Evaluating the role of a galanin enhancer genotype on a range of metabolic, depressive and addictive phenotypes

Funded by •ERC. Grant Number: 284167 •NIH. Grant Number: 1RO1DK0921127-01 •NWO. Grant Numbers: 463-06-001, 451-04-034Peer reviewedPublisher PD

Visualisation of spatial patterns of connectivity and runoff ages derived from a tracer-aided model

We thank the European Research Council ERC (project GA 335910 VEWA) for funding the VeWa project.Peer reviewedPostprin

Regularity of higher codimension area minimizing integral currents

This lecture notes are an expanded version of the course given at the ERC-School on Geometric Measure Theory and Real Analysis, held in Pisa, September 30th - October 30th 2013. The lectures aim to explain the main steps of a new proof of the partial regularity of area minimizing integer rectifiable currents in higher codimension, due originally to F. Almgren, which is contained in a series of papers in collaboration with C. De Lellis (University of Zurich).Comment: This text will appear in "Geometric Measure Theory and Real Analysis", pp. 131--192, Proceedings of the ERC school in Pisa (2013), L. Ambrosio Ed., Edizioni SNS (CRM Series

Status of Rockwell-ERC high efficiency solar cell programs

Programs aimed at developing large area, high efficiency GaAs heteroface cells for low concentration space applications and high concentration terrestrial applications as well as other programs aimed at developing high efficiency multicolor devices for use in similar applications are described. An additional program aimed at achieving improved power to weight ratio by parting thin film solar cells from their growth substrates prior to their incorporation into an array assembly is also described. There is potential for multiple reuse of the substrates which could lead to reduced costs for such devices. Highlights of these programs and their interrelated contributions toward the goals of reducing specific weight, volume and cost of photovoltaic space power systems are discussed. Overall goals are summarized and current programs and their funding sources are listed

Foundation of Computer (Algebra) ANALYSIS Systems: Semantics, Logic, Programming, Verification

We propose a semantics of operating on real numbers that is sound, Turing-complete, and practical. It modifies the intuitive but super-recursive Blum-Shub-Smale model (formalizing Computer ALGEBRA Systems), to coincide in power with the realistic but inconvenient Type-2 Turing machine underlying Computable Analysis: reconciling both as foundation to a Computer ANALYSIS System. Several examples illustrate the elegance of rigorous numerical coding in this framework, formalized as a simple imperative programming language ERC with denotational semantics for REALIZING a real function $f$: arguments $x$ are given as exact real numbers, while values $y=f(x)$ suffice to be returned approximately up to absolute error $2^p$ with respect to an additionally given integer parameter $p\to-\infty$. Real comparison (necessarily) becomes partial, possibly 'returning' the lazy Kleenean value UNKNOWN (subtly different from $\bot$ for classically undefined expressions like 1/0). This asserts closure under composition, and in fact 'Turing-completeness over the reals': All and only functions computable in the sense of Computable Analysis can be realized in ERC. Programs thus operate on a many-sorted structure involving real numbers and integers, the latter connected via the 'error' embedding $Z\ni p\mapsto 2^p\in R$, whose first-order theory is proven decidable and model-complete. This logic serves for formally specifying and formally verifying correctness of ERC programs

The essential value of long-term experimental data for hydrology and water management

We would like to thank the European Research Council ERC for funding the VeWa project and most of Tetzlaff's time (project GA 335910 VeWa). No data were used in producing this manuscript.Peer reviewedPublisher PD

Exact Recovery Conditions for Sparse Representations with Partial Support Information

We address the exact recovery of a k-sparse vector in the noiseless setting when some partial information on the support is available. This partial information takes the form of either a subset of the true support or an approximate subset including wrong atoms as well. We derive a new sufficient and worst-case necessary (in some sense) condition for the success of some procedures based on lp-relaxation, Orthogonal Matching Pursuit (OMP) and Orthogonal Least Squares (OLS). Our result is based on the coherence "mu" of the dictionary and relaxes the well-known condition mu<1/(2k-1) ensuring the recovery of any k-sparse vector in the non-informed setup. It reads mu<1/(2k-g+b-1) when the informed support is composed of g good atoms and b wrong atoms. We emphasize that our condition is complementary to some restricted-isometry based conditions by showing that none of them implies the other. Because this mutual coherence condition is common to all procedures, we carry out a finer analysis based on the Null Space Property (NSP) and the Exact Recovery Condition (ERC). Connections are established regarding the characterization of lp-relaxation procedures and OMP in the informed setup. First, we emphasize that the truncated NSP enjoys an ordering property when p is decreased. Second, the partial ERC for OMP (ERC-OMP) implies in turn the truncated NSP for the informed l1 problem, and the truncated NSP for p<1.Comment: arXiv admin note: substantial text overlap with arXiv:1211.728