Functional programming languages for verification tools: experiences with ML and Haskell

We compare Haskell with ML as programming languages for verification tools, based on our experience developing TRUTH in Haskell and the Edinburgh Concurrency Workbench (CWB) in ML. We discuss not only technical language features but also the "worlds" of the languages, for example, the availability of tools and libraries

Ordered Navigation on Multi-attributed Data Words

We study temporal logics and automata on multi-attributed data words. Recently, BD-LTL was introduced as a temporal logic on data words extending LTL by navigation along positions of single data values. As allowing for navigation wrt. tuples of data values renders the logic undecidable, we introduce ND-LTL, an extension of BD-LTL by a restricted form of tuple-navigation. While complete ND-LTL is still undecidable, the two natural fragments allowing for either future or past navigation along data values are shown to be Ackermann-hard, yet decidability is obtained by reduction to nested multi-counter systems. To this end, we introduce and study nested variants of data automata as an intermediate model simplifying the constructions. To complement these results we show that imposing the same restrictions on BD-LTL yields two 2ExpSpace-complete fragments while satisfiability for the full logic is known to be as hard as reachability in Petri nets

OR.NET - Approaches for Risk Analysis and Measures of Dynamically Interconnected Medical Devices

Nowadays, it lacks an open, standardized and dynamic interconnection of medical devices. All existing combinations of medical devices consist of isolated solutions with proprietary interfaces, as no common standards for networking and the exchange of data of medical devices exist. This situation leads to confusing operating rooms and inefficient operations. Thus, new strategies need to be developed for the authorization of dynamically interconnected medical devices. Primarily, those concern of an acquisition and methodical adaption of new requirements and risks resulting from this way of interconnection. The approach is to develop a method for a risk analysis for interconnected medical devices, which is structured modular and consists of a risk assessment of the standalone device and a risk analysis for the interconnection considering the risks involved in the transfer of functions. When interconnecting the medical devices the risk analysis of each of the devices is taken and they are compared by a gap analysis. Through this strategy it will be possible to realize a standard-compliant dynamic interconnection of medical products, which would be advantageous both for clinic operators and producers. This paper presents the current situation of the authorization of combined medical devices and proposes a strategy for the risk management of dynamically interconnected medical devices as a substantial part of the authorization

Phenotyping of <em>Cercospora beticola</em> resistance of sugar beet genotypes by hyperspectral imaging

Cultivation of disease resistant crops is an important strategy in the integrated pest management which is a guiding principle for good agricultural practice. Therefore, high yielding cultivars with resistance to important plant diseases are needed. The integration of resistance sources such as wild relatives or compatible subspecies might help to enhance the resistance of crops and thus to reduce the need for chemical crop protection measures. For the selection of plants with a specific trait, such as resistance to a plant pathogen, precise determination of the genotype and a reliable characterization of the phenotype are necessary. The rather rapid development of molecular methods and knowledge about genes enhanced the genotyping in plant breeding greatly. The phenotyping, however, is still the bottleneck in resistance breeding. As the phenotype is the result of the interaction of the genotype and the environment phenotyping must be reliable, reproducible and non-invasive. The implementation of sensors in phenotyping systems provides many advantages. Hyperspectral imaging sensors are well suited to characterize different plant traits. Cercospora leaf spot (CLS) is the most important foliar disease of sugar beets and is mainly controlled by fungicide applications. The aim of this study was to characterize the resistance of sugar beet genotypes against Cercospora beticola and the development of a hyperspectral imaging system for phenotyping this disease resistance. A hyperspectral microscope that measures reflection in the visible and near-infrared range from 400 to 1000 nm with a magnification of up to 7.3x was established to determine spectral changes on the plant tissue level. Disease development on five genotypes infected with CLS was evaluated and compared under controlled conditions. Two additional genotypes were used to validate the results of the hyperspectral measurement of CLS dynamics. Resistant genotypes had a lower percentage of diseased leaf area, a reduced number of lesions, lesion size and growth rate and a decreased spore production. Apart from the quantitative difference between highly susceptible and more resistant sugar beets, the lesion phenotype varied in size and spatial composition depending on the host genotype. Using the hyperspectral microscope, lesions could be differentiated into subareas based on their spectral characteristics. Sugar beet genotypes with lower disease severity typically had lesions with smaller centers and produced fewer spores in comparison to highly susceptible genotypes. The differences in number of spores per lesion were closely associated to the spectral difference calculated as area between spectral signatures before and after sporulation. The CLS development, analyzed by hyperspectral imaging over ten days, differed depending on the host genotype and the resistance source. For example, lesion development on a resistant genotype carrying two quantitative trait loci (QTL) was characterized by a fast and abrupt change in spectral reflectance, whereas it was slower and ultimately more severe on the closely related genotype lacking the QTL. The analysis of reflectance and transmittance images by calculating spectral vegetation indices and extracting spectral signatures revealed a potential benefit of transmission measurements. Depending on the topic and analysis method, effects were sometimes stronger pronounced in the transmittance data. The resistance against C. beticola was not complete, instead, it can be described as quantitative and rate-reducing. Some resistance parameters such as a decreased sporulation matter particularly with regards to disease epidemics in the field. Based on the hyperspectral images, a detailed analysis of the lesions was possible. The presented method allowed a reliable differentiation of CLS dynamics and the characterization of even subtle differences in resistance. Hyperspectral imaging is a promising tool with the potential to improve the screening process in breeding for CLS resistance

Symbolic Runtime Verification for Monitoring under Uncertainties and Assumptions

Runtime Verification deals with the question of whether a run of a system adheres to its specification. This paper studies runtime verification in the presence of partial knowledge about the observed run, particularly where input values may not be precise or may not be observed at all. We also allow declaring assumptions on the execution which permits to obtain more precise verdicts also under imprecise inputs. To this end, we show how to understand a given correctness property as a symbolic formula and explain that monitoring boils down to solving this formula iteratively, whenever more and more observations of the run are given. We base our framework on stream runtime verification, which allows to express temporal correctness properties not only in the Boolean but also in richer logical theories. While in general our approach requires to consider larger and larger sets of formulas, we identify domains (including Booleans and Linear Algebra) for which pruning strategies exist, which allows to monitor with constant memory (i.e. independent of the length of the observation) while preserving the same inference power as the monitor that remembers all observations. We empirically exhibit the power of our technique using a prototype implementation under two important cases studies: software for testing car emissions and heart-rate monitoring

Endothelial dysfunction as a nexus for endothelial cell-cardiomyocyte miscommunication

Most studies of the heart focus on cardiomyocytes (CM) at the exclusion of other cell types such as myocardial endothelial cells (EC). Such mono-cellular approaches propagate the presumption that EC provide a mere passive lining or supportive role. In fact, EC contribute to a dynamic network regulating vascular tone, cardiac development, and repair. Two distinct EC types, vascular EC and epicardial EC, possess important structural and signaling properties within both the healthy and diseased myocardium. In this review, we address EC-CM interactions in mature, healthy myocardium, followed by a discussion of diseases characterized by EC dysfunction. Finally, we consider strategies to reverse EC-CM miscommunication to improve patients’ outcomes in various cardiovascular diseases