Qualitative response of interaction networks: application to the validation of biological models

We advocate the use of qualitative models for the analysis of shift equilibria in large biological systems. We present a mathematical method, allowing qualitative predictions to be made of the behaviour of a biological system. These predictions are not dependent on specific values of the kinetic constants. We show how these methods can be used to improve understanding of a complex regulatory system. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An approach to defining the pattern of interaction effects in a two-way layout

Summary A method is given to classify rows and columns into subgroups so that additivity holds within each of the subtables made of the grouped rows or the grouped columns. The least squares estimators of the cell means are easily obtained for the resulting linear model together with their variances. An estimator of the error varianceσ ₂ is given when there is only one observation per cell. A treatment of an ordered table is also given.     

AN ANALYSIS OF AMULTIVARIATE TWO－WAY MODEL WITH INTERACTION AND NO REPLICATION

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Nonlinear supersymmetry and goldstino couplings to the MSSM

We briefly review the nonlinear supersymmetry formalisms in the standard realization and superfield methods. We then evaluate the goldstino couplings to the minimal supersymmetric standard model (MSSM) superfields and discuss their phenomenological consequences. These relate to the tree-level Higgs mass and to invisible Higgs- and Z-boson decays. The Higgs mass is increased from its MSSM tree-level value and brought above the LEP2 mass bound for a low scale of supersymmetry breaking √f ∼ 2 TeV to 7 TeV. The invisible decay rates of the Higgs and Z bosons into goldstino and neutralino are computed and shown to bring stronger constraints on f than their decays into goldstino pairs, which are subleading in 1/f.     

Constraint-based inference algorithms for structural models with latent confounders— empirical application and simulations

Summary  Graphical methods for the discovery of structural models from observational data provide interesting tools for applied researchers. A problem often faced in empirical studies is the presence of latent confounders which produce associations between the observed variables. Although causal inference algorithms exist which can cope with latent confounders, empirical applications assessing the performance of such algorithms are largely lacking. In this study, we apply the constraint based Fast Causal Inference algorithm implemented in the software program TETRAD on a data set containing strategy and performance information about 608 business units. In contrast to the informative and reasonable results for the impirical data, simulation findings reveal problems in recovering some of the structural relations.     

On the structural stability of the Euler-Voigt and Navier-Stokes-Voigt models

We consider the Euler-Voigt equations and the Navier-Stokes-Voigt equations, which are obtained by an inviscid α-regularization from the corresponding equations. The main result we show is the structural stability of the system in terms of the variations of both viscosity and regularization parameters.     

Model-based two-way clustering of second-level units in ordinal multilevel latent Markov models

In this paper, an ordinal multilevel latent Markov model based on separate random effects is proposed. In detail, two distinct second-level discrete effects are considered in the model, one affecting the initial probability vector and the other affecting the transition probability matrix of the first-level ordinal latent Markov process. To model these separate effects, we consider a bi-dimensional mixture specification that allows to avoid unverifiable assumptions on the random effect distribution and to derive a two-way clustering of second-level units. Starting from a general model where the two random effects are dependent, we also obtain the independence model as a special case. The proposal is applied to data on the physical health status of a sample of elderly residents grouped into nursing homes. A simulation study assessing the performance of the proposal is also included.

     

Parallel sparse linear algebra and application to structural mechanics

The framework of this paper is the parallelization of a plasticity algorithm that uses an implicit method and an incremental approach. More precisely, we will focus on some specific parallel sparse linear algebra algorithms which are the most time-consuming steps to solve efficiently such an engineering application. First, we present a general algorithm which computes an efficient static scheduling of block computations for parallel sparse linear factorization. The associated solver, based on a supernodal fan-in approach, is fully driven by this scheduling. Second, we describe a scalable parallel assembly algorithm based on a distribution of elements induced by the previous distribution for the blocks of the sparse matrix. We give an overview of these algorithms and present performance results on an IBM SP2 for a collection of grid and irregular problems. This revised version was published online in June 2006 with corrections to the Cover Date.     

A two-way analysis of variance model with positive definite interaction for homologous factors

A special type of modelling of interaction is investigated in the framework of two-way analysis of variance models for homologous factors. Factors are said to be homologous when their levels are in a meaningful one-to-one relationship, which arise in a wide variety of contexts, as recalled by McCullagh (J. Roy. Statist. Soc. B 62 (2000) 209). The classical linear context for analysis of interaction is extended by positive definiteness restrictions on the interaction parameters. These restrictions aim to provide a spatial representation of the interaction. Properties of the maximum likelihood estimators are derived for a given dimensionality of the model. When the dimension is unknown, an alternative procedure is proposed based on a penalty approach. This approach relies heavily on random matrix theory arguments but we focus on their statistical consequences especially on the reduction of over-fitting problems in the maximum likelihood estimation. Confidence ellipses are provided for an illustrative example.     

Nonparametric variable selection and its application to additive models

Variable selection for multivariate nonparametric regression models usually involves parameterized approximation for nonparametric functions in the objective function. However, this parameterized approximation often increases the number of parameters significantly, leading to the “curse of dimensionality” and inaccurate estimation. In this paper, we propose a novel and easily implemented approach to do variable selection in nonparametric models without parameterized approximation, enabling selection consistency to be achieved. The proposed method is applied to do variable selection for additive models. A two-stage procedure with selection and adaptive estimation is proposed, and the properties of this method are investigated. This two-stage algorithm is adaptive to the smoothness of the underlying components, and the estimation consistency can reach a parametric rate if the underlying model is really parametric. Simulation studies are conducted to examine the performance of the proposed method. Furthermore, a real data example is analyzed for illustration.

     

Continuous polling models and application to ferry assisted WLAN

In this paper we focus on a class of polling systems encountered while modeling the ferry based wireless local area network (FWLAN). A moving ferry, while walking in a predetermined cyclic path, communicates with the static nodes (or users) of the network via a wireless link. The ferry is assumed to stop and communicate with a node that has a packet to send or to receive, when it is closest to that node. The location distribution of the node to which or from which a packet arrives is assumed to have a support of positive Lebesgue measure. These features imply that polling models with finite number of queues cannot be used to model the system. We study in this paper the continuous polling systems with service disciplines that model the use of the FWLAN (and that are more complex than the classical exhaustive or gated services). Our approach is based on discretization of the continuous polling model. We propose a special way of discretizing the continuous system such that: (1)?the known Pseudo conservation laws can be applied to obtain the stationary expected workload of the discrete systems; (2)?the limit, of these ??discretized' expected workloads, equals the stationary expected workload of the continuous system. Our results rely heavily on fixed point analysis of infinite dimensional operators.     

Partitioned treatment of surface-coupled problems with application to the fluid-porous-media interaction

Employing a decoupled solution strategy for the numerical treatment of the set of governing equations describing a surface-coupled phenomenon is a common practice. In this regard, many partitioned solution algorithms have been developed, which usually either belong to the family of Schur-complement methods or to the group of staggered integration schemes. To select a decoupled solution strategy over another is, however, a case-dependent process that should be done with special care. In particular, the performances of the algorithms from the viewpoints of stability and accuracy of the results on the one hand, and the solution speed on the other hand should be investigated. In this contribution, two strategies for a partitioned treatment of the surface-coupled problem of fluid-porous-media interaction (FPMI) are considered. These are one parallel solution algorithm, which is based on the method of localised Lagrange multipliers (LLM), and one sequential solution method, which follows the block-Gauss-Seidel (BGS) integration strategy. In order to investigate the performances of the proposed schemes, an exemplary initial-boundary-value problem is considered and the numerical results obtained by employing the solution algorithms are compared. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A saddle-point theorem with application to structural optimization

The relaxation for optimal complicance design is independent of whether the underlying elastic problem is formulated in terms of displacements or strains. For the purposes of numerical experimentation and computation, it may be advantageous to formulate optimal design problems in terms of displacements as is done in Ref. 1. The relaxed problem delivered by the displacement-based formulation is of min-min-max type. Because of this, efficient numerical implementation is hampered by the order of the last two min-max operations. We show here that the last two min-max operations may be exchanged, facilitating an efficient numerical algorithm. We remark that the rigorous results given here corroborate the numerical methods and experiments given in Ref. 1.This work was supported by NSF Grant DMS-92-05158.     

Robust estimation of nonlinear structural models

The problem is considered of identification of nonlinear error-in-variables models under conditions of a heavy contamination of the sample, including the presence of outliers (i.e., anomalous observations). On the basis of robust estimation methods, we propose a development of the algorithms of adjusted and total least squares. This has enabled us to improve the accuracy of the response prediction in the presence of outliers in the sample. The algorithms are used for constructing the Engel curve from the budget survey data. In result, we draw better conclusions about the regularities of the household behavior when the income changes.     

The algebraic structure of discrete zero curvature equations associated with integrable couplings and application to enlarged Volterra systems

An algebraic structure of discrete zero curvature equations is established for integrable coupling systems associated with semi-direct sums of Lie algebras. As an application example of this algebraic structure, a τ-symmetry algebra for the Volterra lattice integrable couplings is engendered from this theory.     

Dynamical two-dimensional models of solid-fluid interaction

The present paper is devoted to the construction and investigation of two-dimensional hierarchical models for solid-fluid interaction. Applying the variational approach, the three-dimensional initial-boundary value problem is reduced to a sequence of two-dimensional problems and the existence and uniqueness of their solutions in suitable functional spaces is proved. The convergence of the sequence of vector-functions of three space variables to the solution of the original problem is proved and under additional regularity conditions the rate of approximation is estimated. Translated from Sovremennaya Matematika i Ee Prilozheniya (Contemporary Mathematics and Its Applications), Vol. 51, Differential Equations and Their Applications, 2008.     

Iterated Boolean random varieties and application to fracture statistics models

Models of random sets and of point processes are introduced to simulate some specific clustering of points, namely on random lines in R² and R³ and on random planes in R³. The corresponding point processes are special cases of Cox processes. The generating distribution function of the probability distribution of the number of points in a convex set K and the Choquet capacity T (K) are given. A possible application is to model point defects in materials with some degree of alignment. Theoretical results on the probability of fracture of convex specimens in the framework of the weakest link assumption are derived, and used to compare geometrical effects on the sensitivity of materials to fracture.     

Reliability range of model parameters and its application to biological models

This paper deals with the analysis of the determinability of the parameters of mathematical models of biological systems and the estimation of the reliability range of the parameter vectors. The results of the analysis are used to design further experiments for improving the estimation of the parameters. This procedure was illustrated by the investigation of intravenous radiopalmitate kinetics in rats with a special regard to the speed of labelled fatty acid outflow from plasma and lipoprotein formation in the liver. On the basis of the course of parameter sensitivity functions a new theoretical experiment, contributing to a marked improvement of the parameter reliability estimation, was designed. The method was algorithmized in the HYPER and EIGEN programs developed for the EAI690 hybrid computer system.     

A structural theorem on embedded graphs and its application to colorings

In this paper, a Lebesgue type theorem on the structure of graphs embedded in the surface of characteristic σ≤ 0 is given, that generalizes a result of Borodin on plane graphs. As a consequence, it is proved that every such graph without i-circuits for 4 ≤ i ≤ 11 - 3σ is 3-choosable, that offers a new upper bound to a question of Y. Zhao.     

Decomposition of two classes of structural models

The conditional independence structure of a common probability measure is a structural model. In this paper, we solve an open problem posed by Studeny [Probabilistic Conditional Independence Structures, Theme 9, p. 206]. A new approach is proposed to decompose a directed acyclic graph and its optimal properties are studied. We interpret this approach from the perspective of the decomposition of the corresponding conditional independence model and provide an algorithm for identifying the maximal prime subgraphs in a directed acyclic graph.