Large Scales - Long Times: Adding High Energy Resolution to SANS

The Neutron Spin Echo (NSE) variant MIEZE (Modulation of IntEnsity by Zero Effort), where all beam manipulations are performed before the sample position, offers the possibility to perform low background SANS measurements in strong magnetic fields and depolarising samples. However, MIEZE is sensitive to differences \DeltaL in the length of neutron flight paths through the instrument and the sample. In this article, we discuss the major influence of \DeltaL on contrast reduction of MIEZE measurements and its minimisation. Finally we present a design case for enhancing a small-angle neutron scattering (SANS) instrument at the planned European Spallation Source (ESS) in Lund, Sweden, using a combination of MIEZE and other TOF options, such as TISANE offering time windows from ns to minutes. The proposed instrument allows studying fluctuations in depolarizing samples, samples exposed to strong magnetic fields, and spin-incoherently scattering samples in a straightforward way up to time scales of \mus at momentum transfers up to 0.01 {\AA}-1, while keeping the instrumental effort and costs low.Comment: 5 pages, 8 figure

Silly Questions and Arguments for the Implicit, Cinematic Narrator

My chapter aims to advance the debate on a problem often raised by philosophers who are skeptical of implied narrators in movies. This is the concern that positing such elusive narrators gives rise to absurd imaginings (Gaut 2004: 242; Carroll 2006: 179-180). Friends of the implied cinematic narrator reply that the questions critics raise about the workings of the implied cinematic narrator are "silly ones" to ask. I examine how the "absurd imaginings" problem arises for all the central arguments for the elusive cinematic narrator and discuss why the questions critics pose about this narrator are legitimate ones to ask

Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming

Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits

Irregular Migration Theories

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Software for exact integration of polynomials over polyhedra

We are interested in the fast computation of the exact value of integrals of polynomial functions over convex polyhedra. We present speed-ups and extensions of the algorithms presented in previous work by some of the authors. We provide a new software implementation and benchmark computations. The computation of integrals of polynomials over polyhedral regions has many applications; here we demonstrate our algorithmic tools solving a challenge from combinatorial voting theory. © 2012 Elsevier B.V