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Acid mine drainage (AMD) remains a major environmental challenge for the mining industry. The preferred options for effectively limiting the environmental impact of AMD consist in controlling the reactions through the use of preventative techniques. Their principal objective is to exclude at least one of the constitutive elements of the chemical reactions, i.e. water, oxygen, or sulfidic minerals. The article recalls the basic principles and reviews different approaches for the prevention and control of AMD upon mine closure. The main methods include multi-layer covers, water covers, and an elevated water table (with a mono-layer cover). Their main advantages, limitations and uncertainties are addressed. Alternative approaches, such as environmental desulphurization and co-disposal of waste rock and tailings, are also discussed.

Using a combination of the abilities of AFM to scan in contact mode and record force-distance curves, we have shown a novel method to study electrostatic charging of particles. By measuring the length of the long range electrostatic interaction, we are able to compare different mechanisms of generating charge and to study the effect of RH on charge dissipation.

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We consider the problem of type-directed component-based synthesis where, given a set of (typed) components and a query type, the goal is to synthesize a term that inhabits the query. Classical approaches based on proof search in intuitionistic logics do not scale up to the standard libraries of modern languages, which span hundreds or thousands of components. Recent graph reachability based methods proposed for Java do scale, but only apply to monomorphic data and components: polymorphic data and components infinitely explode the size of the graph that must be searched, rendering synthesis intractable. We introduce type-guided abstraction refinement (TYGAR), a new approach for scalable type-directed synthesis over polymorphic datatypes and components. Our key insight is that we can overcome the explosion by building a graph over abstract types which represent a potentially unbounded set of concrete types. We show how to use graph reachability to search for candidate terms over abstract types, and introduce a new algorithm that uses proofs of untypeability of ill-typed candidates to iteratively refine the abstraction until a well-typed result is found. We have implemented TYGAR in H+, a tool that takes as input a set of Haskell libraries and a query type, and returns a Haskell term that uses functions from the provided libraries to implement the query type. Our support for polymorphism allows H+ to work with higher-order functions and type classes, and enables more precise queries due to parametricity. We have evaluated H+ on 44 queries using a set of popular Haskell libraries with a total of 291 components. H+ returns an interesting solution within the first five results for 32 out of 44 queries. Our results show that TYGAR allows H+ to rapidly return well-typed terms, with the median time to first solution of just 1.4 seconds. Moreover, we observe that gains from iterative refinement over exhaustive enumeration are more pronounced on harder queries. CCS Concepts: • Theory of computation → Automated reasoning; • Software and its engineering → Automatic programming.