From Uncertainty Data to Robust Policies for Temporal Logic Planning

We consider the problem of synthesizing robust disturbance feedback policies for systems performing complex tasks. We formulate the tasks as linear temporal logic specifications and encode them into an optimization framework via mixed-integer constraints. Both the system dynamics and the specifications are known but affected by uncertainty. The distribution of the uncertainty is unknown, however realizations can be obtained. We introduce a data-driven approach where the constraints are fulfilled for a set of realizations and provide probabilistic generalization guarantees as a function of the number of considered realizations. We use separate chance constraints for the satisfaction of the specification and operational constraints. This allows us to quantify their violation probabilities independently. We compute disturbance feedback policies as solutions of mixed-integer linear or quadratic optimization problems. By using feedback we can exploit information of past realizations and provide feasibility for a wider range of situations compared to static input sequences. We demonstrate the proposed method on two robust motion-planning case studies for autonomous driving

A Cluster Method for the Ashkin--Teller Model

A cluster Monte Carlo algorithm for the Ashkin-Teller (AT) model is constructed according to the guidelines of a general scheme for such algorithms. Its dynamical behaviour is tested for the square lattice AT model. We perform simulations on the line of critical points along which the exponents vary continuously, and find that critical slowing down is significantly reduced. We find continuous variation of the dynamical exponent $z$ along the line, following the variation of the ratio $\alpha/\nu$, in a manner which satisfies the Li-Sokal bound $z_{cluster}\geq\alpha/\nu$, that was so far proved only for Potts models.Comment: 18 pages, Revtex, figures include

On the statistical evaluation of dose-response functions

The linear-quadratic dependence of effect on the dose of ionizing radiation and its biophysical implications are considered. The estimation of the parameters of the response function and the derivation of the joint confidence region of the estimates are described. The method is applied to the induction of pink mutations inTradescantia which follows the linear-quadratic model. The statistical procedure is also suitable for other response functions

Functional impairment of human resident cardiac stem cells by the cardiotoxic antineoplastic agent trastuzumab

Trastuzumab (TZM), a monoclonal antibody against the ERBB2 protein, increases survival in ERBB2-positive breast cancer patients. Its clinical use, however, is limited by cardiotoxicity. We sought to evaluate whether TZM cardiotoxicity involves inhibition of human adult cardiac-derived stem cells, in addition to previously reported direct adverse effects on cardiomyocytes. To test this idea, we exposed human cardiosphere-derived cells (hCDCs), a natural mixture of cardiac stem cells and supporting cells that has been shown to exert potent regenerative effects, to TZM and tested the effects in vitro and in vivo. We found that ERBB2 mRNA and protein are expressed in hCDCs at levels comparable to those in human myocardium. Although clinically relevant concentrations of TZM had no effect on proliferation, apoptosis, or size of the c-kit-positive hCDC subpopulation, in vitro assays demonstrated diminished potential for cardiogenic differentiation and impaired ability to form microvascular networks in TZM-treated cells. The functional benefit of hCDCs injected into the border zone of acutely infarcted mouse hearts was abrogated by TZM: infarcted animals treated with TZM + hCDCs had a lower ejection fraction, thinner infarct scar, and reduced capillary density in the infarct border zone compared with animals that received hCDCs alone (n = 12 per group). Collectively, these results indicate that TZM inhibits the cardiomyogenic and angiogenic capacities of hCDCs in vitro and abrogates the morphological and functional benefits of hCDC transplantation in vivo. Thus, TZM impairs the function of human resident cardiac stem cells, potentially contributing to TZM cardiotoxicity

Finite-size scaling of the helicity modulus of the two-dimensional O(3) model

Using Monte Carlo methods, we compute the finite-size scaling function of the helicity modulus $\Upsilon$ of the two-dimensional O(3) model and compare it to the low temperature expansion prediction. From this, we estimate the range of validity for the leading terms of the low temperature expansion of the finite-size scaling function and for the low temperature expansion of the correlation length. Our results strongly suggest that a Kosterlitz-Thouless transition at a temperature $T > 0$ is extremely unlikely in this model.Comment: 4 pages, 3 Postscript figures, to appear in Phys. Rev. B Jan. 1997 as a Brief Repor

Asymptotic behavior in the scalar field theory

An asymptotic solution of the system of Schwinger-Dyson equations for four-dimensional Euclidean scalar field theory with interaction $\frac{\lambda}{2}(\phi^*\phi)^2$ is obtained. For $\lambda>\lambda_{cr}=16\pi^2$ the two-particle amplitude has the pathology-free asymptotic behavior at large momenta. For $\lambda<\lambda_{cr}$ the amplitude possesses Landau-type singularity.Comment: 16 pages; journal version; references adde

Cluster update and recognition

We present a fast and robust cluster update algorithm that is especially efficient in implementing the task of image segmentation using the method of superparamagnetic clustering. We apply it to a Potts model with spin interactions that are are defined by gray-scale differences within the image. Motivated by biological systems, we introduce the concept of neural inhibition to the Potts model realization of the segmentation problem. Including the inhibition term in the Hamiltonian results in enhanced contrast and thereby significantly improves segmentation quality. As a second benefit we can - after equilibration - directly identify the image segments as the clusters formed by the clustering algorithm. To construct a new spin configuration the algorithm performs the standard steps of (1) forming clusters and of (2) updating the spins in a cluster simultaneously. As opposed to standard algorithms, however, we share the interaction energy between the two steps. Thus the update probabilities are not independent of the interaction energies. As a consequence, we observe an acceleration of the relaxation by a factor of 10 compared to the Swendson and Wang procedure.Comment: 4 pages, 2 figure