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The increasing capabilities of smartphones is paving way to novel applications through the crowd-sourcing of these untapped resources, to form hyperlocal meshes commonly known as edge-clouds. While a relevant body-of-work is already available for the underlying networking, computing and storage facilities, security and privacy remain second class citizens. In this paper we present Panoptic, an edge-cloud system that enables the search for missing people, similar to the commonly known Amber alert system, in high density scenarios where wireless infrastructure might be limited (WiFi and LTE), e.g. concerts, while featuring privacy and security by design. Since the limited resources present in the mobile devices, namely battery capacity, Panoptic offers a computing offloading that tries to minimize data leakage while offering acceptable levels of performance. Our results show that it is achievable to run these algorithms in an edge-cloud configuration and that it is beneficial to use this architecture to lower data transfer through the wireless infrastructure while enforcing privacy. Results from our experimental evaluation show that the security layer does not impose a significant overhead, and only accounts for 2% of the total execution time for an edge cloud comprised by, but not limited to, 8 devices.

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This paper presents an extensive analysis in relation to transforming electric distribution networks in order to accommodate large quantities of variable renewable energy sources (vRESs). For this purpose, a multi-stage and stochastic mixed integer linear programming (S-MILP) model is employed. The algebraic model developed optimally allocates energy storage systems (ESSs) along with an optimal dynamic distribution network switching. For the analysis, a standard IEEE 119-bus distribution network system was used as a case study. Test results reveal that the joint optimization of ESSs and network reconfiguration markedly increase flexibility in existing systems, leading to an increase in the levels of renewables integration and utilization. Moreover, the analysis of the results shows the prospect of such systems in going fully "carbonfree", i.e. with vRES power entirely meeting system demand. Generally, the current work demonstrates that a more effective integration and utilization of large-scale vRESs is possible when existing systems are equipped with enabling technologies that are already commercially available.

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Manaus, a city of more than two million people, suffers problems arising from strong sunlight and aggravated by several factors, such as traffic congestion and greenhouse gas emissions generated by evaporation and burning of fuel. The present study examined Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) emissions in an urban area of the city using different methodologies. CO and NO2 were measured using automated and passive analyzers, respectively. Meanwhile, direct monitoring of these pollutants was performed in vehicular sources in the vicinity of sampling locations. Results showed that levels of carbon monoxide vary over time, being higher during peak movement of vehicles. NO2 values have exceeded the recommendations of the World Health Organization (WHO), and monitoring at source showed high levels of CO and NO2 emissions to the atmosphere.

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This note, reporting the homonym keynote presented in the International Symposium on Molecular Logic and Computational Synthetic Biology 2018, traces an informal roadmap on Dynamic Logic (DL) field, focusing on its versatility and resilience to be adjusted and adopted in a wide class of application domains and computational paradigms. The exposition argues the room for developments on tagging DL to the analysis of synthetic biologic domain. © 2019, Springer Nature Switzerland AG.

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