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We present a procedure to infer a typing for an arbitrary λ-term M in an intersection-type system that translates into exactly the call-by-name (resp., call-by-value) evaluation of M. Our framework is the recently developed System E which augments intersection types with expansion variables. The inferred typing for M is obtained by setting up a unification problem involving both type variables and expansion variables, which we solve with a confluent rewrite system. The inference procedure is compositional in the sense that typings for different program components can be inferred in any order, and without knowledge of the definition of other program components. Using expansion variables lets us achieve a compositional inference procedure easily. Termination of the procedure is generally undecidable. The procedure terminates and returns a typing if the input M is normalizing according to call-by-name (resp., call-by-value). The inferred typing is exact in the sense that the exact call-by-name (resp., call-by-value) behaviour of M can be obtained by a (polynomial) transformation of the typing. The inferred typing is also principal in the sense that any other typing that translates the call-by-name (resp., call-by-value) evaluation of M can be obtained from the inferred typing for M using a substitution-based transformation.

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The evolution of pharmaceutical competition since Congress passed the Hatch-Waxman Act in 1984 raises questions about whether the act's intended balance of incentives for cost savings and continued innovation has been achieved. Generic drug usage and challenges to brand-name drugs' patents have increased markedly, resulting in greatly increased cost savings but also potentially reduced incentives for innovators. Congress should review whether Hatch-Waxman is achieving its intended purpose of balancing incentives for generics and innovation. It also should consider whether the law should be amended so that some of its provisions are brought more in line with recently enacted legislation governing approval of so-called biosimilars, or the corollary for biologics of generic competition for small-molecule drugs.

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Induced by a literature review, this paper presents a framework of dimensions and indicators highlighting the underpinning aspects and values of social learning within teacher groups. Notions of social networks, communities of practice and learning teams were taken as the main perspectives to influence this social learning framework. The review exercise resulted in four dimensions: (1) practice, (2) domain and value creation, (3) collective identity and (4) organization. The indicators corresponding to these dimensions serve as the foundation for understanding social learning in practice. The framework of dimensions and indicators can be of assistance for researchers as well as teacher groups that aim to assess their views on social learning and analyse whether these views fit the learning goals of the group, or that adjustments are required. In this way, learning processes within groups of teachers can be improved.

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We examined the taxonomic resolution of zooplankton data required to identify ocean basin scale biogeographic zonation in the Southern Ocean. A 2,154 km transect was completed south of Australia. Sea surface temperature (SST) measured at 1 min intervals showed that seven physical zones were sampled. Zooplankton were collected at a spatial resolution of similar to 9.2 km with a continuous plankton recorder, identified to the highest possible taxonomic resolution and enumerated. Zooplankton assemblage similarity between samples was calculated using the Bray-Curtis index for the taxonomic levels of species, genus, family, order and class after first log(10)(x + 1) (LA) and then presence/absence (PA) transformation of abundance data. Although within and between zone sample similarity increased with decreasing taxonomic resolution, for both data transformations, cluster analysis demonstrated that the biogeographic separation of zones remained at all taxonomic levels when using LA data. ANOSIM confirmed this, detecting significant differences in zooplankton assemblage structure between all seven a priori determined physical zones for all taxonomic levels when using the LA data. In the case of the PA data for the complete data set, and both LA and PA data for a crustacean only data set, no significant differences were detected between zooplankton assemblages in the Polar frontal zone (PFZ) and inter-PFZ at any taxonomic level. Loss of information at resolutions below the species level, particularly in the PA data, prevented the separation of some zones. However, the majority of physical zones were biogeographically distinct from species level to class using both LA and PA transformations. Significant relationships between SST and zooplankton community structure, summarised as NMDS scores, at all taxonomic levels, for both LA and PA transformations, and complete and crustacean only data sets, highlighted the biogeographic relevance of low resolution taxonomic data. The retention of biogeographic information in low taxonomic resolution data shows that data sets collected with different taxonomic resolutions may be meaningfully merged for the post hoc generation of Southern Ocean time series.