On the typological economy of syntactic transfer: word order and relative clause high/low attachment preference in L3 Brazilian Portuguese

One central question in the formal linguistic study of adult multilingual morphosyntax (i.e., L3/Ln acquisition) involves determining the role(s) the L1 and/or the L2 play(s) at the L3 initial state (e.g., Bardel & Falk, Second Language Research 23: 459–484, 2007; Falk & Bardel, Second Language Research: forthcoming; Flynn et al., The International Journal of Multilingualism 8: 3–16, 2004; Rothman, Second Language Research: forthcoming; Rothman & Cabrelli, On the initial state of L3 (Ln) acquisition: Selective or absolute transfer?: 2007; Rothman & Cabrelli Amaro, Second Language Research 26: 219–289, 2010). The present article adds to this general program, testing Rothman's (Second Language Research: forthcoming) model for L3 initial state transfer, which when relevant in light of specific language pairings, maintains that typological proximity between the languages is the most deterministic variable determining the selection of syntactic transfer. Herein, I present empirical evidence from the later part of the beginning stages of L3 Brazilian Portuguese (BP) by native speakers of English and Spanish, who have attained an advanced level of proficiency in either English or Spanish as an L2. Examining the related domains of syntactic word order and relative clause attachment preference in L3 BP, the data clearly indicate that Spanish is transferred for both experimental groups irrespective of whether it was the L1 or L2. These results are expected by Rothman's (Second Language Research: forthcoming) model, but not necessarily predicted by other current hypotheses of multilingual syntactic transfer; the implications of this are discussed.

EU membership of the WTO: international trade disputes and judicial protection of individuals by EU Courts

The European Union (EU) is embedded in a pluralistic legal context because of the EU and its Member States’ treaty memberships and domestic laws. Where EU conduct has implications for both the EU’s international trade relations and the legal position of individual traders, it possibly affects EU and its Member States’ obligations under the law of the World Trade Organization (WTO law) as well as the Union’s own multi-layered constitutional legal order. The present paper analyses the way in which the European Court of Justice (ECJ) accommodates WTO and EU law in the context of international trade disputes triggered by the EU. Given the ECJ’s denial of direct effect of WTO law in principle, the paper focuses on the protection of rights and remedies conferred by EU law. It assesses the implications of the WTO Dispute Settlement Understanding (DSU) – which tolerates the acceptance of retaliatory measures constraining traders’ activities in sectors different from those subject to the original trade dispute (Bananas and Hormones cases) – for the protection of ‘retaliation victims’. The paper concludes that governmental discretion conferred by WTO law has not affected the applicability of EU constitutional law but possibly shapes the actual scope of EU rights and remedies where such discretion is exercised in the EU’s general interest.

First order k-th moment finite element analysis of nonlinear operator equations with stochastic data

We develop and analyze a class of efficient Galerkin approximation methods for uncertainty quantification of nonlinear operator equations. The algorithms are based on sparse Galerkin discretizations of tensorized linearizations at nominal parameters. Specifically, we consider abstract, nonlinear, parametric operator equations J(\alpha ,u)=0 for random input \alpha (\omega ) with almost sure realizations in a neighborhood of a nominal input parameter \alpha _0. Under some structural assumptions on the parameter dependence, we prove existence and uniqueness of a random solution, u(\omega ) = S(\alpha (\omega )). We derive a multilinear, tensorized operator equation for the deterministic computation of k-th order statistical moments of the random solution's fluctuations u(\omega ) - S(\alpha _0). We introduce and analyse sparse tensor Galerkin discretization schemes for the efficient, deterministic computation of the k-th statistical moment equation. We prove a shift theorem for the k-point correlation equation in anisotropic smoothness scales and deduce that sparse tensor Galerkin discretizations of this equation converge in accuracy vs. complexity which equals, up to logarithmic terms, that of the Galerkin discretization of a single instance of the mean field problem. We illustrate the abstract theory for nonstationary diffusion problems in random domains.

A finite element method for second order nonvariational elliptic problems

We propose a numerical method to approximate the solution of second order elliptic problems in nonvariational form. The method is of Galerkin type using conforming finite elements and applied directly to the nonvariational (nondivergence) form of a second order linear elliptic problem. The key tools are an appropriate concept of “finite element Hessian” and a Schur complement approach to solving the resulting linear algebra problem. The method is illustrated with computational experiments on three linear and one quasi-linear PDE, all in nonvariational form.

Sparse polynomial approximation in positive order Sobolev spaces with bounded mixed derivatives and applications to elliptic problems with random loading

In the present paper we study the approximation of functions with bounded mixed derivatives by sparse tensor product polynomials in positive order tensor product Sobolev spaces. We introduce a new sparse polynomial approximation operator which exhibits optimal convergence properties in L2 and tensorized View the MathML source simultaneously on a standard k-dimensional cube. In the special case k=2 the suggested approximation operator is also optimal in L2 and tensorized H1 (without essential boundary conditions). This allows to construct an optimal sparse p-version FEM with sparse piecewise continuous polynomial splines, reducing the number of unknowns from O(p2), needed for the full tensor product computation, to View the MathML source, required for the suggested sparse technique, preserving the same optimal convergence rate in terms of p. We apply this result to an elliptic differential equation and an elliptic integral equation with random loading and compute the covariances of the solutions with View the MathML source unknowns. Several numerical examples support the theoretical estimates.