A Novel Algorithm to Quantify Coronary Remodeling Using Inferred Normal Dimensions

Background:Vascular remodeling, the dynamic dimensional change in face of stress, can assume different directions as well as magnitudes in atherosclerotic disease. Classical measurements rely on reference to segments at a distance, risking inappropriate comparison between dislike vessel portions.Objective:to explore a new method for quantifying vessel remodeling, based on the comparison between a given target segment and its inferred normal dimensions.Methods:Geometric parameters and plaque composition were determined in 67 patients using three-vessel intravascular ultrasound with virtual histology (IVUS-VH). Coronary vessel remodeling at cross-section (n = 27.639) and lesion (n = 618) levels was assessed using classical metrics and a novel analytic algorithm based on the fractional vessel remodeling index (FVRI), which quantifies the total change in arterial wall dimensions related to the estimated normal dimension of the vessel. A prediction model was built to estimate the normal dimension of the vessel for calculation of FVRI.Results:According to the new algorithm, “Ectatic” remodeling pattern was least common, “Complete compensatory” remodeling was present in approximately half of the instances, and “Negative” and “Incomplete compensatory” remodeling types were detected in the remaining. Compared to a traditional diagnostic scheme, FVRI-based classification seemed to better discriminate plaque composition by IVUS-VH.Conclusion:Quantitative assessment of coronary remodeling using target segment dimensions offers a promising approach to evaluate the vessel response to plaque growth/regression.

Algorithm engineering for expression dag based number types

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

A note on parallelizing the parameterized expectations algorithm

The parameterized expectations algorithm (PEA) involves a long simulation and a nonlinear least squares (NLS) fit, both embedded in a loop. Both steps are natural candidates for parallelization. This note shows that parallelization can lead to important speedups for the PEA. I provide example code for a simple model that can serve as a template for parallelization of more interesting models, as well as a download link for an image of a bootable CD that allows creation of a cluster and execution of the example code in minutes, with no need to install any software.

Structural inferences from first-price auction experiments

We use structural methods to assess equilibrium models of bidding with data from first-price auction experiments. We identify conditions to test the Nash equilibrium models for homogenous and for heterogeneous constant relative risk aversion when bidders private valuations are independent and uniformly drawn. The outcomes of our study indicate that behavior may have been affected by the procedure used to conduct the experiments and that the usual Nash equilibrium model for heterogeneous constant relative risk averse bidders does not consistently explain the observed overbidding. From an empirical standpoint, our analysis shows the possible drawbacks of overlooking the homogeneity hypothesis when testing symmetric equilibrium models of bidding and it puts in perspective the sensitivity of structural inferences to the available information.

All-pay auction equilibria in contests

We analyze (non-deterministic) contests with anonymous contest success functions. There is no restriction on the number of contestants or on their valuations for the prize. We provide intuitive and easily verifiable conditions for the existence of an equilibrium with properties similar to the one of the (deterministic) all-pay auction. Since these conditions are fulfilled for a wide array of situations, the predictions of this equilibrium are very robust to the specific details of the contest. An application of this result contributes to fill a gap in the analysis of the popular Tullock rent- seeking game because it characterizes properties of an equilibrium for increasing returns to scale larger than two, for any number of contestants and in contests with or without a common value. Keywords: (non-) deterministic contest, all-pay auction, contest success functions. JEL Classification Numbers: C72 (Noncooperative Games), D72 (Economic Models of Political Processes: Rent-Seeking, Elections), D44 (Auctions).

Preferred suppliers in auction markets

In a procurement setting, this paper examines agreements between a buyer and one of the suppliers which would increase their joint surplus. The provisions of such agreements depend on the buyer's ability to design the rules of the final procurement auction. When the buyer has no such ability, their joint surplus can be increased by an agreement which grants to the preferred supplier a right-of-first-refusal on the lowest price offer from the other suppliers. When the buyer does have this ability, one agreement which maximizes their joint surplus includes a revelation game for the cost of the preferred supplier and a reserve price in the procurement auction based on that cost.

The Complete Information First. Price Auction or the Importance of Being Indivisible

Abstract Despite the popularity of auction theoretical thinking, it appears that no one has presented an elementary equilibrium analysis of the first-price sealed-bid auction mechanism under complete information. This paper aims to remedy that omission. We show that the existence of pure strategy undominated Nash equilibria requires that the bidding space is not "too divisible" (that is, a continuum). In fact, when bids must form part of a finite grid there always exists a "high price equilibrium". However, there might also be "low price equilibria" and when the bidding space is very restrictive the revenue obtained in these "low price equilibria" might be very low. We discuss the properties of the equilibria and an application of auction theoretical thinking in which "low price equilibria" may be relevant. Keywords: First-price auctions, undominated Nash equilibria. JEL Classification Numbers: C72 (Noncooperative Games), D44 (Auctions).

An objective anisotropic elastic plastic model and Algorithm applicable to bone mechanics

The implicit projection algorithm of isotropic plasticity is extended to an objective anisotropic elastic perfectly plastic model. The recursion formula developed to project the trial stress on the yield surface, is applicable to any non linear elastic law and any plastic yield function.A curvilinear transverse isotropic model based on a quadratic elastic potential and on Hill's quadratic yield criterion is then developed and implemented in a computer program for bone mechanics perspectives. The paper concludes with a numerical study of a schematic bone-prosthesis system to illustrate the potential of the model.

A numerical algorithm for finding solutions of a generalized Nash equilibrium problem

A family of nonempty closed convex sets is built by using the data of the Generalized Nash equilibrium problem (GNEP). The sets are selected iteratively such that the intersection of the selected sets contains solutions of the GNEP. The algorithm introduced by Iusem-Sosa (2003) is adapted to obtain solutions of the GNEP. Finally some numerical experiments are given to illustrate the numerical behavior of the algorithm.

An algorithm for semi-infinite polynomial optimization

"Vegeu el resum a l'inici del document del fitxer adjunt."

An approximation algorithm for #k-SAT

"Vegeu el resum a l'inici del document del fitxer adjunt"

An iterative Multiscale Finite-Volume algorithm converging to the exact solution

The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed