Concurrent Program Verification with Invariant-Guided Underapproximation

Automatic verification of concurrent programs written in low-level languages like ANSI-C is an important task as multi-core architectures are gaining widespread adoption. Formal verification, although very valuable for this domain, rapidly runs into the state-explosion problem due to multiple thread interleavings. Recently, Bounded Model Checking (BMC) has been used for this purpose, which does not scale in practice. In this work, we develop a method to further constrain the search space for BMC techniques using underapproximations of data flow of shared memory and lazy demand-driven refinement of the approximation. A novel contribution of our method is that our underapproximation is guided by likely data-flow invariants mined from dynamic analysis and our refinement is based on proof-based learning. We have implemented our method in a prototype tool. Initial experiments on benchmark examples show potential performance benefit

Epidemiology and seasonality of respiratory viral infections in hospitalized children in Kuala Lumpur, Malaysia: a retrospective study of 27 years

<p>Abstract</p> <p>Background</p> <p>Viral respiratory tract infections (RTI) are relatively understudied in Southeast Asian tropical countries. In temperate countries, seasonal activity of respiratory viruses has been reported, particularly in association with temperature, while inconsistent correlation of respiratory viral activity with humidity and rain is found in tropical countries. A retrospective study was performed from 1982-2008 to investigate the viral etiology of children (≤ 5 years old) admitted with RTI in a tertiary hospital in Kuala Lumpur, Malaysia.</p> <p>Methods</p> <p>A total of 10269 respiratory samples from all children ≤ 5 years old received at the hospital's diagnostic virology laboratory between 1982-2008 were included in the study. Immunofluorescence staining (for respiratory syncytial virus (RSV), influenza A and B, parainfluenza types 1-3, and adenovirus) and virus isolation were performed. The yearly hospitalization rates and annual patterns of laboratory-confirmed viral RTIs were determined. Univariate ANOVA was used to analyse the demographic parameters of cases. Multiple regression and Spearman's rank correlation were used to analyse the correlation between RSV cases and meteorological parameters.</p> <p>Results</p> <p>A total of 2708 cases were laboratory-confirmed using immunofluorescence assays and viral cultures, with the most commonly detected being RSV (1913, 70.6%), parainfluenza viruses (357, 13.2%), influenza viruses (297, 11.0%), and adenovirus (141, 5.2%). Children infected with RSV were significantly younger, and children infected with influenza viruses were significantly older. The four main viruses caused disease throughout the year, with a seasonal peak observed for RSV in September-December. Monthly RSV cases were directly correlated with rain days, and inversely correlated with relative humidity and temperature.</p> <p>Conclusion</p> <p>Viral RTIs, particularly due to RSV, are commonly detected in respiratory samples from hospitalized children in Kuala Lumpur, Malaysia. As in temperate countries, RSV infection in tropical Malaysia also caused seasonal yearly epidemics, and this has implications for prophylaxis and vaccination programmes.</p

Fractional mathematical model of Listeria infection caused by pre-cooked package food

This article introduces a novel mathematical approach for modeling and analyzing Listeria infection dynamics by considering a system of fractional-order differential equations to understand the complexities. The homotopy perturbation general transform method (HPGTM) is applied to derive approximate solutions for the fractional-order Listeria infection model to obtain valuable insights. The obtained numerical and graphical solutions are rigorously analyzed to explore the effect of fractional orders on the dynamics of Listeria infections. Furthermore, we explore the existence, uniqueness, and stability properties of the solutions, unveiling the critical parameters influencing infection spread and persistence