Exact Algorithms for Solving Stochastic Games

Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games

Forward Stochastic Reachability Analysis for Uncontrolled Linear Systems using Fourier Transforms

We propose a scalable method for forward stochastic reachability analysis for uncontrolled linear systems with affine disturbance. Our method uses Fourier transforms to efficiently compute the forward stochastic reach probability measure (density) and the forward stochastic reach set. This method is applicable to systems with bounded or unbounded disturbance sets. We also examine the convexity properties of the forward stochastic reach set and its probability density. Motivated by the problem of a robot attempting to capture a stochastically moving, non-adversarial target, we demonstrate our method on two simple examples. Where traditional approaches provide approximations, our method provides exact analytical expressions for the densities and probability of capture.Comment: V3: HSCC 2017 (camera-ready copy), DOI updated, minor changes | V2: Review comments included | V1: 10 pages, 12 figure

Mathematical Approach to Security Risk Assessment

The goal of this paper is to provide a mathematical threat modeling methodology and a threat risk assessment tool that may assist security consultants at assessing the security risks in their protected systems/plants, nuclear power plants and stores of hazardous substances: explosive atmospheres and flammable and combustible gases and liquids, and so forth, and at building an appropriate risk mitigation policy. The probability of a penetration into the protected objects is estimated by combining the probability of the penetration by overcoming the security barriers with a vulnerability model. On the basis of the topographical placement of the protected objects, their security features, and the probability of the penetration, we propose a model of risk mitigation and effective decision making

Learning Physics from Data: a Thermodynamic Interpretation

Experimental data bases are typically very large and high dimensional. To learn from them requires to recognize important features (a pattern), often present at scales different to that of the recorded data. Following the experience collected in statistical mechanics and thermodynamics, the process of recognizing the pattern (the learning process) can be seen as a dissipative time evolution driven by entropy from a detailed level of description to less detailed. This is the way thermodynamics enters machine learning. On the other hand, reversible (typically Hamiltonian) evolution is propagation within the levels of description, that is also to be recognized. This is how Poisson geometry enters machine learning. Learning to handle free surface liquids and damped rigid body rotation serves as an illustration.Comment: Submitted to the proceedings of the Les Houches Summer Schoo

Time above the MIC of piperacillin-tazobactam as a predictor of outcome in pseudomonas aeruginosa bacteraemia.

All rights reserved. Pseudomonas aeruginosa bacteremia is an infection associated with a high mortality rate. Piperacillin-tazobactam is a β-lactam-β-lactamase inhibitor combination that is frequently used for the management of Pseudomonas aeruginosa infections. The pharmacokinetic-pharmacodynamic index associated with in vitro maximal bacterial killing for piperacillin-tazobactam is the percentage of the time between doses at which the free fraction concentration remains above the MIC (%fT>MIC). However, the precise %>MICtarget associated with improved clinical outcomes is unknown. The aim of this study was to investigate the correlation between the survival of patients with Pseudomonas aeruginosa bacteremia and the threshold of the piperacillin-tazobactam %fT>MIC. This retrospective study included all adult patients hospitalized over an 82-month period with Pseudomonas aeruginosa bacteremia and treated with piperacillin-tazobactam. Patients with a polymicrobial infection or those who died within 72 h of the time of collection of a sample for culture were excluded. The %fT>MICof piperacillin-tazobactam associated with in-hospital survival was derived using classification and regression tree analysis. After screening 270 patients, 78 were eligible for inclusion in the study; 18% died during hospitalization. Classification and regression tree analysis identified a %fT>MICof >60.68% to be associated with improved survival, and this remained statistically significant after controlling for clinical covariates (odds ratio=7.74, 95% confidence interval=1.32 to 45.2). In conclusion, the findings recommend dosing of piperacillintazobactam with the aim of achieving a pharmacodynamic target %fT>MICof at least 60% in these patients

2,2′-[(3aRS,7aRS)-Perhydro­benz­imid­azole-1,3-di­yl)bis­(methyl­ene)]diphenol

The molecular structure of the title compound, C21H26N2O2, shows two intra­molecular O—H⋯N hydrogen-bonding inter­actions. In the crystal structure, mol­ecular chains are formed along the c axis through weak C—H⋯O inter­actions. Neighbouring chains are weakly associated along the a axis via C—H⋯π inter­actions

Associations Between Perception of Parental Behavior and “Person Picking an Apple From a Tree” Drawings Among Children With and Without Special Educational Needs (SEN)

The present study examines and compares associations between perceptions of parental acceptance/rejection in 191 Greek school age children (84 inclusion class students and 107 typical class students, age range 10–12), and their “Person Picking an Apple from a Tree” (PPAT) drawings. Perception of parental behavior was measured by the “Parental Acceptance-Rejection Questionnaire” (Rohner and Khaleque, 2005). Drawing content was analyzed quantitatively according to a reliable rating system called the Symbolic Content in PPAT drawings (SC-PPAT: Bat Or et al., 2014, 2017). We employed k-means cluster analysis and obtained three relatively discrete PPAT scripts. Drawing content elements and scripts were found to be associated with children’s perceptions of parental behavior; these associations were found mainly among children with special educational needs (SEN) and boys. Results are discussed in terms of children’s subjective experience, clinical implications, and future research directions

Harnessing sensing systems towards urban sustainability transformation

Peer reviewe

In the Hunt for Therapeutic Targets: Mimicking the Growth, Metastasis, and Stromal Associations of Early-Stage Lung Cancer Using a Novel Orthotopic Animal Model

BackgroundThe existing shortage of animal models that properly mimic the progression of early-stage human lung cancer from a solitary confined tumor to an invasive metastatic disease hinders accurate characterization of key interactions between lung cancer cells and their stroma. We herein describe a novel orthotopic animal model that addresses these concerns and consequently serves as an attractive platform to study tumor–stromal cell interactions under conditions that reflect early-stage lung cancer.MethodsUnlike previous methodologies, we directly injected small numbers of human or murine lung cancer cells into murine's left lung and longitudinally monitored disease progression. Next, we used green fluorescent protein-tagged tumor cells and immuno-fluorescent staining to determine the tumor's microanatomic distribution and to look for tumor-infiltrating immune cells and stromal cells. Finally, we compared chemokine gene expression patterns in the tumor and lung microenvironment.ResultsWe successfully generated a solitary pulmonary nodule surrounded by normal lung parenchyma that grew locally and spread distally over time. Notably, we found that both fibroblasts and leukocytes are recruited to the tumor's margins and that distinct myeloid cell attracting and CCR2-binding chemokines are specifically induced in the tumor microenvironment.ConclusionOur orthotopic lung cancer model closely mimics the pathologic sequence of events that characterizes early-stage human lung cancer propagation. It further introduces new means to monitor tumor–stromal cell interactions and offers unique opportunities to test therapeutic targets under conditions that reflect early-stage lung cancer. We argue that for such purposes our model is superior to lung cancer models that are based either on genetic induction of epithelial transformation or on ectopic transplantation of malignant cells