De acordo com o quarto relatório do Intergovernmental Panel on Climate Change (IPCC), as regiões semiáridas do mundo estarão entre as mais afetadas pelos impactos das mudanças climáticas globais. Estudos realizados pelo Ministério do Meio Ambiente (MMA), em 2007, confirmam que, no Nordeste brasileiro, não apenas choverá menos e mais irregularmente, mas, também, haverá mais secas, devido ao aquecimento da temperatura. Diante dos diversos impactos sociais, ambientais e econômicos possíveis nesses cenários, é de fundamental importância a verificação de alternativas sustentáveis para o semiárido brasileiro. Este artigo tem por objetivo avaliar o potencial de algumas das tecnologias sociais (TS) de convivência com o semiárido, desenvolvidas por diversas organizações, para a mitigação das mudanças climáticas e a promoção de desenvolvimento humano. Constata-se que as TS tem grande potencial para auxiliar na mitigação e na adaptação das mudanças climáticas, ao mesmo tempo que promovem melhorias na qualidade de vida das localidades onde estão sendo desenvolvidas.

Interpolant-based model checking has been shown effective on large verification instances, as it efficiently combines automated abstraction and fixed-point checks. On the other hand, methods based on variable quantification have proved their ability to remove free inputs, thus projecting the search space over state variables.In this paper we propose an integrated approach combining the abstraction power of interpolation with techniques relying on AIG and/or BDD representations of states, supporting variable quantification and fixed-point checks. The underlying idea of this combination is to adopt AIG-or BDD-based quantifications to limit and restrict the search space (and the complexity) of the interpolant-based approach. The exploited strategies, individually well-known, are integrated with a new flavor, specifically designed to improve their effectiveness on large verification instances.Experimental results, oriented to hard-to-solve verification problems, show the robustness of our approach.

Scheduling, or planning, is widely recognized as a very important step in several domains such as high level synthesis, real-time systems, and everyday applications. Given a problem described by a number of actions and their relationships, finding a schedule, or a plan, means to find a way to perform all the actions minimizing a specific cost function. The goal of this paper is to develop, analyze and compare different scheduling techniques on a new scheduling/planning problem. The new application domain is aircraft maintenance. It shares with previous ones the underlying problem definition, but it also unveils brand new challenging characteristics, and a different optimization target. We show how to model the problem in a suitable way, and how to solve it with different methodologies going from Satisfiability solvers and Binary Decision Diagrams, to Timed Automata and Coloured Petri Nets. New ideas are put forward in the different domains having efficiency and scalability as main targets. Experimental results stress the different techniques, showing their application range and limits, and defining advantages and disadvantages of the underlying models. Overall, general-purpose tools have been easily applied to our problem, but failed as far as efficiency was concerned. The satisfiability-based approach proved to be faster and more scalable, being able to solve instances 3 − 4 times larger. To sum up, our contributions range from modeling the aircraft maintenance problem as a scheduling instance, to coding this problem with home-made and general-purpose tools, to dovetailing exact and heuristic techniques, and comparing these techniques in terms of efficiency and scalability.

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We study recent developments in quantum computing (QC)