2,588 research outputs found
A New Class of Processes for Formalizing and Generalizing Individual-Based Models: The Semi-Semi-Markov Processes
2000 Mathematics Subject Classification: 60K15, 60K20, 60G20,60J75, 60J80, 60J85, 60-08,
90B15.Individual-based models are a \bottom-up" approach for calculating empirical distributions at the level of the population from simulated individual trajectories. We build a new class of stochastic processes for mathematically formalizing and generalizing these simulation models according to a \top-down" approach, when the individual state changes occur at countable random times. We allow individual population-dependent semi-Markovian transitions in a non closed population such as a branching population. These new processes are called Semi-Semi-Markov Processes (SSMP) and are generalizations of Semi-Markov processes. We calculate their kernel and their probability law, and we build a simulation algorithm from the kernel.This paper was supported by the program ECO-NET 2006 financed by the french foreign
office
Rank 3 permutation characters and maximal subgroups
In this paper we classify all maximal subgroups M of a nearly simple
primitive rank 3 group G of type L=Omega_{2m+1}(3), m > 3; acting on an L-orbit
E of non-singular points of the natural module for L such that 1_P^G <=1_M^G
where P is a stabilizer of a point in E. This result has an application to the
study of minimal genera of algebraic curves which admit group actions.Comment: 41 pages, to appear in Forum Mathematicu
Brief for William E. Brock and John McCain et al., California Democratic Party v. Jones, No. 99-401 (U.S. Mar. 30, 2000)
A one-phase interior point method for nonconvex optimization
The work of Wachter and Biegler suggests that infeasible-start interior point
methods (IPMs) developed for linear programming cannot be adapted to nonlinear
optimization without significant modification, i.e., using a two-phase or
penalty method. We propose an IPM that, by careful initialization and updates
of the slack variables, is guaranteed to find a first-order certificate of
local infeasibility, local optimality or unboundedness of the (shifted)
feasible region. Our proposed algorithm differs from other IPM methods for
nonconvex programming because we reduce primal feasibility at the same rate as
the barrier parameter. This gives an algorithm with more robust convergence
properties and closely resembles successful algorithms from linear programming.
We implement the algorithm and compare with IPOPT on a subset of CUTEst
problems. Our algorithm requires a similar median number of iterations, but
fails on only 9% of the problems compared with 16% for IPOPT. Experiments on
infeasible variants of the CUTEst problems indicate superior performance for
detecting infeasibility.
The code for our implementation can be found at
https://github.com/ohinder/OnePhase .Comment: fixed typo in sign of dual multiplier in KKT syste
Noise and nonlinearities in high-throughput data
High-throughput data analyses are becoming common in biology, communications,
economics and sociology. The vast amounts of data are usually represented in
the form of matrices and can be considered as knowledge networks. Spectra-based
approaches have proved useful in extracting hidden information within such
networks and for estimating missing data, but these methods are based
essentially on linear assumptions. The physical models of matching, when
applicable, often suggest non-linear mechanisms, that may sometimes be
identified as noise. The use of non-linear models in data analysis, however,
may require the introduction of many parameters, which lowers the statistical
weight of the model. According to the quality of data, a simpler linear
analysis may be more convenient than more complex approaches.
In this paper, we show how a simple non-parametric Bayesian model may be used
to explore the role of non-linearities and noise in synthetic and experimental
data sets.Comment: 12 pages, 3 figure
Identification of nonlinear heat transfer laws from boundary observations
We consider the problem of identifying a nonlinear heat transfer law at the boundary, or of the temperature-dependent heat transfer coefficient in a parabolic equation from boundary observations. As a practical example, this model applies to the heat transfer coefficient that describes the intensity of heat exchange between a hot wire and the cooling water in which it is placed. We reformulate the inverse problem as a variational one which aims to minimize a misfit functional and prove that it has a solution. We provide a gradient formula for the misfit functional and then use some iterative methods for solving the variational problem. Thorough investigations are made with respect to several initial guesses and amounts of noise in the input data. Numerical results show that the methods are robust, stable and accurate
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Oral mucosal injury caused by mammalian target of rapamycin inhibitors: emerging perspectives on pathobiology and impact on clinical practice.
In recent years oral mucosal injury has been increasingly recognized as an important toxicity associated with mammalian target of rapamycin (mTOR) inhibitors, including in patients with breast cancer who are receiving everolimus. This review addresses the state-of-the-science regarding mTOR inhibitor-associated stomatitis (mIAS), and delineates its clinical characteristics and management. Given the clinically impactful pain associated with mIAS, this review also specifically highlights new research focusing on the study of the molecular basis of pain. The incidence of mIAS varies widely (2-78%). As reported across multiple mTOR inhibitor clinical trials, grade 3/4 toxicity occurs in up to 9% of patients. Managing mTOR-associated oral lesions with topical oral, intralesional, and/or systemic steroids can be beneficial, in contrast to the lack of evidence supporting steroid treatment of oral mucositis caused by high-dose chemotherapy or radiation. However, steroid management is not uniformly efficacious in all patients receiving mTOR inhibitors. Furthermore, technology does not presently exist to permit clinicians to predict a priori which of their patients will develop these lesions. There thus remains a strategic need to define the pathobiology of mIAS, the molecular basis of pain, and risk prediction relative to development of the clinical lesion. This knowledge could lead to novel future interventions designed to more effectively prevent mIAS and improve pain management if clinically significant mIAS lesions develop
Non-Abelian Monopole and Dyon Solutions in a Modified Einstein-Yang-Mills-Higgs System
We have studied a modified Yang-Mills-Higgs system coupled to Einstein
gravity. The modification of the Einstein-Hilbert action involves a direct
coupling of the Higgs field to the scalar curvature. In this modified system we
are able to write a Bogomol'nyi type condition in curved space and demonstrate
that the positive static energy functional is bounded from below. We then
investigate non-Abelian sperically symmetric static solutions in a similar
fashion to the `t Hooft-Polyakov monopole. After reviewing previously studied
monopole solutions of this type, we extend the formalism to included electric
charge and we present dyon solutions.Comment: 18 pages LaTeX, 7 eps-figure
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