80 research outputs found

    In-hospital and out-of-hospital stroke in patients with COVID-19: two different diseases?

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    Background: Ischemic stroke is a known complication of COVID-19. It may have a different pathogenesis and worse outcome compared to stroke in patients without COVID-19. Furthermore, patients with COVID-19 and out-of-hospital stroke onset might have different characteristics compared to patients with COVID-19 and in-hospital stroke onset. The aim of our study was to analyze the characteristics of patients with stroke with and without COVID-19 and of patients with COVID-19 with in-hospital and out-of-hospital stroke. Methods: We performed a retrospective study of all consecutive patients admitted to our hospital with ischemic stroke between October 2020 and February 2021. We compared functional outcome, lab test, demographic, and clinical characteristics between patients with or without COVID-19. We performed a sub-analysis comparing patients with COVID-19 and in-hospital and out-of-hospital stroke onset. Results: We included in the final analysis 137 patients of whom 26 with COVID-19. Half (13) had out-of-hospital stroke and half in-hospital stroke onset. Overall, patients with COVID-19 had higher mortality compared to the control group (27% vs 9%, p: 0.02), and non-significantly lower rate of good functional outcome (50% vs 63%, p: 0.22). Patients with COVID-19 and out-of-hospital stroke had higher rate of good functional outcome (69% vs 39%, p: 0.05), higher lymphocyte count, and lower D-dimer compared with patients with in-hospital stroke onset. Conclusions: Patients with stroke and COVID-19 had higher mortality compared to patients without COVID-19. Among patients with COVID-19 those with out-of-hospital stroke had better outcome and fewer blood test abnormalities compared to patients with in-hospital stroke

    Ogre and Pythia: An Invariance Proof Method for Weak Consistency Models

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    We design an invariance proof method for concurrent programs parameterised by a weak consistency model. The calculational design of the invariance proof method is by abstract interpretation of a truly parallel analytic semantics. This generalises the methods by Lamport and Owicki-Gries for sequential consistency. We use cat as an example of language to write consistency specifications of both concurrent programs and machine architectures

    Determinacy analysis for logic programs using mode and type information

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    We propose an analysis for detecting procedures and goals that are deterministic (i.e. that produce at most one solution), or predicates whose clause tests are mutually exclusive (which implies that at most one of their clauses will succeed) even if they are not deterministic (because they cali other predicates that can produce more than one solution). Applications of such determinacy information include detecting programming errors, performing certain high-level program transformations for improving search efñciency, optimizing low level code generation and parallel execution, and estimating tighter upper bounds on the computational costs of goals and data sizes, which can be used for program debugging, resource consumption and granularity control, etc. We have implemented the analysis and integrated it in the CiaoPP system, which also infers automatically the mode and type information that our analysis takes as input. Experiments performed on this implementation show that the analysis is fairly accurate and efncient

    Program Verification by Using DISCOVERER

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    Recent advances in program verification indicate that various verification problems can be reduced to semi-algebraic system (SAS for short) solving. An SAS consists of polynomial equations and polynomial inequalities. Algorithms for quantifier elimination of real closed fields are the general method for those problems. But the general method usually has low efficiency for specific problems. To overcome the bottleneck of program verification with a symbolic approach, one has to combine special techniques with the general method. Based on the work of complete discrimination systems of polynomials [33,31], we invented new theories and algorithms [32,30,35] for SAS solving and partly implemented them as a real symbolic computation tool in Maple named DISCOVERER. In this paper, we first summarize the results that we have done so far both on SAS-solving and program verification with DISCOVERER, and then discuss the future work in this direction, including SAS-solving itself, termination analysis and invariant generation of programs, and reachability computation of hybrid systems etc. ? IFIP International Federation for Information Processing 2008.EI
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