Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Mantle dynamics and seismic tomography

Three-dimensional imaging of the Earth's interior, called seismic tomography, has achieved breakthrough advances in the last two decades, revealing fundamental geodynamical processes throughout the Earth's mantle and core. Convective circulation of the entire mantle is taking place, with subducted oceanic lithosphere sinking into the lower mantle, overcoming the resistance to penetration provided by the phase boundary near 650-km depth that separates the upper and lower mantle. The boundary layer at the base of the mantle has been revealed to have complex structure, involving local stratification, extensive structural anisotropy, and massive regions of partial melt. The Earth's high Rayleigh number convective regime now is recognized to be much more interesting and complex than suggested by textbook cartoons, and continued advances in seismic tomography, geodynamical modeling, and high-pressure–high-temperature mineral physics will be needed to fully quantify the complex dynamics of our planet's interior.

Host-parasite dynamics and outgrowth of virus containing a single K70R amino acid change in reverse transcriptase are responsible for the loss of human immunodeficiency virus type 1 RNA load suppression by zidovudine.

The association between human immunodeficiency virus type I (HIV-1) RNA load changes and the emergence of resistant virus variants was investigated in 24 HIV-1-infected asymptomatic persons during 2 years of treatment with zidovudine by sequentially measuring serum HIV-1 RNA load and the relative amounts of HIV-1 RNA containing mutations at reverse transcriptase (RT) codons 70 (K-->R), 41 (M-->L), and 215 (T-->Y/F). A mean maximum decline in RNA load occurred during the first month, followed by a resurgence between 1 and 3 months, which appeared independent of drug-resistance. Mathematical modeling suggests that this resurgence is caused by host-parasite dynamics, and thus reflects infection of the transiently increased numbers of CD4+ lymphocytes. Between 3 and 6 months of treatment, the RNA load returned to baseline values, which was associated with the emergence of virus containing a single lysine to arginine amino acid change at RT codon 70, only conferring an 8-fold reduction in susceptibility. Despite the relative loss of RNA load suppression, selection toward mutations at RT codons 215 and 41 continued. Identical patterns were observed in the mathematical model. While host-parasite dynamics and outgrowth of low-level resistant virus thus appear responsible for the loss of HIV-1 RNA load suppression, zidovudine continues to select for alternative mutations, conferring increasing levels of resistance.

A contribution on modeling methodologies for multibody systems.

Multibody System Dynamics has been responsible for revolutionizing Mechanical Engineering Design by using mathematical models to simulate and optimize the dynamic behavior of a wide range of mechanical systems. These mathematical models not only can provide valuable informations about a system that could otherwise be obtained only by experiments with prototypes, but also have been responsible for the development of many model-based control systems. This work represents a contribution for dynamic modeling of multibody mechanical systems by developing a novel recursive modular methodology that unifies the main contributions of several Classical Mechanics formalisms. The reason for proposing such a methodology is to motivate the implementation of computational routines for modeling complex multibody mechanical systems without being dependent on closed source software and, consequently, to contribute for the teaching of Multibody System Dynamics in undergraduate and graduate levels. All the theoretical developments are based on and motivated by a critical literature review, leading to a general matrix form of the dynamic equations of motion of a multibody mechanical system (that can be expressed in terms of any set of variables adopted for the description of motions performed by the system, even if such a set includes redundant variables) and to a general recursive methodology for obtaining mathematical models of complex systems given a set of equations describing the dynamics of each of its uncoupled subsystems and another set describing the constraints among these subsystems in the assembled system. This work also includes some discussions on the description of motion (using any possible set of motion variables and admitting any kind of constraint that can be expressed by an invariant), and on the conditions for solving forward and inverse dynamics problems given a mathematical model of a multibody system. Finally, some examples of computational packages based on the novel methodology, along with some case studies, are presented, highlighting the contributions that can be achieved by using the proposed methodology.

Nonlinear dynamics in discretionary accruals: An analysis of bank loan-loss provisions

Several studies have analyzed discretionary accruals to address earnings-smoothing behaviors in the banking industry. We argue that the characteristic link between accruals and earnings may be nonlinear, since both the incentives to manipulate income and the practical way to do so depend partially on the relative size of earnings. Given a sample of 15,268 US banks over the period 1996–2011, the main results in this paper suggest that, depending on the size of earnings, bank managers tend to engage in earnings-decreasing strategies when earnings are negative (“big-bath”), use earnings-increasing strategies when earnings are positive, and use provisions as a smoothing device when earnings are positive and substantial (“cookie-jar” accounting). This evidence, which cannot be explained by the earnings-smoothing hypothesis, is consistent with the compensation theory. Neglecting nonlinear patterns in the econometric modeling of these accruals may lead to misleading conclusions regarding the characteristic strategies used in earnings management.

Logical Modeling and Dynamical Analysis of Cellular Networks

The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle.

Development and testing of INTRAS, a microscopic freeway simulation model. Volume 1: program design, parameter calibration and freeway dynamics component development. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Analytical modeling of driver response in crash avoidance maneuvering. Volume I: technical background. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Analytical modeling of driver response in crash avoidance maneuvering. Volume III: a trim model and computer program for determining ground vehicle steady state operating conditions and quasilinear stability coefficients. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

PROMETHEUS 2 - a user oriented program for human crash dynamics. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Simulation of restrained occupant dynamics during vehicle rollover. Final report.

National Highway Traffic Safety Administration, Crashworthiness Research Division, Washington, D.C.

Study of automobile market dynamics. Volume I: description. Final report.

Transportation Systems Center, Cambridge, Mass.

Study of automobile market dynamics. Volume II: analysis. Final report.

Transportation Systems Center, Cambridge, Mass.

Dynamics of the world climate/food system : a model for prediction of world food production and allocation /

Includes bibliographical references.

Workshop on Engineering Turbulence Modeling : proceedings of the Workshop on Engineering Turbulence Modeling sponsored by the Institute for Computational Mechanics in Propulsion and Center for Modeling of Turbulence and Transition, NASA Lewis Research Center, Cleveland, Ohio, August 21-22, 1991.

"ICOMP-92-02; CMOTT-92-02."