Analog Property Checkers: A Ddr2 Case Study

The formal specification component of verification can be exported to simulation through the idea of property checkers. The essence of this approach is the automatic construction of an observer from the specification in the form of a program that can be interfaced with a simulator and alert the user if the property is violated by a simulation trace. Although not complete, this lighter approach to formal verification has been effectively used in software and digital hardware to detect errors. Recently, the idea of property checkers has been extended to analog and mixed-signal systems. In this paper, we apply the property-based checking methodology to an industrial and realistic example of a DDR2 memory interface. The properties describing the DDR2 analog behavior are expressed in the formal specification language stl/psl in form of assertions. The simulation traces generated from an actual DDR2 interface design are checked with respect to the stl/psl assertions using the amt tool. The focus of this paper is on the translation of the official (informal and descriptive) specification of two non-trivial DDR2 properties into stl/psl assertions. We study both the benefits and the current limits of such approach

Model-free reinforcement learning for stochastic parity games

This paper investigates the use of model-free reinforcement learning to compute the optimal value in two-player stochastic games with parity objectives. In this setting, two decision makers, player Min and player Max, compete on a finite game arena - a stochastic game graph with unknown but fixed probability distributions - to minimize and maximize, respectively, the probability of satisfying a parity objective. We give a reduction from stochastic parity games to a family of stochastic reachability games with a parameter ε, such that the value of a stochastic parity game equals the limit of the values of the corresponding simple stochastic games as the parameter ε tends to 0. Since this reduction does not require the knowledge of the probabilistic transition structure of the underlying game arena, model-free reinforcement learning algorithms, such as minimax Q-learning, can be used to approximate the value and mutual best-response strategies for both players in the underlying stochastic parity game. We also present a streamlined reduction from 112-player parity games to reachability games that avoids recourse to nondeterminism. Finally, we report on the experimental evaluations of both reductions

Retrospective case note review of chronic spontaneous urticaria outcomes and adverse effects in patients treated with omalizumab or ciclosporin in UK secondary care.

BACKGROUND: Omalizumab is approved in the UK as add-on treatment for chronic spontaneous urticaria (CSU) in patients with inadequate response to H1-antihistamines. Ciclosporin is an established but unlicensed 3rd line option for CSU. Two parallel retrospective observational studies were conducted to describe outcomes of treatment and adverse events with omalizumab or ciclosporin for CSU treatment. METHODS: Data from UK specialist centres prescribing omalizumab (five centres) or ciclosporin (three centres) in CSU patients were collected from hospital records by clinical staff and pooled for analysis. RESULTS: Forty-six patients prescribed omalizumab and 72 patients prescribed ciclosporin were included. Twenty-two (48%) omalizumab-treated patients had paired Urticaria Activity Scores (UAS7), showing a 25.4 point improvement during treatment (P < 0.0001). Paired Dermatology Life Quality Index (DLQI) was available in 28 (61%) omalizumab-treated and 17 (24%) ciclosporin-treated patients. At least a 75% improvement in DLQI score was observed in 79% of omalizumab-treated and 41% of ciclosporin-treated patients, and 65% of omalizumab-treated patients had complete resolution of their quality-of-life impairment (DLQI 0-1) versus 21% of ciclosporin-treated patients. Clinician comments reported symptom clearance in 15/36 (42%) omalizumab-treated and 10/60 (17%) ciclosporin-treated patients. Proportions of patients with adverse events were similar but those for omalizumab resembled CSU symptoms, making causality assignment difficult, whereas those for ciclosporin were consistent with its known adverse effect profile. CONCLUSIONS: Validated patient-reported measures of disease severity and quality of life should be used routinely in CSU management. Based on clinician comments and DLQI scores, symptoms and quality of life showed a greater improvement in the omalizumab-treated cohort than in the ciclosporin-treated cohort

Reward Shaping for Reinforcement Learning with Omega-Regular Objectives

Recently, successful approaches have been made to exploit good-for-MDPs automata (B\"uchi automata with a restricted form of nondeterminism) for model free reinforcement learning, a class of automata that subsumes good for games automata and the most widespread class of limit deterministic automata. The foundation of using these B\"uchi automata is that the B\"uchi condition can, for good-for-MDP automata, be translated to reachability. The drawback of this translation is that the rewards are, on average, reaped very late, which requires long episodes during the learning process. We devise a new reward shaping approach that overcomes this issue. We show that the resulting model is equivalent to a discounted payoff objective with a biased discount that simplifies and improves on prior work in this direction

SAT-based Explicit LTL Reasoning

We present here a new explicit reasoning framework for linear temporal logic (LTL), which is built on top of propositional satisfiability (SAT) solving. As a proof-of-concept of this framework, we describe a new LTL satisfiability tool, Aalta\_v2.0, which is built on top of the MiniSAT SAT solver. We test the effectiveness of this approach by demonnstrating that Aalta\_v2.0 significantly outperforms all existing LTL satisfiability solvers. Furthermore, we show that the framework can be extended from propositional LTL to assertional LTL (where we allow theory atoms), by replacing MiniSAT with the Z3 SMT solver, and demonstrating that this can yield an exponential improvement in performance

Renal outcome in patients with congenital anomalies of the kidney and urinary tract.

15openopenSanna-Cherchi S; Ravani P; Corbani V; Parodi S; Haupt R; Piaggio G; Innocenti ML; Somenzi D; Trivelli A; Caridi G; Izzi C; Scolari F; Mattioli G; Allegri L; Ghiggeri GM.Sanna Cherchi, S; Ravani, P; Corbani, V; Parodi, S; Haupt, R; Piaggio, G; Innocenti, Ml; Somenzi, D; Trivelli, A; Caridi, G; Izzi, C; Scolari, Francesco; Mattioli, G; Allegri, L; Ghiggeri, G. M

Localization of a gene for nonsyndromic renal hypodysplasia to chromosome 1p32-33.

Nonsyndromic defects in the urinary tract are the most common cause of end-stage renal failure in children and account for a significant proportion of adult nephropathy. The genetic basis of these disorders is not fully understood. We studied seven multiplex kindreds ascertained via an index case with a nonsyndromic solitary kidney or renal hypodysplasia. Systematic ultrasonographic screening revealed that many family members harbor malformations, such as solitary kidneys, hypodysplasia, or ureteric abnormalities (in a total of 29 affected individuals). A genomewide scan identified significant linkage to a 6.9-Mb segment on chromosome 1p32-33 under an autosomal dominant model with reduced penetrance (peak LOD score 3.5 at D1S2652 in the largest kindred). Altogether, three of the seven families showed positive LOD scores at this interval, demonstrating heterogeneity of the trait (peak HLOD 3.9, with 45% of families linked). The chromosome 1p32-33 interval contains 52 transcription units, and at least 23 of these are expressed at stage E12.5 in the murine ureteric bud and/or metanephric mesenchyme. These data show that autosomal dominant nonsyndromic renal hypodysplasia and associated urinary tract malformations are genetically heterogeneous and identify a locus for this common cause of human kidney failure

Variable Compression in ProbLog

In order to compute the probability of a query, ProbLog represents the proofs of the query as disjunctions of conjunctions, for which a Reduced Ordered Binary Decision Diagram (ROBDD) is computed. The paper identifies patterns of Boolean variables that occur in Boolean formulae, namely AND-clusters and OR-clusters. Our method compresses the variables in these clusters and thus reduces the size of ROBDDs without affecting the probability. We give a polynomial algorithm that detects AND-clusters in disjunctive normal form (DNF) Boolean formulae, or OR-clusters in conjunctive normal form (CNF) Boolean formulae. We do an experimental evaluation of the effects of AND-cluster compression for a real application of ProbLog. With our prototype implementation we have a significant improvement in performance (up to 87%) for the generation of ROBDDs. Moreover, compressing AND-clusters of Boolean variables in the DNFs makes it feasible to deal with ProbLog queries that give rise to larger DNFs.acceptance rate: 38%status: publishe