified. We begin with a generalized linear model for the marginal mean, and then move forward to a generalized partial linear model, allowing for nonparametric covariate effect by using the regression spline smoothing approximation. We establish the asymptotic theory for the proposed method and use simulation studies to compare its finite sample performance with that of Qu's method, the complete-case generalized estimating equation (GEE) and the inverse-probability weighted GEE. The proposed method is finally illustrated using data from a longitudinal cohort study. © 2017, The International Biometric Society.
A regional and nonstationary model for partial duration series of extreme rainfall
DEFF Research Database (Denmark)
Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan
2017-01-01
as the explanatory variables in the regional and temporal domain, respectively. Further analysis of partial duration series with nonstationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found...... of extreme rainfall. The framework is built on a partial duration series approach with a nonstationary, regional threshold value. The model is based on generalized linear regression solved by generalized estimation equations. It allows a spatial correlation between the stations in the network and accounts...... furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by generalized least squares are used to validate and discuss the results of the full spatiotemporal model. The model is applied on data from a large Danish rain gauge network...
Snodgrass, Michael; Kalaida, Natasha; Winer, E Samuel
2009-06-01
Access can either be first-order or second-order. First order access concerns whether contents achieve representation in phenomenal consciousness at all; second-order access concerns whether phenomenally conscious contents are selected for metacognitive, higher order processing by reflective consciousness. When the optional and flexible nature of second-order access is kept in mind, there remain strong reasons to believe that exclusion failure can indeed isolate phenomenally conscious stimuli that are not so accessed. Irvine's [Irvine, E. (2009). Signal detection theory, the exclusion failure paradigm and weak consciousness-Evidence for the access/phenomenal distinction? Consciousness and Cognition.] partial access argument fails because exclusion failure is indeed due to lack of second-order access, not insufficient phenomenally conscious information. Further, the enable account conforms with both qualitative differences and subjective report, and is simpler than the endow account. Finally, although first-order access may be a distinct and important process, second-order access arguably reflects the core meaning of access generally.
International Nuclear Information System (INIS)
Pabst, R.; Binns, R.M.
1986-01-01
Normal young piglets and miniature piglets of the Gottingen breed were used as animal models for autotransplantation of splenic fragments. In pigs, regeneration kinetics seem to be comparable to man. Even after six mo, only small splenic nodules with a reduced blood flow were found. No effective stimulator of splenic regeneration has been found for pigs. Pig spleen size and blood supply enable partial splenectomies and ligation of the splenic artery which are models for spleen surgery in man
A partially ionized plasma modeling; Un modele de plasma partiellement ionise
Energy Technology Data Exchange (ETDEWEB)
Le Thanh, K.C.; Raviart, P.A
2003-07-01
We propose a model for the partially ionized plasma sheaths near the anode of an anodic spot electric arc where the cathode is considered as an electron emitter. A fluid description takes into account the heating and the ionization of the plasma induced by the electron beam. As physical hypothesis we assume that the condition of charge neutrality is valid. According that the electron mass can be neglected compared to the ion mass, we can assume that ions and atoms have the same velocity and the same temperature. Electrons and heavy particles are then regarded as two separate fluids coexisting in the plasma. Governing equations are then multi-fluid equations with relaxation correction to the local thermodynamic equilibrium (LTE) and heating by Joule effect. Equations are solved by an operator splitting procedure. That is we first discretize the homogeneous conservation laws (i.e. without source terms) by a finite volume method. The second step is to solve the ordinary differential system (i.e, governing equation without transport terms) with an implicit scheme. (authors)
Cobben, Marleen M P; van Noordwijk, Arie J
2017-10-01
Migration is a widespread phenomenon across the animal kingdom as a response to seasonality in environmental conditions. Partially migratory populations are populations that consist of both migratory and residential individuals. Such populations are very common, yet their stability has long been debated. The inheritance of migratory activity is currently best described by the threshold model of quantitative genetics. The inclusion of such a genetic threshold model for migratory behavior leads to a stable zone in time and space of partially migratory populations under a wide range of demographic parameter values, when assuming stable environmental conditions and unlimited genetic diversity. Migratory species are expected to be particularly sensitive to global warming, as arrival at the breeding grounds might be increasingly mistimed as a result of the uncoupling of long-used cues and actual environmental conditions, with decreasing reproduction as a consequence. Here, we investigate the consequences for migratory behavior and the stability of partially migratory populations under five climate change scenarios and the assumption of a genetic threshold value for migratory behavior in an individual-based model. The results show a spatially and temporally stable zone of partially migratory populations after different lengths of time in all scenarios. In the scenarios in which the species expands its range from a particular set of starting populations, the genetic diversity and location at initialization determine the species' colonization speed across the zone of partial migration and therefore across the entire landscape. Abruptly changing environmental conditions after model initialization never caused a qualitative change in phenotype distributions, or complete extinction. This suggests that climate change-induced shifts in species' ranges as well as changes in survival probabilities and reproductive success can be met with flexibility in migratory behavior at the
Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C
2011-10-31
The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain
An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions
Energy Technology Data Exchange (ETDEWEB)
Oña, J. de; Oña, R. de; Eboli, L.; Forciniti, C.; Mazzulla, G.
2016-07-01
Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future. (Author)
Competing orders in the Hofstadter t -J model
Tu, Wei-Lin; Schindler, Frank; Neupert, Titus; Poilblanc, Didier
2018-01-01
The Hofstadter model describes noninteracting fermions on a lattice in the presence of an external magnetic field. Motivated by the plethora of solid-state phases emerging from electron interactions, we consider an interacting version of the Hofstadter model, including a Hubbard repulsion U . We investigate this model in the large-U limit corresponding to a t -J Hamiltonian with an external (orbital) magnetic field. By using renormalized mean-field theory supplemented by exact diagonalization calculations of small clusters, we find evidence for competing symmetry-breaking phases, exhibiting (possibly coexisting) charge, bond, and superconducting orders. Topological properties of the states are also investigated, and some of our results are compared to related experiments involving ultracold atoms loaded on optical lattices in the presence of a synthetic gauge field.
Twisted quantum double model of topological order with boundaries
Bullivant, Alex; Hu, Yuting; Wan, Yidun
2017-10-01
We generalize the twisted quantum double model of topological orders in two dimensions to the case with boundaries by systematically constructing the boundary Hamiltonians. Given the bulk Hamiltonian defined by a gauge group G and a 3-cocycle in the third cohomology group of G over U (1 ) , a boundary Hamiltonian can be defined by a subgroup K of G and a 2-cochain in the second cochain group of K over U (1 ) . The consistency between the bulk and boundary Hamiltonians is dictated by what we call the Frobenius condition that constrains the 2-cochain given the 3-cocyle. We offer a closed-form formula computing the ground-state degeneracy of the model on a cylinder in terms of the input data only, which can be naturally generalized to surfaces with more boundaries. We also explicitly write down the ground-state wave function of the model on a disk also in terms of the input data only.
Topological order in an exactly solvable 3D spin model
International Nuclear Information System (INIS)
Bravyi, Sergey; Leemhuis, Bernhard; Terhal, Barbara M.
2011-01-01
Research highlights: RHtriangle We study exactly solvable spin model with six-qubit nearest neighbor interactions on a 3D face centered cubic lattice. RHtriangle The ground space of the model exhibits topological quantum order. RHtriangle Elementary excitations can be geometrically described as the corners of rectangular-shaped membranes. RHtriangle The ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. RHtriangle Logical operators acting on the encoded qubits are described in terms of closed strings and closed membranes. - Abstract: We study a 3D generalization of the toric code model introduced recently by Chamon. This is an exactly solvable spin model with six-qubit nearest-neighbor interactions on an FCC lattice whose ground space exhibits topological quantum order. The elementary excitations of this model which we call monopoles can be geometrically described as the corners of rectangular-shaped membranes. We prove that the creation of an isolated monopole separated from other monopoles by a distance R requires an operator acting on Ω(R 2 ) qubits. Composite particles that consist of two monopoles (dipoles) and four monopoles (quadrupoles) can be described as end-points of strings. The peculiar feature of the model is that dipole-type strings are rigid, that is, such strings must be aligned with face-diagonals of the lattice. For periodic boundary conditions the ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. We describe a complete set of logical operators acting on the encoded qubits in terms of closed strings and closed membranes.
A genetic model of progressively partial melting for uranium-bearing granites in south China
International Nuclear Information System (INIS)
Zhai Jianping.
1989-01-01
A genetic model of progressively partial and enrichment mechanism of uranium during partial melting of the sources of material studied and the significance of the genetic model in search of uranium deposits is elaborated. This model accounts better for some geological and geochemical features of uranium-bearing granties and suspects the traditional idea that igneous uranium-bearing granites were formed by fusion of U-rich strata surrounding these granites. Finally this paper points out that the infuence of U-rich strata of wall rocks of granites over uranium-bearing granites depends on variation of water solubility in the magma and assimilation of magma to wall rocks during its ascending and crystallization
DEFF Research Database (Denmark)
Madsen, Henrik; Rasmussen, Peter F.; Rosbjerg, Dan
1997-01-01
Two different models for analyzing extreme hydrologic events, based on, respectively, partial duration series (PDS) and annual maximum series (AMS), are compared. The PDS model assumes a generalized Pareto distribution for modeling threshold exceedances corresponding to a generalized extreme value......). In the case of ML estimation, the PDS model provides the most efficient T-year event estimator. In the cases of MOM and PWM estimation, the PDS model is generally preferable for negative shape parameters, whereas the AMS model yields the most efficient estimator for positive shape parameters. A comparison...... of the considered methods reveals that in general, one should use the PDS model with MOM estimation for negative shape parameters, the PDS model with exponentially distributed exceedances if the shape parameter is close to zero, the AMS model with MOM estimation for moderately positive shape parameters, and the PDS...
Kitta, Takeya; Kanno, Yukiko; Chiba, Hiroki; Higuchi, Madoka; Ouchi, Mifuka; Togo, Mio; Moriya, Kimihiko; Shinohara, Nobuo
2018-01-01
The functions of the lower urinary tract have been investigated for more than a century. Lower urinary tract symptoms, such as incomplete bladder emptying, weak urine stream, daytime urinary frequency, urgency, urge incontinence and nocturia after partial bladder outlet obstruction, is a frequent cause of benign prostatic hyperplasia in aging men. However, the pathophysiological mechanisms have not been fully elucidated. The use of animal models is absolutely imperative for understanding the pathophysiological processes involved in bladder dysfunction. Surgical induction has been used to study lower urinary tract functions of numerous animal species, such as pig, dog, rabbit, guinea pig, rat and mouse, of both sexes. Several morphological and functional modifications under partial bladder outlet obstruction have not only been observed in the bladder, but also in the central nervous system. Understanding the changes of the lower urinary tract functions induced by partial bladder outlet obstruction would also contribute to appropriate drug development for treating these pathophysiological conditions. In the present review, we discuss techniques for creating partial bladder outlet obstruction, the characteristics of several species, as well as issues of each model, and their translational value. © 2017 The Japanese Urological Association.
Directory of Open Access Journals (Sweden)
Jafari Peyman
2012-10-01
Full Text Available Abstract Background The purpose of the study was to determine whether the Persian version of the KIDSCREEN-27 has the optimal number of response category to measure health-related quality of life (HRQoL in children and adolescents. Moreover, we aimed to determine if all the items contributed adequately to their own domain. Findings The Persian version of the KIDSCREEN-27 was completed by 1083 school children and 1070 of their parents. The Rasch partial credit model (PCM was used to investigate item statistics and ordering of response categories. The PCM showed that no item was misfitting. The PCM also revealed that, successive response categories for all items were located in the expected order except for category 1 in self- and proxy-reports. Conclusions Although Rasch analysis confirms that all the items belong to their own underlying construct, response categories should be reorganized and evaluated in further studies, especially in children with chronic conditions.
Temporal aggregation in first order cointegrated vector autoregressive models
DEFF Research Database (Denmark)
La Cour, Lisbeth Funding; Milhøj, Anders
We study aggregation - or sample frequencies - of time series, e.g. aggregation from weekly to monthly or quarterly time series. Aggregation usually gives shorter time series but spurious phenomena, in e.g. daily observations, can on the other hand be avoided. An important issue is the effect of ...... of aggregation on the adjustment coefficient in cointegrated systems. We study only first order vector autoregressive processes for n dimensional time series Xt, and we illustrate the theory by a two dimensional and a four dimensional model for prices of various grades of gasoline...
Lu, Tao; Lu, Minggen; Wang, Min; Zhang, Jun; Dong, Guang-Hui; Xu, Yong
2017-12-18
Longitudinal competing risks data frequently arise in clinical studies. Skewness and missingness are commonly observed for these data in practice. However, most joint models do not account for these data features. In this article, we propose partially linear mixed-effects joint models to analyze skew longitudinal competing risks data with missingness. In particular, to account for skewness, we replace the commonly assumed symmetric distributions by asymmetric distribution for model errors. To deal with missingness, we employ an informative missing data model. The joint models that couple the partially linear mixed-effects model for the longitudinal process, the cause-specific proportional hazard model for competing risks process and missing data process are developed. To estimate the parameters in the joint models, we propose a fully Bayesian approach based on the joint likelihood. To illustrate the proposed model and method, we implement them to an AIDS clinical study. Some interesting findings are reported. We also conduct simulation studies to validate the proposed method.
Chick embryo partial ischemia model: a new approach to study ischemia ex vivo.
Directory of Open Access Journals (Sweden)
Syamantak Majumder
Full Text Available BACKGROUND: Ischemia is a pathophysiological condition due to blockade in blood supply to a specific tissue thus damaging the physiological activity of the tissue. Different in vivo models are presently available to study ischemia in heart and other tissues. However, no ex vivo ischemia model has been available to date for routine ischemia research and for faster screening of anti-ischemia drugs. In the present study, we took the opportunity to develop an ex vivo model of partial ischemia using the vascular bed of 4(th day incubated chick embryo. METHODOLOGY/PRINCIPAL FINDINGS: Ischemia was created in chick embryo by ligating the right vitelline artery using sterile surgical suture. Hypoxia inducible factor- 1 alpha (HIF-1alpha, creatine phospho kinase-MB and reactive oxygen species in animal tissues and cells were measured to confirm ischemia in chick embryo. Additionally, ranolazine, N-acetyl cysteine and trimetazidine were administered as an anti-ischemic drug to validate the present model. Results from the present study depicted that blocking blood flow elevates HIF-1alpha, lipid peroxidation, peroxynitrite level in ischemic vessels while ranolazine administration partially attenuates ischemia driven HIF-1alpha expression. Endothelial cell incubated on ischemic blood vessels elucidated a higher level of HIF-1alpha expression with time while ranolazine treatment reduced HIF-1alpha in ischemic cells. Incubation of caprine heart strip on chick embryo ischemia model depicted an elevated creatine phospho kinase-MB activity under ischemic condition while histology of the treated heart sections evoked edema and disruption of myofibril structures. CONCLUSIONS/SIGNIFICANCE: The present study concluded that chick embryo partial ischemia model can be used as a novel ex vivo model of ischemia. Therefore, the present model can be used parallel with the known in vivo ischemia models in understanding the mechanistic insight of ischemia development and in
Antiferromagnetic order in the Hubbard model on the Penrose lattice
Koga, Akihisa; Tsunetsugu, Hirokazu
2017-12-01
We study an antiferromagnetic order in the ground state of the half-filled Hubbard model on the Penrose lattice and investigate the effects of quasiperiodic lattice structure. In the limit of infinitesimal Coulomb repulsion U →+0 , the staggered magnetizations persist to be finite, and their values are determined by confined states, which are strictly localized with thermodynamics degeneracy. The magnetizations exhibit an exotic spatial pattern, and have the same sign in each of cluster regions, the size of which ranges from 31 sites to infinity. With increasing U , they continuously evolve to those of the corresponding spin model in the U =∞ limit. In both limits of U , local magnetizations exhibit a fairly intricate spatial pattern that reflects the quasiperiodic structure, but the pattern differs between the two limits. We have analyzed this pattern change by a mode analysis by the singular value decomposition method for the fractal-like magnetization pattern projected into the perpendicular space.
Venus spherical harmonic gravity model to degree and order 60
Konopliv, Alex S.; Sjogren, William L.
1994-01-01
The Magellan and Pioneer Venus Orbiter radiometric tracking data sets have been combined to produce a 60th degree and order spherical harmonic gravity field. The Magellan data include the high-precision X-band gravity tracking from September 1992 to May 1993 and post-aerobraking data up to January 5, 1994. Gravity models are presented from the application of Kaula's power rule for Venus and an alternative a priori method using surface accelerations. Results are given as vertical gravity acceleration at the reference surface, geoid, vertical Bouguer, and vertical isostatic maps with errors for the vertical gravity and geoid maps included. Correlation of the gravity with topography for the different models is also discussed.
Ordered LOGIT Model approach for the determination of financial distress.
Kinay, B
2010-01-01
Nowadays, as a result of the global competition encountered, numerous companies come up against financial distresses. To predict and take proactive approaches for those problems is quite important. Thus, the prediction of crisis and financial distress is essential in terms of revealing the financial condition of companies. In this study, financial ratios relating to 156 industrial firms that are quoted in the Istanbul Stock Exchange are used and probabilities of financial distress are predicted by means of an ordered logit regression model. By means of Altman's Z Score, the dependent variable is composed by scaling the level of risk. Thus, a model that can compose an early warning system and predict financial distress is proposed.
Pairing of parafermions of order 2: seniority model
International Nuclear Information System (INIS)
Nelson, Charles A
2004-01-01
As generalizations of the fermion seniority model, four multi-mode Hamiltonians are considered to investigate some of the consequences of the pairing of parafermions of order 2. Two- and four-particle states are explicitly constructed for H A ≡ -GA†A with A† ≡ 1/2 Σ m>0 c† m c† -m and the distinct H C ≡ -GC†C with C† ≡ 1/2 Σ m>0 c† -m c† m , and for the time-reversal invariant H (-) ≡ -G(A† - C†)(A - C) and H (+) ≡ -G(A† + C†)(A + C), which has no analogue in the fermion case. The spectra and degeneracies are compared with those of the usual fermion seniority model
Quantifying and modeling birth order effects in autism.
Directory of Open Access Journals (Sweden)
Tychele Turner
Full Text Available Autism is a complex genetic disorder with multiple etiologies whose molecular genetic basis is not fully understood. Although a number of rare mutations and dosage abnormalities are specific to autism, these explain no more than 10% of all cases. The high heritability of autism and low recurrence risk suggests multifactorial inheritance from numerous loci but other factors also intervene to modulate risk. In this study, we examine the effect of birth rank on disease risk which is not expected for purely hereditary genetic models. We analyzed the data from three publicly available autism family collections in the USA for potential birth order effects and studied the statistical properties of three tests to show that adequate power to detect these effects exist. We detect statistically significant, yet varying, patterns of birth order effects across these collections. In multiplex families, we identify V-shaped effects where middle births are at high risk; in simplex families, we demonstrate linear effects where risk increases with each additional birth. Moreover, the birth order effect is gender-dependent in the simplex collection. It is currently unknown whether these patterns arise from ascertainment biases or biological factors. Nevertheless, further investigation of parental age-dependent risks yields patterns similar to those observed and could potentially explain part of the increased risk. A search for genes considering these patterns is likely to increase statistical power and uncover novel molecular etiologies.
International Nuclear Information System (INIS)
Lin-Jie, Chen; Chang-Feng, Ma
2010-01-01
This paper proposes a lattice Boltzmann model with an amending function for one-dimensional nonlinear partial differential equations (NPDEs) in the form u t + αuu x + βu n u x + γu xx + δu xxx + ζu xxxx = 0. This model is different from existing models because it lets the time step be equivalent to the square of the space step and derives higher accuracy and nonlinear terms in NPDEs. With the Chapman–Enskog expansion, the governing evolution equation is recovered correctly from the continuous Boltzmann equation. The numerical results agree well with the analytical solutions. (general)
Modeling of a partially debonded piezoelectric actuator in smart composite laminates
International Nuclear Information System (INIS)
Huang, Bin; Soo Kim, Heung; Ho Yoon, Gil
2015-01-01
A partially debonded piezoelectric actuator in smart composite laminates was modeled using an improved layerwise displacement field and Heaviside unit step functions. The finite element method with four node plate element and the extended Hamilton principle were used to derive the governing equation. The effects of actuator debonding on the smart composite laminate were investigated in both the frequency and time domains. The frequency and transient responses were obtained using the mode superposition method and the Newmark time integration algorithm, respectively. Two partial actuator debonding cases were studied to investigate the debonding effects on the actuation capability of the piezoelectric actuator. The effect of actuator debonding on the natural frequencies was subtler, but severe reductions of the actuation ability were observed in both the frequency and time responses, especially in the edge debonded actuator case. The results provided confirmation that the proposed modeling could be used in virtual experiments of actuator failure in smart composite laminates. (paper)
Dynamics and phenomenology of higher order gravity cosmological models
Moldenhauer, Jacob Andrew
2010-10-01
I present here some new results about a systematic approach to higher-order gravity (HOG) cosmological models. The HOG models are derived from curvature invariants that are more general than the Einstein-Hilbert action. Some of the models exhibit late-time cosmic acceleration without the need for dark energy and fit some current observations. The open question is that there are an infinite number of invariants that one could select, and many of the published papers have stressed the need to find a systematic approach that will allow one to study methodically the various possibilities. We explore a new connection that we made between theorems from the theory of invariants in general relativity and these cosmological models. In summary, the theorems demonstrate that curvature invariants are not all independent from each other and that for a given Ricci Segre type and Petrov type (symmetry classification) of the space-time, there exists a complete minimal set of independent invariants (a basis) in terms of which all the other invariants can be expressed. As an immediate consequence of the proposed approach, the number of invariants to consider is dramatically reduced from infinity to four invariants in the worst case and to only two invariants in the cases of interest, including all Friedmann-Lemaitre-Robertson-Walker metrics. We derive models that pass stability and physical acceptability conditions. We derive dynamical equations and phase portrait analyses that show the promise of the systematic approach. We consider observational constraints from magnitude-redshift Supernovae Type Ia data, distance to the last scattering surface of the Cosmic Microwave Background radiation, and Baryon Acoustic Oscillations. We put observational constraints on general HOG models. We constrain different forms of the Gauss-Bonnet, f(G), modified gravity models with these observations. We show some of these models pass solar system tests. We seek to find models that pass physical and
Roof planes detection via a second-order variational model
Benciolini, Battista; Ruggiero, Valeria; Vitti, Alfonso; Zanetti, Massimo
2018-04-01
The paper describes a unified automatic procedure for the detection of roof planes in gridded height data. The procedure exploits the Blake-Zisserman (BZ) model for segmentation in both 2D and 1D, and aims to detect, to model and to label roof planes. The BZ model relies on the minimization of a functional that depends on first- and second-order derivatives, free discontinuities and free gradient discontinuities. During the minimization, the relative strength of each competitor is controlled by a set of weight parameters. By finding the minimum of the approximated BZ functional, one obtains: (1) an approximation of the data that is smoothed solely within regions of homogeneous gradient, and (2) an explicit detection of the discontinuities and gradient discontinuities of the approximation. Firstly, input data is segmented using the 2D BZ. The maps of data and gradient discontinuities are used to isolate building candidates and planar patches (i.e. regions with homogeneous gradient) that correspond to roof planes. Connected regions that can not be considered as buildings are filtered according to both patch dimension and distribution of the directions of the normals to the boundary. The 1D BZ model is applied to the curvilinear coordinates of boundary points of building candidates in order to reduce the effect of data granularity when the normals are evaluated. In particular, corners are preserved and can be detected by means of gradient discontinuity. Lastly, a total least squares model is applied to estimate the parameters of the plane that best fits the points of each planar patch (orthogonal regression with planar model). Refinement of planar patches is performed by assigning those points that are close to the boundaries to the planar patch for which a given proximity measure assumes the smallest value. The proximity measure is defined to account for the variance of a fitting plane and a weighted distance of a point from the plane. The effectiveness of the
Mathematical Modeling of Partial-Porous Circular Cylinders with Water Waves
Directory of Open Access Journals (Sweden)
Min-Su Park
2015-01-01
Full Text Available The interaction of water waves with partially porous-surfaced circular cylinders was investigated. A three-dimensional numerical modeling was developed based on the complete mathematical formulation of the eigenfunction expansion method in the potential flow. Darcy’s law was applied to describe the porous boundary. The partial-porous cylinder is composed of a porous-surfaced body near the free surface, and an impermeable-surfaced body with an end-capped rigid bottom below the porous region. The optimal ratio of the porous portion to the impermeable portion can be adopted to design an effective ocean structure with minimal hydrodynamic impact. To scrutinize the hydrodynamic interactions in N partial-porous circular cylinders, the computational fluid domain is divided into three regions: an exterior region, N inner porous body regions, and N regions beneath the body. Wave excitation forces and wave run-up on multibodied partial-porous cylinders are calculated and compared for various porous-portion ratios and wave conditions, all of which significantly influence the hydrodynamic property.
Comparison of partial and complete arterial occlusion models for studying intestinal ischemia
International Nuclear Information System (INIS)
Parks, D.A.; Grogaard, B.; Granger, D.N.
1982-01-01
Mucosal albumin clearance was measured in jejunal segments of dogs under control conditions and following complete or partial arterial occlusion of varying durations (1, 2, 3, or 4 hours). The rate of albumin clearance was estimated from the luminal perfusion rate and the activity of protein bound 125 I in the perfusate and plasma. Partial and total arterial occlusions of 60 minutes to 4 hours' duration produced significant increases in mucosal albumin clearance. The magnitude of the rise in albumin clearance was directly related to the duration of ischemia in both total and partial arterial occlusion models. However, the magnitude of the increase in albumin clearance was significantly greater with total arterial occlusion for any given duration of ischemia. The albumin clearance results obtained in the present study compare favorably with previously reported morphologic changes in the intestinal mucosa produced by both total and partial occlusion of the superior mesenteric artery. The agreement between morphologic and physiologic measurements indicates that mucosal albumin clearance may be a useful tool for studying the pathophysiology of intestinal ischemia
Falk, Richard A.
The monograph examines the relationship of nuclear power to world order. The major purpose of the document is to stimulate research, education, dialogue, and political action for a just and peaceful world order. The document is presented in five chapters. Chapter I stresses the need for a system of global security to counteract dangers brought…
Energy Technology Data Exchange (ETDEWEB)
Pravinraj, T., E-mail: pravinraj1711@gmail.com; Patrikar, Rajendra
2017-07-01
Highlights: • A LBM model on partial wetting surface for droplet dynamics is presented by introducing a simple initial partial wetting boundary condition in SC model. • With our approach one can tune the splitting volume and time by carefully choosing strip width and position. • It is shown that the droplet spreading on chemically heterogeneous surfaces can be controlled not only by Weber number but also by tuning strip width ratio. • The directional transportation of a droplet due to chemical wetting gradient is simulated and analyzed using hybrid thermodynamic-image processing technique. • Microstructure surface and its influence on the directional wetting based transportation of droplet are demonstrated. - Abstract: Partial wetting surfaces and its influence on the droplet movement of micro and nano scale being contemplated for many useful applications. The dynamics of the droplet usually analyzed with a multiphase lattice Boltzmann method (LBM). In this paper, the influence of partial wetting surface on the dynamics of droplet is systematically analyzed for various cases. Splitting of droplets due to chemical gradient of the surface is studied and analyses of splitting time for various widths of the strips for different Weber numbers are computed. With the proposed model one can tune the splitting volume and time by carefully choosing a strip width and droplet position. The droplet spreading on chemically heterogeneous surfaces shows that the spreading can be controlled not only by parameters of Weber number but also by tuning strip width ratio. The transportation of the droplet from hydrophobic surface to hydrophilic surface due to chemical gradient is simulated and analyzed using our hybrid thermodynamic-image processing technique. The results prove that with the progress of time the surface free energy decreases with increase in spreading area. Finally, the transportation of a droplet on microstructure gradient is demonstrated. The model explains
A partial hearing animal model for chronic electro-acoustic stimulation
Irving, S.; Wise, A. K.; Millard, R. E.; Shepherd, R. K.; Fallon, J. B.
2014-08-01
Objective. Cochlear implants (CIs) have provided some auditory function to hundreds of thousands of people around the world. Although traditionally carried out only in profoundly deaf patients, the eligibility criteria for implantation have recently been relaxed to include many partially-deaf patients with useful levels of hearing. These patients receive both electrical stimulation from their implant and acoustic stimulation via their residual hearing (electro-acoustic stimulation; EAS) and perform very well. It is unclear how EAS improves speech perception over electrical stimulation alone, and little evidence exists about the nature of the interactions between electric and acoustic stimuli. Furthermore, clinical results suggest that some patients that undergo cochlear implantation lose some, if not all, of their residual hearing, reducing the advantages of EAS over electrical stimulation alone. A reliable animal model with clinically-relevant partial deafness combined with clinical CIs is important to enable these issues to be studied. This paper outlines such a model that has been successfully used in our laboratory. Approach. This paper outlines a battery of techniques used in our laboratory to generate, validate and examine an animal model of partial deafness and chronic CI use. Main results. Ototoxic deafening produced bilaterally symmetrical hearing thresholds in neonatal and adult animals. Electrical activation of the auditory system was confirmed, and all animals were chronically stimulated via adapted clinical CIs. Acoustic compound action potentials (CAPs) were obtained from partially-hearing cochleae, using the CI amplifier. Immunohistochemical analysis allows the effects of deafness and electrical stimulation on cell survival to be studied. Significance. This animal model has applications in EAS research, including investigating the functional interactions between electric and acoustic stimulation, and the development of techniques to maintain residual
The Dif Identification in Constructed Response Items Using Partial Credit Model
Heri Retnawati
2017-01-01
The study was to identify the load, the type and the significance of differential item functioning (DIF) in constructed response item using the partial credit model (PCM). The data in the study were the students’ instruments and the students’ responses toward the PISA-like test items that had been completed by 386 ninth grade students and 460 tenth grade students who had been about 15 years old in the Province of Yogyakarta Special Region in Indonesia. The analysis toward the item characteris...
POPE: Partial Order Preserving Encoding
2016-09-09
Girao, and M. Acharya. Concealed data aggregation for reverse multicast traffic in sensor networks : Encryption, key distribution, and routing adaptation...are common in “ big data ” applications while still maintain- ing search functionality and achieving stronger security. Specifi- cally, we propose a new...security and performance makes our scheme better suited for today’s insert-heavy databases. 1. INTRODUCTION Range queries over big data . A common
Control-oriented reduced order modeling of dipteran flapping flight
Faruque, Imraan
Flying insects achieve flight stabilization and control in a manner that requires only small, specialized neural structures to perform the essential components of sensing and feedback, achieving unparalleled levels of robust aerobatic flight on limited computational resources. An engineering mechanism to replicate these control strategies could provide a dramatic increase in the mobility of small scale aerial robotics, but a formal investigation has not yet yielded tools that both quantitatively and intuitively explain flapping wing flight as an "input-output" relationship. This work uses experimental and simulated measurements of insect flight to create reduced order flight dynamics models. The framework presented here creates models that are relevant for the study of control properties. The work begins with automated measurement of insect wing motions in free flight, which are then used to calculate flight forces via an empirically-derived aerodynamics model. When paired with rigid body dynamics and experimentally measured state feedback, both the bare airframe and closed loop systems may be analyzed using frequency domain system identification. Flight dynamics models describing maneuvering about hover and cruise conditions are presented for example fruit flies (Drosophila melanogaster) and blowflies (Calliphorids). The results show that biologically measured feedback paths are appropriate for flight stabilization and sexual dimorphism is only a minor factor in flight dynamics. A method of ranking kinematic control inputs to maximize maneuverability is also presented, showing that the volume of reachable configurations in state space can be dramatically increased due to appropriate choice of kinematic inputs.
Simulation of local instabilities with the use of reduced order models
International Nuclear Information System (INIS)
Dykin, V.; Demaziere, C.; Lange, C.; Hennig, D.
2011-01-01
The development of an advanced reduced order model (ROM) with four heated channels, taking into account local, regional and core-wide oscillations, is described. The ROM contains three sub-models: a neutron-kinetic model (describing neutron transport), a thermal- hydraulic model (describing the coolant flow) and a heat transfer model (describing heat transfer between the fuel and the coolant). All these three models are coupled to each other, using two feedback mechanisms: void feedback and doppler feedback. Each of the sub-models is described by a set of reduced ordinary differential equations, derived from the corresponding time space-dependent partial differential equations by using different types of approximations and mathematical techniques. All three models were developed from past ROMs and, subsequently, were modified in order to fit the purpose of our investigations. One of the novelties of the present ROM is that it takes into account the effect of the first three neutronic modes, namely the fundamental, the first and the second azimuthal modes, as well as the effect of local oscillations on these modes. In order to have a proper representation of both azimuthal modes, a four heated channel ROM was developed. Another modification, compared to earlier work, is the determination of the coupling reactivity coefficients for both void fraction and fuel temperature, which were calculated explicitly by evaluating cross-section perturbations with the help of the SIMULATE-3 and the CORESIM codes. The ROM was thereafter applied to a channel instability event that occurred at the Swedish Forsmark-1 BWR in 1996/1997. The time signals for each of the modes were generated from the ROM and compared with the measurements, performed at the plant. Some qualitative comparison between the ROM and the measurements was made. The results could bear some significance in understanding the instability event and its coupling mechanism to core-wide oscillations. (author)
Jacobian projection reduced-order models for dynamic systems with contact nonlinearities
Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.
2018-02-01
In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.
Directory of Open Access Journals (Sweden)
Katia M S Cabral
Full Text Available BEX3 (Brain Expressed X-linked protein 3 is a member of a mammal-specific placental protein family. Several studies have found the BEX proteins to be associated with neurodegeneration, the cell cycle and cancer. BEX3 has been predicted to be intrinsically disordered and also to represent an intracellular hub for cell signaling. The pro-apoptotic activity of BEX3 in association with a number of additional proteins has been widely supported; however, to the best of our knowledge, very limited data are available on the conformation of any of the members of the BEX family. In this study, we structurally characterized BEX3 using biophysical experimental data. Small angle X-ray scattering and atomic force microscopy revealed that BEX3 forms a specific higher-order oligomer that is consistent with a globular molecule. Solution nuclear magnetic resonance, partial proteinase K digestion, circular dichroism spectroscopy, and fluorescence techniques that were performed on the recombinant protein indicated that the structure of BEX3 is composed of approximately 31% α-helix and 20% β-strand, contains partially folded regions near the N- and C-termini, and a core which is proteolysis-resistant around residues 55-120. The self-oligomerization of BEX3 has been previously reported in cell culture and is consistent with our in vitro data.
Cabral, Katia M S; Raymundo, Diana P; Silva, Viviane S; Sampaio, Laura A G; Johanson, Laizes; Hill, Luis Fernando; Almeida, Fabio C L; Cordeiro, Yraima; Almeida, Marcius S
2015-01-01
BEX3 (Brain Expressed X-linked protein 3) is a member of a mammal-specific placental protein family. Several studies have found the BEX proteins to be associated with neurodegeneration, the cell cycle and cancer. BEX3 has been predicted to be intrinsically disordered and also to represent an intracellular hub for cell signaling. The pro-apoptotic activity of BEX3 in association with a number of additional proteins has been widely supported; however, to the best of our knowledge, very limited data are available on the conformation of any of the members of the BEX family. In this study, we structurally characterized BEX3 using biophysical experimental data. Small angle X-ray scattering and atomic force microscopy revealed that BEX3 forms a specific higher-order oligomer that is consistent with a globular molecule. Solution nuclear magnetic resonance, partial proteinase K digestion, circular dichroism spectroscopy, and fluorescence techniques that were performed on the recombinant protein indicated that the structure of BEX3 is composed of approximately 31% α-helix and 20% β-strand, contains partially folded regions near the N- and C-termini, and a core which is proteolysis-resistant around residues 55-120. The self-oligomerization of BEX3 has been previously reported in cell culture and is consistent with our in vitro data.
Model test on partial expansion in stratified subsidence during foundation pit dewatering
Wang, Jianxiu; Deng, Yansheng; Ma, Ruiqiang; Liu, Xiaotian; Guo, Qingfeng; Liu, Shaoli; Shao, Yule; Wu, Linbo; Zhou, Jie; Yang, Tianliang; Wang, Hanmei; Huang, Xinlei
2018-02-01
Partial expansion was observed in stratified subsidence during foundation pit dewatering. However, the phenomenon was suspected to be an error because the compression of layers is known to occur when subsidence occurs. A slice of the subsidence cone induced by drawdown was selected as the prototype. Model tests were performed to investigate the phenomenon. The underlying confined aquifer was generated as a movable rigid plate with a hinge at one end. The overlying layers were simulated with remolded materials collected from a construction site. Model tests performed under the conceptual model indicated that partial expansion occurred in stratified settlements under coordination deformation and consolidation conditions. During foundation pit dewatering, rapid drawdown resulted in rapid subsidence in the dewatered confined aquifer. The rapidly subsiding confined aquifer top was the bottom deformation boundary of the overlying layers. Non-coordination deformation was observed at the top and bottom of the subsiding overlying layers. The subsidence of overlying layers was larger at the bottom than at the top. The layers expanded and became thicker. The phenomenon was verified using numerical simulation method based on finite difference method. Compared with numerical simulation results, the boundary effect of the physical tests was obvious in the observation point close to the movable endpoint. The tensile stress of the overlying soil layers induced by the underlying settlement of dewatered confined aquifer contributed to the expansion phenomenon. The partial expansion of overlying soil layers was defined as inversed rebound. The inversed rebound was induced by inversed coordination deformation. Compression was induced by the consolidation in the overlying soil layers because of drainage. Partial expansion occurred when the expansion exceeded the compression. Considering the inversed rebound, traditional layer-wise summation method for calculating subsidence should be
Theory and Low-Order Modeling of Unsteady Airfoil Flows
Ramesh, Kiran
Unsteady flow phenomena are prevalent in a wide range of problems in nature and engineering. These include, but are not limited to, aerodynamics of insect flight, dynamic stall in rotorcraft and wind turbines, leading-edge vortices in delta wings, micro-air vehicle (MAV) design, gust handling and flow control. The most significant characteristics of unsteady flows are rapid changes in the circulation of the airfoil, apparent-mass effects, flow separation and the leading-edge vortex (LEV) phenomenon. Although experimental techniques and computational fluid dynamics (CFD) methods have enabled the detailed study of unsteady flows and their underlying features, a reliable and inexpensive loworder method for fast prediction and for use in control and design is still required. In this research, a low-order methodology based on physical principles rather than empirical fitting is proposed. The objective of such an approach is to enable insights into unsteady phenomena while developing approaches to model them. The basis of the low-order model developed here is unsteady thin-airfoil theory. A time-stepping approach is used to solve for the vorticity on an airfoil camberline, allowing for large amplitudes and nonplanar wakes. On comparing lift coefficients from this method against data from CFD and experiments for some unsteady test cases, it is seen that the method predicts well so long as LEV formation does not occur and flow over the airfoil is attached. The formation of leading-edge vortices (LEVs) in unsteady flows is initiated by flow separation and the formation of a shear layer at the airfoil's leading edge. This phenomenon has been observed to have both detrimental (dynamic stall in helicopters) and beneficial (high-lift flight in insects) effects. To predict the formation of LEVs in unsteady flows, a Leading Edge Suction Parameter (LESP) is proposed. This parameter is calculated from inviscid theory and is a measure of the suction at the airfoil's leading edge. It
A dynamic neural field model of temporal order judgments.
Hecht, Lauren N; Spencer, John P; Vecera, Shaun P
2015-12-01
Temporal ordering of events is biased, or influenced, by perceptual organization-figure-ground organization-and by spatial attention. For example, within a region assigned figural status or at an attended location, onset events are processed earlier (Lester, Hecht, & Vecera, 2009; Shore, Spence, & Klein, 2001), and offset events are processed for longer durations (Hecht & Vecera, 2011; Rolke, Ulrich, & Bausenhart, 2006). Here, we present an extension of a dynamic field model of change detection (Johnson, Spencer, Luck, & Schöner, 2009; Johnson, Spencer, & Schöner, 2009) that accounts for both the onset and offset performance for figural and attended regions. The model posits that neural populations processing the figure are more active, resulting in a peak of activation that quickly builds toward a detection threshold when the onset of a target is presented. This same enhanced activation for some neural populations is maintained when a present target is removed, creating delays in the perception of the target's offset. We discuss the broader implications of this model, including insights regarding how neural activation can be generated in response to the disappearance of information. (c) 2015 APA, all rights reserved).
Vortex network community based reduced-order force model
Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya; Taira, Kunihiko
2017-11-01
We characterize the vortical wake interactions by utilizing network theory and cluster-based approaches, and develop a data-inspired unsteady force model. In the present work, the vortical interaction network is defined by nodes representing vortical elements and the edges quantified by induced velocity measures amongst the vortices. The full vorticity field is reduced to a finite number of vortical clusters based on network community detection algorithm, which serves as a basis for a skeleton network that captures the essence of the wake dynamics. We use this reduced representation of the wake to develop a data-inspired reduced-order force model that can predict unsteady fluid forces on the body. The overall formulation is demonstrated for laminar flows around canonical bluff body wake and stalled flow over an airfoil. We also show the robustness of the present network-based model against noisy data, which motivates applications towards turbulent flows and experimental measurements. Supported by the National Science Foundation (Grant 1632003).
An odor interaction model of binary odorant mixtures by a partial differential equation method.
Yan, Luchun; Liu, Jiemin; Wang, Guihua; Wu, Chuandong
2014-07-09
A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.
An Odor Interaction Model of Binary Odorant Mixtures by a Partial Differential Equation Method
Directory of Open Access Journals (Sweden)
Luchun Yan
2014-07-01
Full Text Available A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE method. Based on the measurement method (tangent-intercept method of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture’s odor intensity to the individual odorant’s relative odor activity value (OAV. Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.
McNeish, Daniel; Dumas, Denis
2017-01-01
Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components-ability, capacity, and availability-where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study-Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.
Directory of Open Access Journals (Sweden)
Salvador Lucas
2015-12-01
Full Text Available Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.
Robust-BD Estimation and Inference for General Partially Linear Models
Directory of Open Access Journals (Sweden)
Chunming Zhang
2017-11-01
Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.
Computational design of patterned interfaces using reduced order models
International Nuclear Information System (INIS)
Vattre, A.J.; Abdolrahim, N.; Kolluri, K.; Demkowicz, M.J.
2014-01-01
Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids. Many interfaces have non-uniform internal structures comprised of misfit dislocations, which in turn govern interface properties. We develop and validate a computational strategy for designing interfaces with controlled misfit dislocation patterns by tailoring interface crystallography and composition. Our approach relies on a novel method for predicting the internal structure of interfaces: rather than obtaining it from resource-intensive atomistic simulations, we compute it using an efficient reduced order model based on anisotropic elasticity theory. Moreover, our strategy incorporates interface synthesis as a constraint on the design process. As an illustration, we apply our approach to the design of interfaces with rapid, 1-D point defect diffusion. Patterned interfaces may be integrated into the microstructure of composite materials, markedly improving performance. (authors)
Basic first-order model theory in Mizar
Directory of Open Access Journals (Sweden)
Marco Bright Caminati
2010-01-01
Full Text Available The author has submitted to Mizar Mathematical Library a series of five articles introducing a framework for the formalization of classical first-order model theory.In them, Goedel's completeness and Lowenheim-Skolem theorems have also been formalized for the countable case, to offer a first application of it and to showcase its utility.This is an overview and commentary on some key aspects of this setup.It features exposition and discussion of a new encoding of basic definitions and theoretical gears needed for the task, remarks about the design strategies and approaches adopted in their implementation, and more general reflections about proof checking induced by the work done.
Consequences of the partial restoration of chiral symmetry in an AdS/QCD model
International Nuclear Information System (INIS)
Kim, Youngman; Lee, Hyun Kyu
2008-01-01
Chiral symmetry is an essential concept in understanding QCD at low energy. We treat the chiral condensate, which measures the spontaneous breaking of chiral symmetry, as a free parameter to investigate the effect of partially restored chiral symmetry on the physical quantities in the framework of an AdS/QCD model. We observe an interesting scaling behavior among the nucleon mass, pion decay constant, and chiral condensate. We propose a phenomenological way to introduce the temperature dependence of a physical quantity in the AdS/QCD model with the thermal AdS metric.
The partial duration series method in regional index-flood modeling
DEFF Research Database (Denmark)
Madsen, Henrik; Rosbjerg, Dan
1997-01-01
A regional index-flood method based on the partial duration series model is introduced. The model comprises the assumptions of a Poisson-distributed number of threshold exceedances and generalized Pareto (GP) distributed peak magnitudes. The regional T-year event estimator is based on a regional...... estimator is superior to the at-site estimator even in extremely heterogenous regions, the performance of the regional estimator being relatively better in regions with a negative shape parameter. When the record length increases, the relative performance of the regional estimator decreases, but it is still...
DEFF Research Database (Denmark)
Madsen, Henrik; Rosbjerg, Dan
1997-01-01
parameters is inferred from regional data using generalized least squares (GLS) regression. Two different Bayesian T-year event estimators are introduced: a linear estimator that requires only some moments of the prior distributions to be specified and a parametric estimator that is based on specified......A regional estimation procedure that combines the index-flood concept with an empirical Bayes method for inferring regional information is introduced. The model is based on the partial duration series approach with generalized Pareto (GP) distributed exceedances. The prior information of the model...
Exotic muon-to-positron conversion in nuclei: partial transition sum evaluation by using shell model
International Nuclear Information System (INIS)
Divari, P.C.; Vergados, J.D.; Kosmas, T.S.; Skouras, L.D.
2001-01-01
A comprehensive study of the exotic (μ - ,e + ) conversion in 27 Al, 27 Al(μ - ,e + ) 27 Na is presented. The relevant operators are deduced assuming one-pion and two-pion modes in the framework of intermediate neutrino mixing models, paying special attention to the light neutrino case. The total rate is calculated by summing over partial transition strengths for all kinematically accessible final states derived with s-d shell model calculations employing the well-known Wildenthal realistic interaction
Ullah, Asmat; Chen, Wen; Khan, Mushtaq Ahmad
2017-07-01
This paper introduces a fractional order total variation (FOTV) based model with three different weights in the fractional order derivative definition for multiplicative noise removal purpose. The fractional-order Euler Lagrange equation which is a highly non-linear partial differential equation (PDE) is obtained by the minimization of the energy functional for image restoration. Two numerical schemes namely an iterative scheme based on the dual theory and majorization- minimization algorithm (MMA) are used. To improve the restoration results, we opt for an adaptive parameter selection procedure for the proposed model by applying the trial and error method. We report numerical simulations which show the validity and state of the art performance of the fractional-order model in visual improvement as well as an increase in the peak signal to noise ratio comparing to corresponding methods. Numerical experiments also demonstrate that MMAbased methodology is slightly better than that of an iterative scheme.
Imai, Takashi; Kovalenko, Andriy; Hirata, Fumio
2005-04-14
The three-dimensional reference interaction site model (3D-RISM) theory is applied to the analysis of hydration effects on the partial molar volume of proteins. For the native structure of some proteins, the partial molar volume is decomposed into geometric and hydration contributions using the 3D-RISM theory combined with the geometric volume calculation. The hydration contributions are correlated with the surface properties of the protein. The thermal volume, which is the volume of voids around the protein induced by the thermal fluctuation of water molecules, is directly proportional to the accessible surface area of the protein. The interaction volume, which is the contribution of electrostatic interactions between the protein and water molecules, is apparently governed by the charged atomic groups on the protein surface. The polar atomic groups do not make any contribution to the interaction volume. The volume differences between low- and high-pressure structures of lysozyme are also analyzed by the present method.
Nguyen, Howard; Willacy, Karen; Allen, Mark
2012-01-01
KINETICS is a coupled dynamics and chemistry atmosphere model that is data intensive and computationally demanding. The potential performance gain from using a supercomputer motivates the adaptation from a serial version to a parallelized one. Although the initial parallelization had been done, bottlenecks caused by an abundance of communication calls between processors led to an unfavorable drop in performance. Before starting on the parallel optimization process, a partial overhaul was required because a large emphasis was placed on streamlining the code for user convenience and revising the program to accommodate the new supercomputers at Caltech and JPL. After the first round of optimizations, the partial runtime was reduced by a factor of 23; however, performance gains are dependent on the size of the data, the number of processors requested, and the computer used.
Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations
Bang, Youngsuk
Reduced order modeling (ROM) has been recognized as an indispensable approach when the engineering analysis requires many executions of high fidelity simulation codes. Examples of such engineering analyses in nuclear reactor core calculations, representing the focus of this dissertation, include the functionalization of the homogenized few-group cross-sections in terms of the various core conditions, e.g. burn-up, fuel enrichment, temperature, etc. This is done via assembly calculations which are executed many times to generate the required functionalization for use in the downstream core calculations. Other examples are sensitivity analysis used to determine important core attribute variations due to input parameter variations, and uncertainty quantification employed to estimate core attribute uncertainties originating from input parameter uncertainties. ROM constructs a surrogate model with quantifiable accuracy which can replace the original code for subsequent engineering analysis calculations. This is achieved by reducing the effective dimensionality of the input parameter, the state variable, or the output response spaces, by projection onto the so-called active subspaces. Confining the variations to the active subspace allows one to construct an ROM model of reduced complexity which can be solved more efficiently. This dissertation introduces a new algorithm to render reduction with the reduction errors bounded based on a user-defined error tolerance which represents the main challenge of existing ROM techniques. Bounding the error is the key to ensuring that the constructed ROM models are robust for all possible applications. Providing such error bounds represents one of the algorithmic contributions of this dissertation to the ROM state-of-the-art. Recognizing that ROM techniques have been developed to render reduction at different levels, e.g. the input parameter space, the state space, and the response space, this dissertation offers a set of novel
A note on inventory model for ameliorating items with time dependent second order demand rate
Directory of Open Access Journals (Sweden)
Gobinda Chandra Panda
2013-03-01
Full Text Available Background: This paper is concerned with the development of ameliorating inventory models. The ameliorating inventory is the inventory of goods whose utility increases over the time by ameliorating activation. Material and Methods: This study is performed according to two areas: one is an economic order quantity (EOQ model for the items whose utility is ameliorating in accordance with Weibull distribution, and the other is a partial selling quantity (PSQ model developed for selling the surplus inventory accumulated by ameliorating activation with linear demand. The aim of this paper was to develop a mathematical model for inventory type concerned in the paper. Numerical examples were presented show the effect of ameliorating rate on inventory polices. Results and Conclusions: The inventory model for items with Weibull ameliorating is developed. For the case of small ameliorating rate (less than linear demand rate, EOQ model is developed, and for the case where ameliorating rate is greater than linear demand rate, PSQ model is developed. .
Yuniarto, Budi; Kurniawan, Robert
2017-03-01
PLS Path Modeling (PLS-PM) is different from covariance based SEM, where PLS-PM use an approach based on variance or component, therefore, PLS-PM is also known as a component based SEM. Multiblock Partial Least Squares (MBPLS) is a method in PLS regression which can be used in PLS Path Modeling which known as Multiblock PLS Path Modeling (MBPLS-PM). This method uses an iterative procedure in its algorithm. This research aims to modify MBPLS-PM with Back Propagation Neural Network approach. The result is MBPLS-PM algorithm can be modified using the Back Propagation Neural Network approach to replace the iterative process in backward and forward step to get the matrix t and the matrix u in the algorithm. By modifying the MBPLS-PM algorithm using Back Propagation Neural Network approach, the model parameters obtained are relatively not significantly different compared to model parameters obtained by original MBPLS-PM algorithm.
A Partially-Stirred Batch Reactor Model for Under-Ventilated Fire Dynamics
McDermott, Randall; Weinschenk, Craig
2013-11-01
A simple discrete quadrature method is developed for closure of the mean chemical source term in large-eddy simulations (LES) and implemented in the publicly available fire model, Fire Dynamics Simulator (FDS). The method is cast as a partially-stirred batch reactor model for each computational cell. The model has three distinct components: (1) a subgrid mixing environment, (2) a mixing model, and (3) a set of chemical rate laws. The subgrid probability density function (PDF) is described by a linear combination of Dirac delta functions with quadrature weights set to satisfy simple integral constraints for the computational cell. It is shown that under certain limiting assumptions, the present method reduces to the eddy dissipation concept (EDC). The model is used to predict carbon monoxide concentrations in direct numerical simulation (DNS) of a methane slot burner and in LES of an under-ventilated compartment fire.
Effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit.
Xi, Peng; Li, Yan; Ge, Xiaojin; Liu, Dandan; Miao, Mingsan
2018-05-01
Observing the effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit. We prepared boiling water scalded rabbits with deep II degree scald models and applied high, medium and low doses of nano-silver hydrogel coating film for different time and area. Then we compared the difference of burned paper weight before administration and after administration model burns, burn local skin irritation points infection, skin crusting and scabs from the time, and the impact of local skin tissue morphology. Rabbits deep II degree burn model successful modeling; on day 12, 18, high, medium and low doses of nano-silver hydrogel coating film significantly reduced skin irritation of rabbits infected with the integral value ( P film group significantly decreased skin irritation, infection integral value ( P film significantly reduced film rabbits' scalded skin crusting time ( P film on the deep partial thickness burns has a significant therapeutic effect; external use has a significant role in wound healing.
Whole object surface area and volume of partial-view 3D models
International Nuclear Information System (INIS)
Mulukutla, Gopal K; Proussevitch, Alexander A; Genareau, Kimberly D; Durant, Adam J
2017-01-01
Micro-scale 3D models, important components of many studies in science and engineering, are often used to determine morphological characteristics such as shape, surface area and volume. The application of techniques such as stereoscopic scanning electron microscopy on whole objects often results in ‘partial-view’ models with a portion of object not within the field of view thus not captured in the 3D model. The nature and extent of the surface not captured is dependent on the complex interaction of imaging system attributes (e.g. working distance, viewing angle) with object size, shape and morphology. As a result, any simplistic assumptions in estimating whole object surface area or volume can lead to significant errors. In this study, we report on a novel technique to estimate the physical fraction of an object captured in a partial-view 3D model of an otherwise whole object. This allows a more accurate estimate of surface area and volume. Using 3D models, we demonstrate the robustness of this method and the accuracy of surface area and volume estimates relative to true values. (paper)
A Reduced-order NLTE Kinetic Model for Radiating Plasmas of Outer Envelopes of Stellar Atmospheres
Energy Technology Data Exchange (ETDEWEB)
Munafò, Alessandro [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 206A Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States); Mansour, Nagi N. [NASA Ames Research Center, Moffett Field, 94035 CA (United States); Panesi, Marco, E-mail: munafo@illinois.edu, E-mail: nagi.n.mansour@nasa.gov, E-mail: m.panesi@illinois.edu [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 306 Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States)
2017-04-01
The present work proposes a self-consistent reduced-order NLTE kinetic model for radiating plasmas found in the outer layers of stellar atmospheres. A detailed collisional-radiative kinetic mechanism is constructed by leveraging the most up-to-date set of ab initio and experimental data available in the literature. This constitutes the starting point for the derivation of a reduced-order model, obtained by lumping the bound energy states into groups. In order to determine the needed thermo-physical group properties, uniform and Maxwell–Boltzmann energy distributions are used to reconstruct the energy population of each group. Finally, the reduced set of governing equations for the material gas and the radiation field is obtained based on the moment method. Applications consider the steady flow across a shock wave in partially ionized hydrogen. The results clearly demonstrate that adopting a Maxwell–Boltzmann grouping allows, on the one hand, for a substantial reduction of the number of unknowns and, on the other, to maintain accuracy for both gas and radiation quantities. Also, it is observed that, when neglecting line radiation, the use of two groups already leads to a very accurate resolution of the photo-ionization precursor, internal relaxation, and radiative cooling regions. The inclusion of line radiation requires adopting just one additional group to account for optically thin losses in the α , β , and γ lines of the Balmer and Paschen series. This trend has been observed for a wide range of shock wave velocities.
A new nonlinear turbulence model based on Partially-Averaged Navier-Stokes Equations
International Nuclear Information System (INIS)
Liu, J T; Wu, Y L; Cai, C; Liu, S H; Wang, L Q
2013-01-01
Partially-averaged Navier-Stokes (PANS) Model was recognized as a Reynolds-averaged Navier-Stokes (RANS) to direct numerical simulation (DNS) bridging method. PANS model was purported for any filter width-from RANS to DNS. PANS method also shared some similarities with the currently popular URANS (unsteady RANS) method. In this paper, a new PANS model was proposed, which was based on RNG k-ε turbulence model. The Standard and RNG k-ε turbulence model were both isotropic models, as well as PANS models. The sheer stress in those PANS models was solved by linear equation. The linear hypothesis was not accurate in the simulation of complex flow, such as stall phenomenon. The sheer stress here was solved by nonlinear method proposed by Ehrhard. Then, the nonlinear PANS model was set up. The pressure coefficient of the suction side of the NACA0015 hydrofoil was predicted. The result of pressure coefficient agrees well with experimental result, which proves that the nonlinear PANS model can capture the high pressure gradient flow. A low specific centrifugal pump was used to verify the capacity of the nonlinear PANS model. The comparison between the simulation results of the centrifugal pump and Particle Image Velocimetry (PIV) results proves that the nonlinear PANS model can be used in the prediction of complex flow field
Sparsity enabled cluster reduced-order models for control
Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.
2018-01-01
Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.
On order reduction in hydrogen isotope distillation models
International Nuclear Information System (INIS)
Sarigiannis, D.A.
1994-01-01
The design integration of the fuel processing system for the next generation fusion reactor plants (such as ITER and beyond) requires the enhancement of safety features related to the operation of the system. The current drive for inherent safety of hazardous chemical plants warrants the minimization of active toxic or radioactive inventories and the identification of process pathways with minimal risk of accidental or routine releases. New mathematical and numerical tools have been developed for the dynamic simulation and optimization of the safety characteristics related to tritium in all its forms in the fusion fuel processing system. The separation of hydrogen isotopes by cryogenic distillation is a key process therein, due to the importance of the separation performance for the quality of the fuel mixture and the on site inventory, the increased energy requirements for cryogenic operation, and the high order of mathematical complexity required for accurate models, able to predict the transient as well as the steady state behavior of the process. The modeling methodology described here is a part of a new dynamic simulation code that captures the inventory dynamics of all the species in the fusion fuel processing plant. The significant reduction of the computational effort and time required by this code will permit designers to easily explore a variety of design and technology options and assess their impact on the overall power plant safety
MacNab, Ying C
2016-08-01
This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.
Li, Xu; Yang, Chuanlei; Wang, Yinyan; Wang, Hechun
2018-01-01
To achieve a much more extensive intake air flow range of the diesel engine, a variable-geometry compressor (VGC) is introduced into a turbocharged diesel engine. However, due to the variable diffuser vane angle (DVA), the prediction for the performance of the VGC becomes more difficult than for a normal compressor. In the present study, a prediction model comprising an elliptical equation and a PLS (partial least-squares) model was proposed to predict the performance of the VGC. The speed lines of the pressure ratio map and the efficiency map were fitted with the elliptical equation, and the coefficients of the elliptical equation were introduced into the PLS model to build the polynomial relationship between the coefficients and the relative speed, the DVA. Further, the maximal order of the polynomial was investigated in detail to reduce the number of sub-coefficients and achieve acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority of compressor performance prediction, the prediction results of this model were compared with those of the look-up table and back-propagation neural networks (BPNNs). The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than the look-up table and the BPNN methods under the same condition in VGC performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for the VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future.
International Nuclear Information System (INIS)
Khaleghi, H.; Hosseini, S.M.
2003-01-01
In recent years special attention has been paid to the topic of diesel engine combustion. Various combustion models are used in CFD codes. In this paper Partially Stirred Reactor (PaSR) model, one of the newest turbulent combustion models, is introduced. This model has been employed in conjunction with the non-iterative PISO algorithm to calculate spray combustion in an axi-symmetric, direct injection diesel engine. Qualitative consideration of the results shows very good agreement with physical expectations and other numerical and experimental results. (author)
Styranivska, Oksana; Kliuchkovska, Nataliia; Mykyyevych, Nataliya
2017-01-01
To analyze the stress-strain states of bone and abutment teeth during the use of different prosthetic designs of fixed partial dentures with the use of relevant mathematical modeling principles. The use of Comsol Multiphysics 3.5 (Comsol AB, Sweden) software during the mathematical modeling of stress-strain states provided numerical data for analytical interpretation in three different clinical scenarios with fixed dentures and different abutment teeth and demountable prosthetic denture with the saddle-shaped intermediate part. Microsoft Excel Software (Microsoft Office 2017) helped to evaluate absolute mistakes of stress and strain parameters of each abutment tooth during three modeled scenarios and normal condition and to summarize data into the forms of tables. In comparison with the fixed prosthetic denture supported by the canine, first premolar, and third molar, stresses at the same abutment teeth with the use of demountable denture with the saddle-shaped intermediate part decreased: at the mesial abutment tooth by 2.8 times, at distal crown by 6.1 times, and at the intermediate part by 11.1 times, respectively, the deformation level decreased by 3.1, 1.9, and 1.4 times at each area. The methods of mathematical modeling proved that complications during the use of fixed partial dentures based on the overload effect of the abutment teeth and caused by the deformation process inside the intermediate section of prosthetic construction.
Partial least squares path modeling basic concepts, methodological issues and applications
Noonan, Richard
2017-01-01
This edited book presents the recent developments in partial least squares-path modeling (PLS-PM) and provides a comprehensive overview of the current state of the most advanced research related to PLS-PM. The first section of this book emphasizes the basic concepts and extensions of the PLS-PM method. The second section discusses the methodological issues that are the focus of the recent development of the PLS-PM method. The third part discusses the real world application of the PLS-PM method in various disciplines. The contributions from expert authors in the field of PLS focus on topics such as the factor-based PLS-PM, the perfect match between a model and a mode, quantile composite-based path modeling (QC-PM), ordinal consistent partial least squares (OrdPLSc), non-symmetrical composite-based path modeling (NSCPM), modern view for mediation analysis in PLS-PM, a multi-method approach for identifying and treating unobserved heterogeneity, multigroup analysis (PLS-MGA), the assessment of the common method b...
Rasch-Master's Partial Credit Model in the assessment of children's creativity in drawings.
Nakano, Tatiana de Cássia; Primi, Ricardo
2014-01-01
The purpose of the present study was to use the Partial Credit Model to study the factors of the Test of Creativity in Children and identify which characteristics of the creative person would be more effective to differentiate subjects according to their ability level. A sample of 1426 students from first to eighth grades answered the instrument. The Partial Credits model was used to estimate the ability of the subjects and item difficulties on a common scale for each of the four factors, indicating which items required a higher level of creativity to be scored and will differentiate the more creative individuals. The results demonstrated that the greater part of the characteristics showed good fit indices, with values between 0.80 and 1.30 both infit and outfit, indicating a response pattern consistent with the model. The characteristics of Unusual Perspective, Expression of Emotion and Originality have been identified as better predictors of creative performance because requires greater ability level (usually above two standard deviation). These results may be used in the future development of an instrument's reduced form or simplification of the current correction model.
Nam, Sung Sik
2017-06-19
Complex wireless transmission systems require multi-dimensional joint statistical techniques for performance evaluation. Here, we first present the exact closed-form results on order statistics of any arbitrary partial sums of Gamma random variables with the closedform results of core functions specialized for independent and identically distributed Nakagami-m fading channels based on a moment generating function-based unified analytical framework. These both exact closed-form results have never been published in the literature. In addition, as a feasible application example in which our new offered derived closed-form results can be applied is presented. In particular, we analyze the outage performance of the finger replacement schemes over Nakagami fading channels as an application of our method. Note that these analysis results are directly applicable to several applications, such as millimeter-wave communication systems in which an antenna diversity scheme operates using an finger replacement schemes-like combining scheme, and other fading scenarios. Note also that the statistical results can provide potential solutions for ordered statistics in any other research topics based on Gamma distributions or other advanced wireless communications research topics in the presence of Nakagami fading.
Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility
Kou, Jisheng; Sun, Shuyu
2016-01-01
In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic
A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence
Directory of Open Access Journals (Sweden)
Simon Zwieback
2015-06-01
Full Text Available Changes in soil moisture between two radar acquisitions can impact the observed coherence in differential interferometry: both coherence magnitude |Υ| and phase Φ are affected. The influence on the latter potentially biases the estimation of deformations. These effects have been found to be variable in magnitude and sign, as well as dependent on polarization, as opposed to predictions by existing models. Such diversity can be explained when the soil is modelled as a half-space with spatially varying dielectric properties and a rough interface. The first-order perturbative solution achieves–upon calibration with airborne L band data–median correlations ρ at HH polarization of 0.77 for the phase Φ, of 0.50 for |Υ|, and for the phase triplets ≡ of 0.56. The predictions are sensitive to the choice of dielectric mixing model, in particular the absorptive properties; the differences between the mixing models are found to be partially compensatable by varying the relative importance of surface and volume scattering. However, for half of the agricultural fields the Hallikainen mixing model cannot reproduce the observed sensitivities of the phase to soil moisture. In addition, the first-order expansion does not predict any impact on the HV coherence, which is however empirically found to display similar sensitivities to soil moisture as the co-pol channels HH and VV. These results indicate that the first-order solution, while not able to reproduce all observed phenomena, can capture some of the more salient patterns of the effect of soil moisture changes on the HH and VV DInSAR signals. Hence it may prove useful in separating the deformations from the moisture signals, thus yielding improved displacement estimates or new ways for inferring soil moisture.
Fixed point and anomaly mediation in partial {\\boldsymbol{N}}=2 supersymmetric standard models
Yin, Wen
2018-01-01
Motivated by the simple toroidal compactification of extra-dimensional SUSY theories, we investigate a partial N = 2 supersymmetric (SUSY) extension of the standard model which has an N = 2 SUSY sector and an N = 1 SUSY sector. We point out that below the scale of the partial breaking of N = 2 to N = 1, the ratio of Yukawa to gauge couplings embedded in the original N = 2 gauge interaction in the N = 2 sector becomes greater due to a fixed point. Since at the partial breaking scale the sfermion masses in the N = 2 sector are suppressed due to the N = 2 non-renormalization theorem, the anomaly mediation effect becomes important. If dominant, the anomaly-induced masses for the sfermions in the N = 2 sector are almost UV-insensitive due to the fixed point. Interestingly, these masses are always positive, i.e. there is no tachyonic slepton problem. From an example model, we show interesting phenomena differing from ordinary MSSM. In particular, the dark matter particle can be a sbino, i.e. the scalar component of the N = 2 vector multiplet of {{U}}{(1)}Y. To obtain the correct dark matter abundance, the mass of the sbino, as well as the MSSM sparticles in the N = 2 sector which have a typical mass pattern of anomaly mediation, is required to be small. Therefore, this scenario can be tested and confirmed in the LHC and may be further confirmed by the measurement of the N = 2 Yukawa couplings in future colliders. This model can explain dark matter, the muon g-2 anomaly, and gauge coupling unification, and relaxes some ordinary problems within the MSSM. It is also compatible with thermal leptogenesis.
Autoregressive Model with Partial Forgetting within Rao-Blackwellized Particle Filter
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Hofman, Radek
2012-01-01
Roč. 41, č. 5 (2012), s. 582-589 ISSN 0361-0918 R&D Projects: GA MV VG20102013018; GA ČR GA102/08/0567 Grant - others:ČVUT(CZ) SGS 10/099/OHK3/1T/16 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian methods * Particle filters * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.295, year: 2012 http://library.utia.cas.cz/separaty/2012/AS/dedecius-autoregressive model with partial forgetting within rao-blackwellized particle filter.pdf
Screening for a Chronic Disease: A Multiple Stage Duration Model with Partial Observability.
Mroz, Thomas A; Picone, Gabriel; Sloan, Frank; Yashkin, Arseniy P
2016-08-01
We estimate a dynamic multi-stage duration model to investigate how early detection of diabetes can delay the onset of lower extremity complications and death. We allow for partial observability of the disease stage, unmeasured heterogeneity, and endogenous timing of diabetes screening. Timely diagnosis appears important. We evaluate the effectiveness of two potential policies to reduce the monetary costs of frequent screening in terms of lost longevity. Compared to the status quo, the more restrictive policy yields an implicit value for an additional year of life of about $50,000, while the less restrictive policy implies a value of about $120,000.
A queueing model for error control of partial buffer sharing in ATM
Directory of Open Access Journals (Sweden)
Ahn Boo Yong
1999-01-01
Full Text Available We model the error control of the partial buffer sharing of ATM by a queueing system M 1 , M 2 / G / 1 / K + 1 with threshold and instantaneous Bernoulli feedback. We first derive the system equations and develop a recursive method to compute the loss probabilities at an arbitrary time epoch. We then build an approximation scheme to compute the mean waiting time of each class of cells. An algorithm is developed for finding the optimal threshold and queue capacity for a given quality of service.
Modelling of diffusion from equilibrium diffraction fluctuations in ordered phases
International Nuclear Information System (INIS)
Arapaki, E.; Argyrakis, P.; Tringides, M.C.
2008-01-01
Measurements of the collective diffusion coefficient D c at equilibrium are difficult because they are based on monitoring low amplitude concentration fluctuations generated spontaneously, that are difficult to measure experimentally. A new experimental method has been recently used to measure time-dependent correlation functions from the diffraction intensity fluctuations and was applied to measure thermal step fluctuations. The method has not been applied yet to measure superstructure intensity fluctuations in surface overlayers and to extract D c . With Monte Carlo simulations we study equilibrium fluctuations in Ising lattice gas models with nearest neighbor attractive and repulsive interactions. The extracted diffusion coefficients are compared to the ones obtained from equilibrium methods. The new results are in good agreement with the results from the other methods, i.e., D c decreases monotonically with coverage Θ for attractive interactions and increases monotonically with Θ for repulsive interactions. Even the absolute value of D c agrees well with the results obtained with the probe area method. These results confirm that this diffraction based method is a novel, reliable way to measure D c especially within the ordered region of the phase diagram when the superstructure spot has large intensity
Coenzyme Q10 partially restores pathological alterations in a macrophage model of Gaucher disease.
de la Mata, Mario; Cotán, David; Oropesa-Ávila, Manuel; Villanueva-Paz, Marina; de Lavera, Isabel; Álvarez-Córdoba, Mónica; Luzón-Hidalgo, Raquel; Suárez-Rivero, Juan M; Tiscornia, Gustavo; Sánchez-Alcázar, José A
2017-02-06
Gaucher disease (GD) is caused by mutations in the GBA1 gene which encodes lysosomal β-glucocerebrosidase (GCase). In GD, partial or complete loss of GCase activity causes the accumulation of the glycolipids glucosylceramide (GlcCer) and glucosylsphingosine in the lysosomes of macrophages. In this manuscript, we investigated the effects of glycolipids accumulation on lysosomal and mitochondrial function, inflammasome activation and efferocytosis capacity in a THP-1 macrophage model of Gaucher disease. In addition, the beneficial effects of coenzyme Q 10 (CoQ) supplementation on cellular alterations were evaluated. Chemically-induced Gaucher macrophages were developed by differentiateing THP-1 monocytes to macrophages by treatment with phorbol 12-myristate 13-acetate (PMA) and then inhibiting intracellular GCase with conduritol B-epoxide (CBE), a specific irreversible inhibitor of GCase activity, and supplementing the medium with exogenous GlcCer. This cell model accumulated up to 16-fold more GlcCer compared with control THP-1 cells. Chemically-induced Gaucher macrophages showed impaired autophagy flux associated with mitochondrial dysfunction and increased oxidative stress, inflammasome activation and impaired efferocytosis. All abnormalities were partially restored by supplementation with CoQ. These data suggest that targeting mitochondria function and oxidative stress by CoQ can ameliorate the pathological phenotype of Gaucher cells. Chemically-induced Gaucher macrophages provide cellular models that can be used to investigate disease pathogenesis and explore new therapeutics for GD.
Analysis and Modeling of Parallel Photovoltaic Systems under Partial Shading Conditions
Buddala, Santhoshi Snigdha
Since the industrial revolution, fossil fuels like petroleum, coal, oil, natural gas and other non-renewable energy sources have been used as the primary energy source. The consumption of fossil fuels releases various harmful gases into the atmosphere as byproducts which are hazardous in nature and they tend to deplete the protective layers and affect the overall environmental balance. Also the fossil fuels are bounded resources of energy and rapid depletion of these sources of energy, have prompted the need to investigate alternate sources of energy called renewable energy. One such promising source of renewable energy is the solar/photovoltaic energy. This work focuses on investigating a new solar array architecture with solar cells connected in parallel configuration. By retaining the structural simplicity of the parallel architecture, a theoretical small signal model of the solar cell is proposed and modeled to analyze the variations in the module parameters when subjected to partial shading conditions. Simulations were run in SPICE to validate the model implemented in Matlab. The voltage limitations of the proposed architecture are addressed by adopting a simple dc-dc boost converter and evaluating the performance of the architecture in terms of efficiencies by comparing it with the traditional architectures. SPICE simulations are used to compare the architectures and identify the best one in terms of power conversion efficiency under partial shading conditions.
Partial synchronization in networks of non-linearly coupled oscillators: The Deserter Hubs Model
Energy Technology Data Exchange (ETDEWEB)
Freitas, Celso, E-mail: cbnfreitas@gmail.com; Macau, Elbert, E-mail: elbert.macau@inpe.br [Associate Laboratory for Computing and Applied Mathematics - LAC, Brazilian National Institute for Space Research - INPE (Brazil); Pikovsky, Arkady, E-mail: pikovsky@uni-potsdam.de [Department of Physics and Astronomy, University of Potsdam, Germany and Department of Control Theory, Nizhni Novgorod State University, Gagarin Av. 23, 606950, Nizhni Novgorod (Russian Federation)
2015-04-15
We study the Deserter Hubs Model: a Kuramoto-like model of coupled identical phase oscillators on a network, where attractive and repulsive couplings are balanced dynamically due to nonlinearity of interactions. Under weak force, an oscillator tends to follow the phase of its neighbors, but if an oscillator is compelled to follow its peers by a sufficient large number of cohesive neighbors, then it actually starts to act in the opposite manner, i.e., in anti-phase with the majority. Analytic results yield that if the repulsion parameter is small enough in comparison with the degree of the maximum hub, then the full synchronization state is locally stable. Numerical experiments are performed to explore the model beyond this threshold, where the overall cohesion is lost. We report in detail partially synchronous dynamical regimes, like stationary phase-locking, multistability, periodic and chaotic states. Via statistical analysis of different network organizations like tree, scale-free, and random ones, we found a measure allowing one to predict relative abundance of partially synchronous stationary states in comparison to time-dependent ones.
Carraro, Mattia; Park, Albert H; Harrison, Robert V
2016-02-01
Some forms of sensorineural hearing loss involve damage or degenerative changes to the stria vascularis and/or other vascular structures in the cochlea. In animal models, many methods for anatomical assessment of cochlear vasculature exist, each with advantages and limitations. One methodology, corrosion casting, has proved useful in some species, however in the mouse model this technique is difficult to achieve because digestion of non vascular tissue results in collapse of the delicate cast specimen. We have developed a partial corrosion cast method that allows visualization of vasculature along much of the cochlear length but maintains some structural integrity of the specimen. We provide a detailed step-by-step description of this novel technique. We give some illustrative examples of the use of the method in mouse models of presbycusis and cytomegalovirus (CMV) infection. Copyright © 2015 Elsevier B.V. All rights reserved.
A comparison of partially specular radiosity and ray tracing for room acoustics modeling
Beamer, C. Walter; Muehleisen, Ralph T.
2005-04-01
Partially specular (PS) radiosity is an extended form of the general radiosity method. Acoustic radiosity is a form of bulk transfer of radiant acoustic energy. This bulk transfer is accomplished through a system of energy balance equations that relate the bulk energy transfer of each surface in the system to all other surfaces in the system. Until now acoustic radiosity has been limited to modeling only diffuse surface reflection. The new PS acoustic radiosity method can model all real surface types, diffuse, specular and everything in between. PS acoustic radiosity also models all real source types and distributions, not just point sources. The results of the PS acoustic radiosity method are compared to those of well known ray tracing programs. [Work supported by NSF.
Modeling treatment of ischemic heart disease with partially observable Markov decision processes.
Hauskrecht, M; Fraser, H
1998-01-01
Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead they are very often dependent and interleaved over time, mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of Partially observable Markov decision processes (POMDPs) developed and used in operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In the paper, we show how the POMDP framework could be used to model and solve the problem of the management of patients with ischemic heart disease, and point out modeling advantages of the framework over standard decision formalisms.
Effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit
Directory of Open Access Journals (Sweden)
Peng Xi
2018-05-01
Full Text Available Objective: Observing the effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit. Method: We prepared boiling water scalded rabbits with deep II degree scald models and applied high, medium and low doses of nano-silver hydrogel coating film for different time and area. Then we compared the difference of burned paper weight before administration and after administration model burns, burn local skin irritation points infection, skin crusting and scabs from the time, and the impact of local skin tissue morphology. Result: Rabbits deep II degree burn model successful modeling; on day 12, 18, high, medium and low doses of nano-silver hydrogel coating film significantly reduced skin irritation of rabbits infected with the integral value (P < 0.01, P < 0.05; high, medium and low doses of nano-silver hydrogel coating film group significantly decreased skin irritation, infection integral value (P < 0.01, P < 0.05; high, medium and low doses of nano-silver hydrogel coating film significantly reduced film rabbits’ scalded skin crusting time (P < 0.01, significantly shortened the rabbit skin burns from the scab time (P < 0.01, and significantly improved the treatment of skin diseases in rabbits scald model change (P < 0.01, P < 0.05. Conclusion: The nano-silver hydrogel coating film on the deep partial thickness burns has a significant therapeutic effect; external use has a significant role in wound healing. Keywords: Nano-silver hydrogel coating film, Deep degree burns, Topical, Rabbits
Evaluation of regeneration of liver function in pig model of auxiliary partial liver transplantation
International Nuclear Information System (INIS)
Li Jiaxin; Chen Xiaopeng; Rui Ging; Shong Qun; Chen Fangman; Lu Meijing; Chen Yongquan
2010-01-01
Objective: To establish a pig model of auxiliary partial liver transplantation and observe the liver function regeneration of host liver and graft. Methods: The portal vein providing for the host liver were gradually contracted; the donor hepatic veins were eng-to-side anastomosed to inferior vena cava in host caudal; graft was transplanted into the space under the host liver, part of receivers relieved portal vein angiography and color Doppler flow imaging was performed 3 days after surgery. Liver function of double livers in relievers was checked up, 3 days and 1 week after surgery respectively. Results: After surgery 10 relievers survived over 1 week, blood enzymology from hepatic vein of grafts 1 week after surgery were not ameliorative significantly compared with those 3 days after surgery (P > 0.05). Blood enzymology indexes from hepatic veins of grafts 1 week after surgery were were improved significantly compared with 3 days after surgery (P < 0.05). The graft did not reveal atrophic and gained favorable function. Conclusion: Favorable regeneration in the auxiliary partial liver transplantation model has achieved. Ideal foundation has been established for simulating and investigating human auxiliary liver transplantation. (authors)
Pravinraj, T.; Patrikar, Rajendra
2017-07-01
Partial wetting surfaces and its influence on the droplet movement of micro and nano scale being contemplated for many useful applications. The dynamics of the droplet usually analyzed with a multiphase lattice Boltzmann method (LBM). In this paper, the influence of partial wetting surface on the dynamics of droplet is systematically analyzed for various cases. Splitting of droplets due to chemical gradient of the surface is studied and analyses of splitting time for various widths of the strips for different Weber numbers are computed. With the proposed model one can tune the splitting volume and time by carefully choosing a strip width and droplet position. The droplet spreading on chemically heterogeneous surfaces shows that the spreading can be controlled not only by parameters of Weber number but also by tuning strip width ratio. The transportation of the droplet from hydrophobic surface to hydrophilic surface due to chemical gradient is simulated and analyzed using our hybrid thermodynamic-image processing technique. The results prove that with the progress of time the surface free energy decreases with increase in spreading area. Finally, the transportation of a droplet on microstructure gradient is demonstrated. The model explains the temporal behaviour of droplet during the spreading, recoiling and translation along with tracking of contact angle hysteresis phenomenon.
Bakker, Mark
2001-05-01
An analytic, approximate solution is derived for the modeling of three-dimensional flow to partially penetrating wells. The solution is written in terms of a correction on the solution for a fully penetrating well and is obtained by dividing the aquifer up, locally, in a number of aquifer layers. The resulting system of differential equations is solved by application of the theory for multiaquifer flow. The presented approach has three major benefits. First, the solution may be applied to any groundwater model that can simulate flow to a fully penetrating well; the solution may be superimposed onto the solution for the fully penetrating well to simulate the local three-dimensional drawdown and flow field. Second, the approach is applicable to isotropic, anisotropic, and stratified aquifers and to both confined and unconfined flow. Third, the solution extends over a small area around the well only; outside this area the three-dimensional effect of the partially penetrating well is negligible, and no correction to the fully penetrating well is needed. A number of comparisons are made to existing three-dimensional, analytic solutions, including radial confined and unconfined flow and a well in a uniform flow field. It is shown that a subdivision in three layers is accurate for many practical cases; very accurate solutions are obtained with more layers.
[Partial nucleotomy of the ovine disc as an in vivo model for disc degeneration].
Guder, E; Hill, S; Kandziora, F; Schnake, K J
2009-01-01
The aim of this study was to develop a suitable animal model for the clinical situation of progressive disc degeneration after microsurgical nucleotomy. Twenty sheep underwent standardised partial anterolateral nucleotomy at lumbar segment 3/4. After randomisation, 10 animals were sacrificed after 12 weeks (group 1). The remainder was sacrificed after 48 weeks (group 2). For radiological examination X-rays, MRI and post-mortem CT scans were performed. Lumbar discs L 3/4 with adjacent subchondral trabecular bone were harvested and analysed macroscopically and histologically. An image-analysing computer program was used to measure histomorphometric indices of bone structure. 17 segments could be evaluated. After 12 weeks (group 1) histological and radiological degenerative disc changes were noted. After 48 weeks (group 2), radiological signs in MRI reached statistical significance. Furthermore, group 2 showed significantly more osteophyte formations in CT scans. Histomorphometric changes of the disc and the adjacent vertebral bone structure suggest a significant progressive degenerative remodelling. The facet joints did not show any osteoarthrosis after 48 weeks. Partial nucleotomy of the ovine lumbar disc leads to radiological and histological signs of disc degeneration similar to those seen in humans after microsurgical nucleotomy. The presented in vivo model may be useful to evaluate new orthopaedic treatment strategies.
Tricriticality in the q-neighbor Ising model on a partially duplex clique.
Chmiel, Anna; Sienkiewicz, Julian; Sznajd-Weron, Katarzyna
2017-12-01
We analyze a modified kinetic Ising model, a so-called q-neighbor Ising model, with Metropolis dynamics [Phys. Rev. E 92, 052105 (2015)PLEEE81539-375510.1103/PhysRevE.92.052105] on a duplex clique and a partially duplex clique. In the q-neighbor Ising model each spin interacts only with q spins randomly chosen from its whole neighborhood. In the case of a duplex clique the change of a spin is allowed only if both levels simultaneously induce this change. Due to the mean-field-like nature of the model we are able to derive the analytic form of transition probabilities and solve the corresponding master equation. The existence of the second level changes dramatically the character of the phase transition. In the case of the monoplex clique, the q-neighbor Ising model exhibits a continuous phase transition for q=3, discontinuous phase transition for q≥4, and for q=1 and q=2 the phase transition is not observed. On the other hand, in the case of the duplex clique continuous phase transitions are observed for all values of q, even for q=1 and q=2. Subsequently we introduce a partially duplex clique, parametrized by r∈[0,1], which allows us to tune the network from monoplex (r=0) to duplex (r=1). Such a generalized topology, in which a fraction r of all nodes appear on both levels, allows us to obtain the critical value of r=r^{*}(q) at which a tricriticality (switch from continuous to discontinuous phase transition) appears.
Ordering kinetics in model systems with inhibited interfacial adsorption
DEFF Research Database (Denmark)
Willart, J.-F.; Mouritsen, Ole G.; Naudts, J.
1992-01-01
. The results are related to experimental work on ordering processes in orientational glasses. It is suggested that the experimental observation of very slow ordering kinetics in, e.g., glassy crystals of cyanoadamantane may be a consequence of low-temperature activated processes which ultimately lead...
Abnormal Waves Modelled as Second-order Conditional Waves
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
2005-01-01
The paper presents results for the expected second order short-crested wave conditional of a given wave crest at a specific point in time and space. The analysis is based on the second order Sharma and Dean shallow water wave theory. Numerical results showing the importance of the spectral densit...
State reduced order models for the modelling of the thermal behavior of buildings
Energy Technology Data Exchange (ETDEWEB)
Menezo, Christophe; Bouia, Hassan; Roux, Jean-Jacques; Depecker, Patrick [Institute National de Sciences Appliquees de Lyon, Villeurbanne Cedex, (France). Centre de Thermique de Lyon (CETHIL). Equipe Thermique du Batiment]. E-mail: menezo@insa-cethil-etb.insa-lyon.fr; bouia@insa-cethil-etb.insa-lyon.fr; roux@insa-cethil-etb.insa-lyon.fr; depecker@insa-cethil-etb.insa-lyon.fr
2000-07-01
This work is devoted to the field of building physics and related to the reduction of heat conduction models. The aim is to enlarge the model libraries of heat and mass transfer codes through limiting the considerable dimensions reached by the numerical systems during the modelling process of a multizone building. We show that the balanced realization technique, specifically adapted to the coupling of reduced order models with the other thermal phenomena, turns out to be very efficient. (author)
Phase behavior and reactive transport of partial melt in heterogeneous mantle model
Jordan, J.; Hesse, M. A.
2013-12-01
The reactive transport of partial melt is the key process that leads to the chemical and physical differentiation of terrestrial planets and smaller celestial bodies. The essential role of the lithological heterogeneities during partial melting of the mantle is increasingly recognized. How far can enriched melts propagate while interacting with the ambient mantle? Can the melt flow emanating from a fertile heterogeneity be localized through a reactive infiltration feedback in a model without exogenous factors or contrived initial conditions? A full understanding of the role of heterogeneities requires reactive melt transport models that account for the phase behavior of major elements. Previous work on reactive transport in the mantle focuses on trace element partitioning; we present the first nonlinear chromatographic analysis of reactive melt transport in systems with binary solid solution. Our analysis shows that reactive melt transport in systems with binary solid solution leads to the formation of two separate reaction fronts: a slow melting/freezing front along which enthalpy change is dominant and a fast dissolution/precipitation front along which compositional changes are dominated by an ion-exchange process over enthalpy change. An intermediate state forms between these two fronts with a bulk-rock composition and enthalpy that are not necessarily bounded by the bulk-rock composition and enthalpy of either the enriched heterogeneity or the depleted ambient mantle. The formation of this intermediate state makes it difficult to anticipate the porosity changes and hence the stability of reaction fronts. Therefore, we develop a graphical representation for the solution that allows identification of the intermediate state by inspection, for all possible bulk-rock compositions and enthalpies of the heterogeneity and the ambient mantle. We apply the analysis to the partial melting of an enriched heterogeneity. This leads to the formation of moving precipitation
Jaggi, Chandra K.; Khanna, Aditi; Verma, Priyanka
2011-07-01
In today's business transactions, there are various reasons, namely, bulk purchase discounts, re-ordering costs, seasonality of products, inflation induced demand, etc., which force the buyer to order more than the warehouse capacity. Such situations call for additional storage space to store the excess units purchased. This additional storage space is typically a rented warehouse. Inflation plays a very interesting and significant role here: It increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organisation prefers to keep a higher inventory, thereby increasing the aggregate demand. This additional inventory needs additional storage space, which is facilitated by a rented warehouse. Ignoring the effects of the time value of money and inflation might yield misleading results. In this study, a two-warehouse inventory model with linear trend in demand under inflationary conditions having different rates of deterioration has been developed. Shortages at the owned warehouse are also allowed subject to partial backlogging. The solution methodology provided in the model helps to decide on the feasibility of renting a warehouse. Finally, findings have been illustrated with the help of numerical examples. Comprehensive sensitivity analysis has also been provided.
Jaza Folefack, Achille Jean
2009-05-01
This paper analyses the possibility of substitution between compost and mineral fertilizer in order to assess the impact on the foreign exchange savings in Cameroon of increasing the use of compost. In this regard, a partial equilibrium model was built up and used as a tool for policy simulations. The review of existing literature already suggests that, the compost commercial value i.e. value of substitution (33,740 FCFA tonne(-1)) is higher compared to the compost real price (30,000 FCFA tonne(-1)), proving that it could be profitable to substitute the mineral fertilizer by compost. Further results from the scenarios used in the modelling exercise show that, increasing the compost availability is the most favourable policy for the substitution of mineral fertilizer by compost. This policy helps to save about 18.55% of the annual imported mineral fertilizer quantity and thus to avoid approximately 8.47% of the yearly total import expenditure in Cameroon. The policy of decreasing the transport rate of compost in regions that are far from the city is also favourable to the substitution. Therefore, in order to encourage the substitution of mineral fertilizer by compost, programmes of popularization of compost should be highlighted and be among the top priorities in the agricultural policy of the Cameroon government.
A Novel Method for Decoding Any High-Order Hidden Markov Model
Directory of Open Access Journals (Sweden)
Fei Ye
2014-01-01
Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.
Oscillator strength of partially ionized high-Z atom on Hartree-Fock Slater model
International Nuclear Information System (INIS)
Nakamura, S.; Nishikawa, T.; Takabe, H.; Mima, K.
1991-01-01
The Hartree-Fock Slater (HFS) model has been solved for the partially ionized gold ions generated when an intense laser light is irradiated on a gold foil target. The resultant energy levels are compared with those obtained by a simple screened hydrogenic model with l-splitting effect (SHML). It is shown that the energy levels are poorly model by SHML as the ionization level becomes higher. The resultant wave functions are used to evaluate oscillator strength of important line radiations and compared with those obtained by a simple model using hydrogenic wave functions. Its demonstrated that oscillator strength of the 4p-4d and 4d-4f lines are well modeled by the simple method, while the 4-5 transitions such as 4f-5g, 4d-5f, 4p-5d, and 4f-5p forming the so-called N-band emission are poorly modeled and HFS results less strong line emissions. (author)
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Yong-Hong Zhang
2015-05-01
Full Text Available Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI. The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14. The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs.
Cheng, Guang
2014-02-01
We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based on a spline approximation of the nonparametric part of the model and the generalized estimating equations (GEE). Although the model in consideration is natural and useful in many practical applications, the literature on this model is very limited because of challenges in dealing with dependent data for nonparametric additive models. We show that the proposed estimators are consistent and asymptotically normal even if the covariance structure is misspecified. An explicit consistent estimate of the asymptotic variance is also provided. Moreover, we derive the semiparametric efficiency score and information bound under general moment conditions. By showing that our estimators achieve the semiparametric information bound, we effectively establish their efficiency in a stronger sense than what is typically considered for GEE. The derivation of our asymptotic results relies heavily on the empirical processes tools that we develop for the longitudinal/clustered data. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2014 ISI/BS.
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S. Fournier
2017-01-01
Full Text Available A numerical model based on equivalent electrical networks has been built to simulate the dynamic behavior of a positive-displacement MEMS micropump dedicated to insulin delivery. This device comprises a reservoir in direct communication with the inlet check valve, a pumping membrane actuated by a piezo actuator, two integrated piezoresistive pressure sensors, an anti-free-flow check valve at the outlet, and finally a fluidic pathway up to the patient cannula. The pressure profiles delivered by the sensors are continuously analyzed during the therapy in order to detect failures like occlusion. The numerical modeling is a reliable way to better understand the behavior of the micropump in case of failure. The experimental pressure profiles measured during the actuation phase have been used to validate the numerical modeling. The effect of partial occlusion on the pressure profiles has been also simulated. Based on this analysis, a new management of partial occlusion for MEMS micropump is finally proposed.
Development and Validity of a Silicone Renal Tumor Model for Robotic Partial Nephrectomy Training.
Monda, Steven M; Weese, Jonathan R; Anderson, Barrett G; Vetter, Joel M; Venkatesh, Ramakrishna; Du, Kefu; Andriole, Gerald L; Figenshau, Robert S
2018-04-01
To provide a training tool to address the technical challenges of robot-assisted laparoscopic partial nephrectomy, we created silicone renal tumor models using 3-dimensional printed molds of a patient's kidney with a mass. In this study, we assessed the face, content, and construct validity of these models. Surgeons of different training levels completed 4 simulations on silicone renal tumor models. Participants were surveyed on the usefulness and realism of the model as a training tool. Performance was measured using operation-specific metrics, self-reported operative demands (NASA Task Load Index [NASA TLX]), and blinded expert assessment (Global Evaluative Assessment of Robotic Surgeons [GEARS]). Twenty-four participants included attending urologists, endourology fellows, urology residents, and medical students. Post-training surveys of expert participants yielded mean results of 79.2 on the realism of the model's overall feel and 90.2 on the model's overall usefulness for training. Renal artery clamp times and GEARS scores were significantly better in surgeons further in training (P ≤.005 and P ≤.025). Renal artery clamp times, preserved renal parenchyma, positive margins, NASA TLX, and GEARS scores were all found to improve across trials (P <.001, P = .025, P = .024, P ≤.020, and P ≤.006, respectively). Face, content, and construct validity were demonstrated in the use of a silicone renal tumor model in a cohort of surgeons of different training levels. Expert participants deemed the model useful and realistic. Surgeons of higher training levels performed better than less experienced surgeons in various study metrics, and improvements within individuals were observed over sequential trials. Future studies should aim to assess model predictive validity, namely, the association between model performance improvements and improvements in live surgery. Copyright © 2018 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Christer Dalen
2017-10-01
Full Text Available A model reduction technique based on optimization theory is presented, where a possible higher order system/model is approximated with an unstable DIPTD model by using only step response data. The DIPTD model is used to tune PD/PID controllers for the underlying possible higher order system. Numerous examples are used to illustrate the theory, i.e. both linear and nonlinear models. The Pareto Optimal controller is used as a reference controller.
Ghost imaging and its visibility with partially coherent elliptical Gaussian Schell-model beams
International Nuclear Information System (INIS)
Luo, Meilan; Zhu, Weiting; Zhao, Daomu
2015-01-01
The performances of the ghost image and the visibility with partially coherent elliptical Gaussian Schell-model beams have been studied. In that case we have derived the condition under which the goal ghost image is achievable. Furthermore, the visibility is assessed in terms of the parameters related to the source to find that the visibility reduces with the increase of the beam size, while it is a monotonic increasing function of the transverse coherence length. More specifically, it is found that the inequalities of the source sizes in x and y directions, as well as the transverse coherence lengths, play an important role in the ghost image and the visibility. - Highlights: • We studied the ghost image and visibility with partially coherent EGSM beams. • We derived the condition under which the goal ghost image is achievable. • The visibility is assessed in terms of the parameters related to the source. • The source sizes and coherence lengths play role in the ghost image and visibility.
Gamma-Ray Emission Tomography: Modeling and Evaluation of Partial-Defect Testing Capabilities
International Nuclear Information System (INIS)
Jacobsson Svard, S.; Jansson, P.; Davour, A.; Grape, S.; White, T.A.; Smith, L.E.; Deshmukh, N.; Wittman, R.S.; Mozin, V.; Trellue, H.
2015-01-01
Gamma emission tomography (GET) for spent nuclear fuel verification is the subject for IAEA MSP project JNT1955. In line with IAEA Safeguards R&D plan 2012-2023, the aim of this effort is to ''develop more sensitive and less intrusive alternatives to existing NDA instruments to perform partial defect test on spent fuel assembly prior to transfer to difficult to access storage''. The current viability study constitutes the first phase of three, with evaluation and decision points between each phase. Two verification objectives have been identified; (1) counting of fuel pins in tomographic images without any a priori knowledge of the fuel assembly under study, and (2) quantitative measurements of pinby- pin properties, e.g., burnup, for the detection of anomalies and/or verification of operator-declared data. Previous measurements performed in Sweden and Finland have proven GET highly promising for detecting removed or substituted fuel rods in BWR and VVER-440 fuel assemblies even down to the individual fuel rod level. The current project adds to previous experiences by pursuing a quantitative assessment of the capabilities of GET for partial defect detection, across a broad range of potential IAEA applications, fuel types and fuel parameters. A modelling and performance-evaluation framework has been developed to provide quantitative GET performance predictions, incorporating burn-up and cooling-time calculations, Monte Carlo radiation-transport and detector-response modelling, GET instrument definitions (existing and notional) and tomographic reconstruction algorithms, which use recorded gamma-ray intensities to produce images of the fuel's internal source distribution or conclusive rod-by-rod data. The framework also comprises image-processing algorithms and performance metrics that recognize the inherent tradeoff between the probability of detecting missing pins and the false-alarm rate. Here, the modelling and analysis framework is
Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.
2012-08-01
Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.
Real-time characterization of partially observed epidemics using surrogate models.
Energy Technology Data Exchange (ETDEWEB)
Safta, Cosmin; Ray, Jaideep; Lefantzi, Sophia; Crary, David (Applied Research Associates, Arlington, VA); Sargsyan, Khachik; Cheng, Karen (Applied Research Associates, Arlington, VA)
2011-09-01
We present a statistical method, predicated on the use of surrogate models, for the 'real-time' characterization of partially observed epidemics. Observations consist of counts of symptomatic patients, diagnosed with the disease, that may be available in the early epoch of an ongoing outbreak. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information on the dynamics of the etiologic agent in the affected population e.g., the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and epidemiological parameters are estimated as distributions using a Markov chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. In some cases, the inverse problem can be computationally expensive, primarily due to the epidemic simulator used inside the inversion algorithm. We present a method, based on replacing the epidemiological model with computationally inexpensive surrogates, that can reduce the computational time to minutes, without a significant loss of accuracy. The surrogates are created by projecting the output of an epidemiological model on a set of polynomial chaos bases; thereafter, computations involving the surrogate model reduce to evaluations of a polynomial. We find that the epidemic characterizations obtained with the surrogate models is very close to that obtained with the original model. We also find that the number of projections required to construct a surrogate model is O(10)-O(10{sup 2}) less than the number of samples required by the MCMC to construct a stationary posterior distribution; thus, depending upon the epidemiological models in question, it may be possible to omit the offline creation and caching of surrogate models, prior to their use in an inverse problem. The technique is demonstrated on synthetic data as well as
Directory of Open Access Journals (Sweden)
Toran Pour Alireza
2016-01-01
Full Text Available Pedestrian crashes account for 11% of all reported traffic crashes in Melbourne metropolitan area between 2004 and 2013. There are very limited studies on pedestrian accidents at mid-blocks. Mid-block crashes account for about 46% of the total pedestrian crashes in Melbourne metropolitan area. Meanwhile, about 50% of all pedestrian fatalities occur at mid-blocks. In this research, Partial Proportional Odds (PPO model is applied to examine vehicle-pedestrian crash severity at mid-blocks in Melbourne metropolitan area. The PPO model is a logistic regression model that allows the covariates that meet the proportional odds assumption to affect different crash severity levels with the same magnitude; whereas the covariates that do not meet the proportional odds assumption can have different effects on different severity levels. In this research vehicle-pedestrian crashes at mid-blocks are analysed for first time. In addition, some factors such as distance of crashes to public transport stops, average road slope and some social characteristics are considered to develop the model in this research for first time. Results of PPO model show that speed limit, light condition, pedestrian age and gender, and vehicle type are the most significant factors that influence vehicle-pedestrian crash severity at mid-blocks.
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Margaretha Ohyver
2016-12-01
Full Text Available Partial Least Squares (PLS method was developed in 1960 by Herman Wold. The method particularly suits with construct a regression model when the number of independent variables is many and highly collinear. The PLS can be combined with other methods, one of which is a Continuous Wavelet Transformation (CWT. By considering that the presence of outliers can lead to a less reliable model, and this kind of transformation may be required at a stage of pre-processing, the data is free of noise or outliers. Based on the previous study, Kendari hotel room occupancy rate was affected by the outlier, and it had a low value of R2. Therefore, this research aimed to obtain a good model by combining the PLS method and CWT transformation using the Mexican Hats them other wavelet of CWT. The research concludes that merging the PLS and the Mexican Hat transformation has resulted in a better model compared to the model that combined the PLS and the Haar wavelet transformation as shown in the previous study. The research shows that by changing the mother of the wavelet, the value of R2 can be improved significantly. The result provides information on how to increase the value of R2. The other advantage is the information for hotel managements to notice the age of the hotel, the maximum rates, the facilities, and the number of rooms to increase the number of visitors.
Bilinear reduced order approximate model of parabolic distributed solar collectors
Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem
2015-01-01
This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low
Continuum Kinetic Plasma Modeling Using a Conservative 4th-Order Method with AMR
Vogman, Genia; Colella, Phillip
2012-10-01
When the number of particles in a Debye sphere is large, a plasma can be accurately represented by a distribution function, which can be treated as a continuous incompressible fluid in phase space. In the most general case the evolution of such a distribution function is described by the 6D Boltzmann-Maxwell partial differential equation system. To address the challenges associated with solving a 6D hyperbolic governing equation, a simpler 3D Vlasov-Poisson system is considered. A 4th-order accurate Vlasov-Poisson model has been developed in one spatial and two velocity dimensions. The governing equation is cast in conservation law form and is solved with a finite volume representation. Adaptive mesh refinement (AMR) is used to allow for efficient use of computational resources while maintaining desired levels of resolution. The model employs a flux limiter to remedy non-physical effects such as numerical dispersion. The model is tested on the two-stream, beam-plasma, and Dory-Guest-Harris instabilities. All results are compared with linear theory.
Zhang, K.; Ghobadian, A.; Nouri, J. M.
2017-01-01
A comparative study of two combustion models based on non-premixed assumption and partially premixed assumptions using the overall models of Zimont Turbulent Flame Speed Closure Method (ZTFSC) and Extended Coherent Flamelet Method (ECFM) are conducted through Reynolds stress turbulence modelling of Tay model gas turbine combustor for the first time. The Tay model combustor retains all essential features of a realistic gas turbine combustor. It is seen that the non-premixed combustion model fa...
The use of partial least squares path modeling in international marketing
Henseler, Jörg; Ringle, Christian M.; Sinkovics, Rudolf R.
2009-01-01
In order to determine the status quo of PLS path modeling in international marketing research, we conducted an exhaustive literature review. An evaluation of double-blind reviewed journals through important academic publishing databases (e.g., ABI/Inform, Elsevier ScienceDirect, Emerald Insight,
Markopoulou, Catherine K; Kouskoura, Maria G; Koundourellis, John E
2011-06-01
Twenty-five descriptors and 61 structurally different analytes have been used on a partial least squares (PLS) to latent structure technique in order to study chromatographically their interaction mechanism on a phenyl column. According to the model, 240 different retention times of the analytes, expressed as Y variable (log k), at different % MeOH mobile-phase concentrations have been correlated with their theoretical most important structural or molecular descriptors. The goodness-of-fit was estimated by the coefficient of multiple determinations r(2) (0.919), and the root mean square error of estimation (RMSEE=0.1283) values with a predictive ability (Q(2)) of 0.901. The model was further validated using cross-validation (CV), validated by 20 response permutations r(2) (0.0, 0.0146), Q(2) (0.0, -0.136) and validated by external prediction. The contribution of certain mechanism interactions between the analytes, the mobile phase and the column, proportional or counterbalancing is also studied. Trying to evaluate the influence on Y of every variable in a PLS model, VIP (variables importance in the projection) plot provides evidence that lipophilicity (expressed as Log D, Log P), polarizability, refractivity and the eluting power of the mobile phase are dominant in the retention mechanism on a phenyl column. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Zhi MJ
2017-09-01
Full Text Available Mu-Jun Zhi,1,2,* Kun Liu,1,* Zhou-Li Zheng,1,3 Xun He,1 Tie Li,2 Guang Sun,1,2 Meng Zhang,4 Fu-Chun Wang,2 Xin-Yan Gao,1 Bing Zhu1 1Department of Physiology, Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 2College of Acupuncture and Moxibustion, Changchun University of Chinese Medicine, Changchun, People’s Republic of China; 3College of Acupuncture and Moxibution, Shaanxi University of Chinese Medicine, People’s Republic of China; 4Department of Chinese Medicine, Dongli Hospital of Traditional Chinese Medicine, Tianjin, People’s Republic of China *These authors contributed equally to this work Purpose: To validate and explore the application of a rat model of chronic constriction injury to the partial sciatic nerve in investigation of acupuncture analgesia.Methods: Chronic constriction injury of the sciatic nerve (CCI and chronic constriction injury of the partial sciatic nerve (CCIp models were generated by ligating either the sciatic nerve trunk or its branches in rats. Both models were evaluated via paw mechanical withdrawal latency (PMWL, paw mechanical withdrawal threshold (PMWT, nociceptive reflex-induced electromyogram (C-fiber reflex EMG, and dorsal root ganglion immunohistochemistry. Electroacupuncture (EA was performed at GB30 to study the analgesic effects on neuropathic pain and the underlying mechanisms.Results: Following ligation of the common peroneal and tibial nerves, CCIp rats exhibited hindlimb dysfunction, hind paw shrinkage and lameness, mirroring those of CCI rats (generated by ligating the sciatic nerve trunk. Compared to presurgery measurements, CCIp and CCI modeling significantly decreased the PMWL and PMWT. EA at GB30 increased the PMWL and PMWT in both CCI and CCIp rats. Calcitonin gene-related polypeptide and substance P expressions were apparently increased in both CCI and CCIp groups, but were not different from each other. The C
Qin, Guoyou; Zhang, Jiajia; Zhu, Zhongyi; Fung, Wing
2016-12-20
Outliers, measurement error, and missing data are commonly seen in longitudinal data because of its data collection process. However, no method can address all three of these issues simultaneously. This paper focuses on the robust estimation of partially linear models for longitudinal data with dropouts and measurement error. A new robust estimating equation, simultaneously tackling outliers, measurement error, and missingness, is proposed. The asymptotic properties of the proposed estimator are established under some regularity conditions. The proposed method is easy to implement in practice by utilizing the existing standard generalized estimating equations algorithms. The comprehensive simulation studies show the strength of the proposed method in dealing with longitudinal data with all three features. Finally, the proposed method is applied to data from the Lifestyle Education for Activity and Nutrition study and confirms the effectiveness of the intervention in producing weight loss at month 9. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Agrawal, Shelesh; Seuntjens, Dries; Cocker, Pieter De; Lackner, Susanne; Vlaeminck, Siegfried E
2018-04-01
Twenty years ago, mainstream partial nitritation/anammox (PN/A) was conceptually proposed as pivotal for a more sustainable treatment of municipal wastewater. Its economic potential spurred research, yet practice awaits a comprehensive recipe for microbial resource management. Implementing mainstream PN/A requires transferable and operable ways to steer microbial competition as to meet discharge requirements on a year-round basis at satisfactory conversion rates. In essence, the competition for nitrogen, organic carbon and oxygen is grouped into 'ON/OFF' (suppression/promotion) and 'IN/OUT' (wash-out/retention and seeding) strategies, selecting for desirable conversions and microbes. Some insights need mechanistic understanding, while empirical observations suffice elsewhere. The provided methodological R&D framework integrates insights in engineering, microbiome and modeling. Such synergism should catalyze the implementation of energy-positive sewage treatment. Copyright © 2018 Elsevier Ltd. All rights reserved.
New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models
Directory of Open Access Journals (Sweden)
Yunbei Ma
2014-01-01
Full Text Available In biomedical research, one major objective is to identify risk factors and study their risk impacts, as this identification can help clinicians to both properly make a decision and increase efficiency of treatments and resource allocation. A two-step penalized-based procedure is proposed to select linear regression coefficients for linear components and to identify significant nonparametric varying-coefficient functions for semiparametric varying-coefficient partially linear Cox models. It is shown that the penalized-based resulting estimators of the linear regression coefficients are asymptotically normal and have oracle properties, and the resulting estimators of the varying-coefficient functions have optimal convergence rates. A simulation study and an empirical example are presented for illustration.
CMS Partial Releases Model, Tools, and Applications. Online and Framework-Light Releases
Jones, Christopher D; Meschi, Emilio; Shahzad Muzaffar; Andreas Pfeiffer; Ratnikova, Natalia; Sexton-Kennedy, Elizabeth
2009-01-01
The CMS Software project CMSSW embraces more than a thousand packages organized in subsystems for analysis, event display, reconstruction, simulation, detector description, data formats, framework, utilities and tools. The release integration process is highly automated by using tools developed or adopted by CMS. Packaging in rpm format is a built-in step in the software build process. For several well-defined applications it is highly desirable to have only a subset of the CMSSW full package bundle. For example, High Level Trigger algorithms that run on the Online farm, and need to be rebuilt in a special way, require no simulation, event display, or analysis packages. Physics analysis applications in Root environment require only a few core libraries and the description of CMS specific data formats. We present a model of CMS Partial Releases, used for preparation of the customized CMS software builds, including description of the tools used, the implementation, and how we deal with technical challenges, suc...
Arfawi Kurdhi, Nughthoh; Adi Diwiryo, Toray; Sutanto
2016-02-01
This paper presents an integrated single-vendor two-buyer production-inventory model with stochastic demand and service level constraints. Shortage is permitted in the model, and partial backordered partial lost sale. The lead time demand is assumed follows a normal distribution and the lead time can be reduced by adding crashing cost. The lead time and ordering cost reductions are interdependent with logaritmic function relationship. A service level constraint policy corresponding to each buyer is considered in the model in order to limit the level of inventory shortages. The purpose of this research is to minimize joint total cost inventory model by finding the optimal order quantity, safety stock, lead time, and the number of lots delivered in one production run. The optimal production-inventory policy gained by the Lagrange method is shaped to account for the service level restrictions. Finally, a numerical example and effects of the key parameters are performed to illustrate the results of the proposed model.
Maxworthy, T.
1997-08-01
A simple three-layer model of the dynamics of partially enclosed seas, driven by a surface buoyancy flux, is presented. It contains two major elements, a hydraulic constraint at the exit contraction and friction in the interior of the main body of the sea; both together determine the vertical structure and magnitudes of the interior flow variables, i.e. velocity and density. Application of the model to the large-scale dynamics of the Red Sea gives results that are not in disagreement with observation once the model is applied, also, to predict the dense outflow from the Gulf of Suez. The latter appears to be the agent responsible for the formation of dense bottom water in this system. Also, the model is reasonably successful in predicting the density of the outflow from the Persian Gulf, and can be applied to any number of other examples of convectively driven flow in long, narrow channels, with or without sills and constrictions at their exits.
Nitrous Oxide Production in a Granule-based Partial Nitritation Reactor: A Model-based Evaluation.
Peng, Lai; Sun, Jing; Liu, Yiwen; Dai, Xiaohu; Ni, Bing-Jie
2017-04-03
Sustainable wastewater treatment has been attracting increasing attentions over the past decades. However, the production of nitrous oxide (N 2 O), a potent GHG, from the energy-efficient granule-based autotrophic nitrogen removal is largely unknown. This study applied a previously established N 2 O model, which incorporated two N 2 O production pathways by ammonia-oxidizing bacteria (AOB) (AOB denitrification and the hydroxylamine (NH 2 OH) oxidation). The two-pathway model was used to describe N 2 O production from a granule-based partial nitritation (PN) reactor and provide insights into the N 2 O distribution inside granules. The model was evaluated by comparing simulation results with N 2 O monitoring profiles as well as isotopic measurement data from the PN reactor. The model demonstrated its good predictive ability against N 2 O dynamics and provided useful information about the shift of N 2 O production pathways inside granules for the first time. The simulation results indicated that the increase of oxygen concentration and granule size would significantly enhance N 2 O production. The results further revealed a linear relationship between N 2 O production and ammonia oxidation rate (AOR) (R 2 = 0.99) under the conditions of varying oxygen levels and granule diameters, suggesting that bulk oxygen and granule size may exert an indirect effect on N 2 O production by causing a change in AOR.
International Nuclear Information System (INIS)
Ng, Felix S.L.
2016-01-01
We develop a statistical-mechanical model of one-dimensional normal grain growth that does not require any drift-velocity parameterization for grain size, such as used in the continuity equation of traditional mean-field theories. The model tracks the population by considering grain sizes in neighbour pairs; the probability of a pair having neighbours of certain sizes is determined by the size-frequency distribution of all pairs. Accordingly, the evolution obeys a partial integro-differential equation (PIDE) over ‘grain size versus neighbour grain size’ space, so that the grain-size distribution is a projection of the PIDE's solution. This model, which is applicable before as well as after statistically self-similar grain growth has been reached, shows that the traditional continuity equation is invalid outside this state. During statistically self-similar growth, the PIDE correctly predicts the coarsening rate, invariant grain-size distribution and spatial grain size correlations observed in direct simulations. The PIDE is then reducible to the standard continuity equation, and we derive an explicit expression for the drift velocity. It should be possible to formulate similar parameterization-free models of normal grain growth in two and three dimensions.
Modeling of strongly heat-driven flow in partially saturated fractured porous media
International Nuclear Information System (INIS)
Pruess, K.; Tsang, Y.W.; Wang, J.S.Y.
1985-01-01
The authors have performed modeling studies on the simultaneous transport of heat, liquid water, vapor, and air in partially saturated fractured porous media, with particular emphasis on strongly heat-driven flow. The presence of fractures makes the transport problem very complex, both in terms of flow geometry and physics. The numerical simulator used for their flow calculations takes into account most of the physical effects which are important in multi-phase fluid and heat flow. It has provisions to handle the extreme non-linearities which arise in phase transitions, component disappearances, and capillary discontinuities at fracture faces. They model a region around an infinite linear string of nuclear waste canisters, taking into account both the discrete fractures and the porous matrix. From an analysis of the results obtained with explicit fractures, they develop equivalent continuum models which can reproduce the temperature, saturation, and pressure variation, and gas and liquid flow rates of the discrete fracture-porous matrix calculations. The equivalent continuum approach makes use of a generalized relative permeability concept to take into account the fracture effects. This results in a substantial simplification of the flow problem which makes larger scale modeling of complicated unsaturated fractured porous systems feasible. Potential applications for regional scale simulations and limitations of the continuum approach are discussed. 27 references, 13 figures, 2 tables
International Nuclear Information System (INIS)
Wang, J.S.Y.; Narasimhan, T.N.
1993-06-01
This report discusses conceptual models and mathematical equations, analyzes distributions and correlations among hydrological parameters of soils and tuff, introduces new path integration approaches, and outlines scaling procedures to model potential-driven fluid flow in heterogeneous media. To properly model the transition from fracture-dominated flow under saturated conditions to matrix-dominated flow under partially saturated conditions, characteristic curves and permeability functions for fractures and matrix need to be improved and validated. Couplings from two-phase flow, heat transfer, solute transport, and rock deformation to liquid flow are also important. For stochastic modeling of alternating units of welded and nonwelded tuff or formations bounded by fault zones, correlations and constraints on average values of saturated permeability and air entry scaling factor between different units need to be imposed to avoid unlikely combinations of parameters and predictions. Large-scale simulations require efficient and verifiable numerical algorithms. New path integration approaches based on postulates of minimum work and mass conservation to solve flow geometry and potential distribution simultaneously are introduced. This verifiable integral approach, together with fractal scaling procedures to generate statistical realizations with parameter distribution, correlation, and scaling taken into account, can be used to quantify uncertainties and generate the cumulative distribution function for groundwater travel times
Internalisation of external costs in the Polish power generation sector: A partial equilibrium model
International Nuclear Information System (INIS)
Kudelko, Mariusz
2006-01-01
This paper presents a methodical framework, which is the basis for the economic analysis of the mid-term planning of development of the Polish energy system. The description of the partial equilibrium model and its results are demonstrated for different scenarios applied. The model predicts the generation, investment and pricing of mid-term decisions that refer to the Polish electricity and heat markets. The current structure of the Polish energy sector is characterised by interactions between the supply and demand sides of the energy sector. The supply side regards possibilities to deliver fuels from domestic and import sources and their conversion through transformation processes. Public power plants, public CHP plants, industry CHP plants and municipal heat plants represent the main producers of energy in Poland. Demand is characterised by the major energy consumers, i.e. industry and construction, transport, agriculture, trade and services, individual consumers and export. The relationships between the domestic electricity and heat markets are modelled taking into account external costs estimates. The volume and structure of energy production, electricity and heat prices, emissions, external costs and social welfare of different scenarios are presented. Results of the model demonstrate that the internalisation of external costs through the increase in energy prices implies significant improvement in social welfare
Modeling of strongly heat-driven flow in partially saturated fractured porous media
International Nuclear Information System (INIS)
Pruess, K.; Tsang, Y.W.; Wang, J.S.Y.
1984-10-01
We have performed modeling studies on the simultaneous transport of heat, liquid water, vapor, and air in partially saturated fractured porous media, with particular emphasis on strongly heat-driven flow. The presence of fractures makes the transport problem very complex, both in terms of flow geometry and physics. The numerical simulator used for our flow calculations takes into account most of the physical effects which are important in multi-phase fluid and heat flow. It has provisions to handle the extreme non-linearities which arise in phase transitions, component disappearances, and capillary discontinuities at fracture faces. We model a region around an infinite linear string of nuclear waste canisters, taking into account both the discrete fractures and the porous matrix. From an analysis of the results obtained with explicit fractures, we develop equivalent continuum models which can reproduce the temperature, saturation, and pressure variation, and gas and liquid flow rates of the discrete fracture-porous matrix calculations. The equivalent continuum approach makes use of a generalized relative permeability concept to take into account for fracture effects. This results in a substantial simplification of the flow problem which makes larger scale modeling of complicated unsaturated fractured porous systems feasible. Potential applications for regional scale simulations and limitations of the continuum approach are discussed. 27 references, 13 figures, 2 tables
Genetic analysis of partial egg production records in Japanese quail using random regression models.
Abou Khadiga, G; Mahmoud, B Y F; Farahat, G S; Emam, A M; El-Full, E A
2017-08-01
The main objectives of this study were to detect the most appropriate random regression model (RRM) to fit the data of monthly egg production in 2 lines (selected and control) of Japanese quail and to test the consistency of different criteria of model choice. Data from 1,200 female Japanese quails for the first 5 months of egg production from 4 consecutive generations of an egg line selected for egg production in the first month (EP1) was analyzed. Eight RRMs with different orders of Legendre polynomials were compared to determine the proper model for analysis. All criteria of model choice suggested that the adequate model included the second-order Legendre polynomials for fixed effects, and the third-order for additive genetic effects and permanent environmental effects. Predictive ability of the best model was the highest among all models (ρ = 0.987). According to the best model fitted to the data, estimates of heritability were relatively low to moderate (0.10 to 0.17) showed a descending pattern from the first to the fifth month of production. A similar pattern was observed for permanent environmental effects with greater estimates in the first (0.36) and second (0.23) months of production than heritability estimates. Genetic correlations between separate production periods were higher (0.18 to 0.93) than their phenotypic counterparts (0.15 to 0.87). The superiority of the selected line over the control was observed through significant (P egg production in earlier ages (first and second months) than later ones. A methodology based on random regression animal models can be recommended for genetic evaluation of egg production in Japanese quail. © 2017 Poultry Science Association Inc.
Directory of Open Access Journals (Sweden)
Rajesh P N Rao
2010-11-01
Full Text Available A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs. Actions are selected based not on a single optimal estimate of state but on the posterior distribution over states (the belief state. We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize
International Nuclear Information System (INIS)
Navarro, V.; Alonso, J.; Asensio, L.; Yustres, A.; Pintado, X.
2012-01-01
Document available in extended abstract form only. The use of numerical methods, especially the Finite Element Method (FEM), for solving boundary problems in Unsaturated Soil Mechanics has experienced significant progress. Several codes, both built mainly for research purposes and commercial software, are now available. In the last years, Multi-physic Partial Differentiation Equation Solvers (MPDES) have turned out to be an interesting proposal. In this family of solvers, the user defines the governing equations and the behaviour models, generally using a computer algebra environment. The code automatically assembles and solves the equation systems, saving the user having to redefine the structures of memory storage or to implement solver algorithms. The user can focus on the definition of the physics of the problem, while it is possible to couple virtually any physical or chemical process that can be described by a PDE. This can be done, for instance, in COMSOL Multiphysics (CM). Nonetheless, the versatility of CM is compromised by the impossibility to implement models with variables defined by implicit functions. Elasto-plastic models involve an implicit coupling among stress increments, plastic strains and plastic variables increments. For this reason, they cannot be implemented in CM in a straightforward way. This means a very relevant limitation for the use of this tool in the analysis of geomechanical boundary value problems. In this work, a strategy to overcome this problem using the multi-physics concept is presented. A mixed method is proposed, considering the constitutive stresses, the pre-consolidation pressure and the plastic variables as main unknowns of the model. Mixed methods usually present stability problems. However, the algorithmics present in CM include several numerical strategies to minimise this kind of problems. Besides, CM is based on the application of the FEM with Lagrange multipliers, an approach that significantly contributes stability
Temporal Aggregation in First Order Cointegrated Vector Autoregressive models
DEFF Research Database (Denmark)
Milhøj, Anders; la Cour, Lisbeth Funding
2011-01-01
with the frequency of the data. We also introduce a graphical representation that will prove useful as an additional informational tool for deciding the appropriate cointegration rank of a model. In two examples based on models of time series of different grades of gasoline, we demonstrate the usefulness of our...
Calculus for cognitive scientists higher order models and their analysis
Peterson, James K
2016-01-01
This book offers a self-study program on how mathematics, computer science and science can be profitably and seamlessly intertwined. This book focuses on two variable ODE models, both linear and nonlinear, and highlights theoretical and computational tools using MATLAB to explain their solutions. It also shows how to solve cable models using separation of variables and the Fourier Series.
Higher-Order Hamiltonian Model for Unidirectional Water Waves
Bona, J. L.; Carvajal, X.; Panthee, M.; Scialom, M.
2018-04-01
Formally second-order correct, mathematical descriptions of long-crested water waves propagating mainly in one direction are derived. These equations are analogous to the first-order approximations of KdV- or BBM-type. The advantage of these more complex equations is that their solutions corresponding to physically relevant initial perturbations of the rest state may be accurate on a much longer timescale. The initial value problem for the class of equations that emerges from our derivation is then considered. A local well-posedness theory is straightforwardly established by a contraction mapping argument. A subclass of these equations possess a special Hamiltonian structure that implies the local theory can be continued indefinitely.
A deterministic partial differential equation model for dose calculation in electron radiotherapy.
Duclous, R; Dubroca, B; Frank, M
2010-07-07
High-energy ionizing radiation is a prominent modality for the treatment of many cancers. The approaches to electron dose calculation can be categorized into semi-empirical models (e.g. Fermi-Eyges, convolution-superposition) and probabilistic methods (e.g.Monte Carlo). A third approach to dose calculation has only recently attracted attention in the medical physics community. This approach is based on the deterministic kinetic equations of radiative transfer. We derive a macroscopic partial differential equation model for electron transport in tissue. This model involves an angular closure in the phase space. It is exact for the free streaming and the isotropic regime. We solve it numerically by a newly developed HLLC scheme based on Berthon et al (2007 J. Sci. Comput. 31 347-89) that exactly preserves the key properties of the analytical solution on the discrete level. We discuss several test cases taken from the medical physics literature. A test case with an academic Henyey-Greenstein scattering kernel is considered. We compare our model to a benchmark discrete ordinate solution. A simplified model of electron interactions with tissue is employed to compute the dose of an electron beam in a water phantom, and a case of irradiation of the vertebral column. Here our model is compared to the PENELOPE Monte Carlo code. In the academic example, the fluences computed with the new model and a benchmark result differ by less than 1%. The depths at half maximum differ by less than 0.6%. In the two comparisons with Monte Carlo, our model gives qualitatively reasonable dose distributions. Due to the crude interaction model, these so far do not have the accuracy needed in clinical practice. However, the new model has a computational cost that is less than one-tenth of the cost of a Monte Carlo simulation. In addition, simulations can be set up in a similar way as a Monte Carlo simulation. If more detailed effects such as coupled electron-photon transport, bremsstrahlung
A deterministic partial differential equation model for dose calculation in electron radiotherapy
Duclous, R.; Dubroca, B.; Frank, M.
2010-07-01
High-energy ionizing radiation is a prominent modality for the treatment of many cancers. The approaches to electron dose calculation can be categorized into semi-empirical models (e.g. Fermi-Eyges, convolution-superposition) and probabilistic methods (e.g. Monte Carlo). A third approach to dose calculation has only recently attracted attention in the medical physics community. This approach is based on the deterministic kinetic equations of radiative transfer. We derive a macroscopic partial differential equation model for electron transport in tissue. This model involves an angular closure in the phase space. It is exact for the free streaming and the isotropic regime. We solve it numerically by a newly developed HLLC scheme based on Berthon et al (2007 J. Sci. Comput. 31 347-89) that exactly preserves the key properties of the analytical solution on the discrete level. We discuss several test cases taken from the medical physics literature. A test case with an academic Henyey-Greenstein scattering kernel is considered. We compare our model to a benchmark discrete ordinate solution. A simplified model of electron interactions with tissue is employed to compute the dose of an electron beam in a water phantom, and a case of irradiation of the vertebral column. Here our model is compared to the PENELOPE Monte Carlo code. In the academic example, the fluences computed with the new model and a benchmark result differ by less than 1%. The depths at half maximum differ by less than 0.6%. In the two comparisons with Monte Carlo, our model gives qualitatively reasonable dose distributions. Due to the crude interaction model, these so far do not have the accuracy needed in clinical practice. However, the new model has a computational cost that is less than one-tenth of the cost of a Monte Carlo simulation. In addition, simulations can be set up in a similar way as a Monte Carlo simulation. If more detailed effects such as coupled electron-photon transport, bremsstrahlung
Neutrino masses and their ordering: global data, priors and models
Gariazzo, S.; Archidiacono, M.; de Salas, P. F.; Mena, O.; Ternes, C. A.; Tórtola, M.
2018-03-01
We present a full Bayesian analysis of the combination of current neutrino oscillation, neutrinoless double beta decay and Cosmic Microwave Background observations. Our major goal is to carefully investigate the possibility to single out one neutrino mass ordering, namely Normal Ordering or Inverted Ordering, with current data. Two possible parametrizations (three neutrino masses versus the lightest neutrino mass plus the two oscillation mass splittings) and priors (linear versus logarithmic) are exhaustively examined. We find that the preference for NO is only driven by neutrino oscillation data. Moreover, the values of the Bayes factor indicate that the evidence for NO is strong only when the scan is performed over the three neutrino masses with logarithmic priors; for every other combination of parameterization and prior, the preference for NO is only weak. As a by-product of our Bayesian analyses, we are able to (a) compare the Bayesian bounds on the neutrino mixing parameters to those obtained by means of frequentist approaches, finding a very good agreement; (b) determine that the lightest neutrino mass plus the two mass splittings parametrization, motivated by the physical observables, is strongly preferred over the three neutrino mass eigenstates scan and (c) find that logarithmic priors guarantee a weakly-to-moderately more efficient sampling of the parameter space. These results establish the optimal strategy to successfully explore the neutrino parameter space, based on the use of the oscillation mass splittings and a logarithmic prior on the lightest neutrino mass, when combining neutrino oscillation data with cosmology and neutrinoless double beta decay. We also show that the limits on the total neutrino mass ∑ mν can change dramatically when moving from one prior to the other. These results have profound implications for future studies on the neutrino mass ordering, as they crucially state the need for self-consistent analyses which explore the
Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E
2017-12-01
1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.
Deshmukh, S.A.R.K.; Laverman, J.A.; van Sint Annaland, M.; Kuipers, J.A.M.
2005-01-01
A small laboratory-scale membrane-assisted fluidized bed reactor (MAFBR) was constructed in order to experimentally demonstrate the reactor concept for the partial oxidation of methanol to formaldehyde. Methanol conversion and product selectivities were measured at various overall fluidization
How do we make models that are useful in understanding partial epilepsies?
Prince, David A
2014-01-01
The goals of constructing epilepsy models are (1) to develop approaches to prophylaxis of epileptogenesis following cortical injury; (2) to devise selective treatments for established epilepsies based on underlying pathophysiological mechanisms; and (3) use of a disease (epilepsy) model to explore brain molecular, cellular and circuit properties. Modeling a particular epilepsy syndrome requires detailed knowledge of key clinical phenomenology and results of human experiments that can be addressed in critically designed laboratory protocols. Contributions to understanding mechanisms and treatment of neurological disorders has often come from research not focused on a specific disease-relevant issue. Much of the foundation for current research in epilepsy falls into this category. Too strict a definition of the relevance of an experimental model to progress in preventing or curing epilepsy may, in the long run, slow progress. Inadequate exploration of the experimental target and basic laboratory results in a given model can lead to a failed effort and false negative or positive results. Models should be chosen based on the specific issues to be addressed rather than on convenience of use. Multiple variables including maturational age, species and strain, lesion type, severity and location, latency from injury to experiment and genetic background will affect results. A number of key issues in clinical and basic research in partial epilepsies remain to be addressed including the mechanisms active during the latent period following injury, susceptibility factors that predispose to epileptogenesis, injury - induced adaptive versus maladaptive changes, mechanisms of pharmaco-resistance and strategies to deal with multiple pathophysiological processes occurring in parallel.
Faes, Luca; Nollo, Giandomenico
2010-11-01
The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. Moreover, we propose the utilization of an extended MVAR model including both instantaneous and lagged effects. This model is used to assess PDC either in accordance with the definition of Granger causality when considering only lagged effects (iPDC), or with an extended form of causality, when we consider both instantaneous and lagged effects (ePDC). The approach is first evaluated on three theoretical examples of MVAR processes, which show that the presence of instantaneous correlations may produce misleading profiles of PDC and gPDC, while ePDC and iPDC derived from the extended model provide here a correct interpretation of extended and lagged causality. It is then applied to representative examples of cardiorespiratory and EEG MV time series. They suggest that ePDC and iPDC are better interpretable than PDC and gPDC in terms of the known cardiovascular and neural physiologies.
A model reduction approach to numerical inversion for a parabolic partial differential equation
International Nuclear Information System (INIS)
Borcea, Liliana; Druskin, Vladimir; Zaslavsky, Mikhail; Mamonov, Alexander V
2014-01-01
We propose a novel numerical inversion algorithm for the coefficients of parabolic partial differential equations, based on model reduction. The study is motivated by the application of controlled source electromagnetic exploration, where the unknown is the subsurface electrical resistivity and the data are time resolved surface measurements of the magnetic field. The algorithm presented in this paper considers inversion in one and two dimensions. The reduced model is obtained with rational interpolation in the frequency (Laplace) domain and a rational Krylov subspace projection method. It amounts to a nonlinear mapping from the function space of the unknown resistivity to the small dimensional space of the parameters of the reduced model. We use this mapping as a nonlinear preconditioner for the Gauss–Newton iterative solution of the inverse problem. The advantage of the inversion algorithm is twofold. First, the nonlinear preconditioner resolves most of the nonlinearity of the problem. Thus the iterations are less likely to get stuck in local minima and the convergence is fast. Second, the inversion is computationally efficient because it avoids repeated accurate simulations of the time-domain response. We study the stability of the inversion algorithm for various rational Krylov subspaces, and assess its performance with numerical experiments. (paper)
A model reduction approach to numerical inversion for a parabolic partial differential equation
Borcea, Liliana; Druskin, Vladimir; Mamonov, Alexander V.; Zaslavsky, Mikhail
2014-12-01
We propose a novel numerical inversion algorithm for the coefficients of parabolic partial differential equations, based on model reduction. The study is motivated by the application of controlled source electromagnetic exploration, where the unknown is the subsurface electrical resistivity and the data are time resolved surface measurements of the magnetic field. The algorithm presented in this paper considers inversion in one and two dimensions. The reduced model is obtained with rational interpolation in the frequency (Laplace) domain and a rational Krylov subspace projection method. It amounts to a nonlinear mapping from the function space of the unknown resistivity to the small dimensional space of the parameters of the reduced model. We use this mapping as a nonlinear preconditioner for the Gauss-Newton iterative solution of the inverse problem. The advantage of the inversion algorithm is twofold. First, the nonlinear preconditioner resolves most of the nonlinearity of the problem. Thus the iterations are less likely to get stuck in local minima and the convergence is fast. Second, the inversion is computationally efficient because it avoids repeated accurate simulations of the time-domain response. We study the stability of the inversion algorithm for various rational Krylov subspaces, and assess its performance with numerical experiments.
International Nuclear Information System (INIS)
Nasef, Mohamed Mahmoud; Ahmad Ali, Amgad; Saidi, Hamdani; Ahmad, Arshad
2014-01-01
Modeling and optimization aspects of radiation induced grafting (RIG) of 4-vinylpyridine (4-VP) onto partially fluorinated polymers such as poly(ethylene-co-tetrafluoroethene) (ETFE) and poly(vinylidene fluoride) (PVDF) films were comparatively investigated using response surface method (RSM). The effects of independent parameters: absorbed dose, monomer concentration, grafting time and reaction temperature on the response, grafting yield (GY) were correlated through two quadratic models. The results of this work confirm that RSM is a reliable tool not only for optimization of the reaction parameters and prediction of GY in RIG processes, but also for the reduction of the number of the experiments, monomer consumption and absorbed dose leading to an improvement of the overall reaction cost. - Highlights: • Comparative study of radiation induced grafting of 4-VP onto PVDF and ETFE films. • Optimization of reaction parameters for both grafting systems was made using RSM. • Single factor design for both grafting systems was used as a reference. • Two quadratic regression models were developed for prediction of grafting yield. • RSM is an effective tool for handling grafting reactions under different conditions
Energy Technology Data Exchange (ETDEWEB)
Sanchidrian, Jose A.; Lopez, Lina M. [Universidad Politecnica de Madrid - E.T.S.I. Minas, Rios Rosas 21, E-28003 Madrid (Spain)
2006-02-15
The energy delivered by explosives is described by means of the useful expansion work along the isentrope of the detonation products. A thermodynamic code (W-DETCOM) is used, in which a partial reaction model has been implemented. In this model, the reacted fraction of the explosive in the detonation state is used as a fitting factor so that the calculated detonation velocity meets the experimental value. Calculations based on such a model have been carried out for a number of commercial explosives of ANFO and emulsion types. The BKW (Becker-Kistiakowsky-Wilson) equation of state is used for the detonation gases with the Sandia parameter set (BKWS). The energy delivered in the expansion (useful work) is calculated, and the values obtained are compared with the Gurney energies from cylinder test data at various expansion ratios. The expansion work values obtained are much more realistic than those from an ideal detonation calculation and, in most cases, the values predicted by the calculation are in good agreement with the experimental ones. (Abstract Copyright [2006], Wiley Periodicals, Inc.)