Model Checker Execution Reports

Software model checking constitutes an undecidable problem and, as such, even an ideal tool will in some cases fail to give a conclusive answer. In practice, software model checkers fail often and usually do not provide any information on what was effectively checked. The purpose of this work is to provide a conceptual framing to extend software model checkers in a way that allows users to access information about incomplete checks. We characterize the information that model checkers themselves can provide, in terms of analyzed traces, i.e. sequences of statements, and safe cones, and present the notion of execution reports, which we also formalize. We instantiate these concepts for a family of techniques based on Abstract Reachability Trees and implement the approach using the software model checker CPAchecker. We evaluate our approach empirically and provide examples to illustrate the execution reports produced and the information that can be extracted

High and Efficient Production of Nanomaterials by Microfluidic Reactor Approaches

This chapter overviews different approaches for the synthesis of nanostructured materials based on alternative methodologies to the most conventional and widespread colloidal wet chemical route and with a great potential applicability to large-scale and continuous production of nanomaterials. Their major outcomes, current progress in synthesis of micro and nanostructures by using microfluidics techniques and potential applications for the next future are reviewed throughout three different sections. Emphasis is placed on nanomaterials production basics, nanomaterials production techniques and microfluidic reactors (types, materials, designs). The integration of nanoparticle and microreactor technologies delivers enormous possibilities for the further development of novel materials and reactors. In this chapter, recent achievements in the synthesis of nanoparticles in microfluidic reactors are stated. A variety of strategies for synthesizing inorganic and polymeric nanoparticles are presented and compared, including continuous flow, gas–liquid segmented flow and droplet-based microreactor

Geofences on the Blockchain: Enabling Decentralized Location-based Services

A decentralized ride- or carsharing application is among the early proposals of what smart contracts on blockchains may enable in the future. To facilitate use cases in the field of location-based services (LBS), smart contracts need to receive trustworthy positioning information, and be able to process them. We propose an approach on how geofences can be defined in smart contracts, and how supplied positions can be evaluated on whether they are contained in the geofence or not. The approach relies on existing location encoding systems like Geohashes and S2 cells that can transform polygons into a grid of cells. These can be stored in a smart contract to represent a geofence. An oracle run by a mobile network provider can submit network-based positioning information to the contract, that compares it with the geofence. We evaluate the location encoding systems on their ability to model city geofences and mobile network cell position estimates and analyze the costs associated with storing and evaluating received oracle-positions in an Ethereum-based smart contract implementation. Our results show that S2 encodings perform better than Geohashes, that the one-time cost of geofence definition corresponds linearly with the number of grid cells used, and that the evaluation of oracle-submitted locations does not incur high costs

A Discrete Time Mathematical Model on Lung Cancer Incorporating Smokers and Non Smokers

Cancer epidemiology is the branch of epidemiology concerned with the disease cancer. Cancer epidemiology uses epidemiological methods to find the cause of cancer and to identify and develop improved treatments. In this paper, we construct and analyze a discrete time mathematical model on lung cancer involving smokers and non smokers. We derive the two equilibrium points namely smoke free and smoke induced equilibrium and analyze the conditions in which the equilibrium points are stable or unstable. We derive the basic reproduction number of the model. Finally, we prove our theoretical results using numerical simulations through MATLAB

Stability Analysis of a Discrete Time Model on Plant-Soil Interactions

In this paper, a nonlinear mathematical model on plant soil interactions is proposed and analyzed. We consider the variables namely, density of the plant species, nutrient concentration in the soil and in the plant for metabolic activity. We consider that the growth rate of the plant species is dependent on the density of the nutrient concentration in the plant. The relationship between the concentration and the rate of uptake is often described quantitatively by Michaelis?Menten kinetics. We discretize the model by applying Backward Euler method and analyse the stability of the model both locally and globally. We analyse the nutrient concentration in Tomato plant and provide numerical simulations for the dynamical behaviour of plant soil interactions for each nutrient. The numerical simulations are provided using MATLAB

Adjustment of model parameters to estimate distribution transformers remaining lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.Fil: Jimenez, Victor Adrian. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Will, Adrian L. E.. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Gotay Sardiñas, Jorge. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Rodriguez, Sebastian Alberto. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentin

Murphy Scale: A Locational Equivalent Intensity Scale for Hazard Events

Empirical cross-hazard analysis and prediction of disaster vulnerability, resilience, and risk requires a common metric of hazard strengths across hazard types. In this paper, the authors propose an equivalent intensity scale for cross-hazard evaluation of hazard strengths of events for entire durations at locations. The proposed scale is called the Murphy Scale, after Professor Colleen Murphy. A systematic review and typology of hazard strength metrics is presented to facilitate the delineation of the defining dimensions of the proposed scale. An empirical methodology is introduced to derive equivalent intensities of hazard events on a Murphy Scale. Using historical data on impacts and hazard strength indicators of events from 2013 to 2017, the authors demonstrate the utility of the proposed methodology for computing the equivalent intensities for earthquakes and tropical cyclones. As part of a new area of research called hazard equivalency, the proposed Murphy Scale paves the way toward creating multi-hazard hazard maps. The proposed scale can also be leveraged to facilitate hazard communication regarding past and future local experiences of hazard events for enhancing multi-hazard preparedness, mitigation, and emergency response

Equivalent Hazard Magnitude Scale

Hazard magnitude scales are widely adopted to facilitate communication regarding hazard events and the corresponding decision making for emergency management. A hazard magnitude scale measures the strength of a hazard event considering the natural forcing phenomena and the severity of the event with respect to average entities at risk. However, existing hazard magnitude scales cannot be easily adapted for comparative analysis across different hazard types. Here, we propose an equivalent hazard magnitude scale to measure the hazard strength of an event across multiple types of hazards. We name the scale the Gardoni Scale after Professor Paolo Gardoni. We design the equivalent hazard magnitude on the Gardoni Scale as a linear transformation of the expectation of a measure of adverse impact of a hazard event given average exposed value and vulnerability. With records of 12 hazard types from 1900 to 2020, we demonstrate that the equivalent magnitude can be empirically derived with historical data on hazard magnitude indicators and records of event impacts. In this study, we model the impact metric as a function of fatalities, total affected population, and total economic damage. We show that hazard magnitudes of events can be evaluated and compared across hazard types. We find that tsunami and drought events tend to have large hazard magnitudes, while tornadoes are relatively small in terms of hazard magnitude. In addition, we demonstrate that the scale can be used to determine hazard equivalency of individual historical events. For example, we compute that the hazard magnitude of the February 2021 North American cold wave event affecting the southern states of the United States of America was equivalent to the hazard magnitude of Hurricane Harvey in 2017 or a magnitude 7.5 earthquake. Future work will expand the current study in hazard equivalency to modelling of local intensities of hazard events and hazard conditions within a multi-hazard context