Cyclic phonology–syntax-interaction : movement to first position in German

This paper investigates the nature of the attraction of XPs to clauseinitial position in German (and other languages). It argues that there are two different types of preposing. First, an XP can move when it is attracted by an EPP-like feature of Comp. Comp can, however, also attract elements that bear the formal marker of some semantic or pragmatic (information theoretic) function. This second type of movement is driven by the attraction of a formal property of the moved element. It has often been misanalysed as “operator” movement in the past

The restricted access of information structure to syntax : a minority report

This paper sketches the view that syntax does not directly interact with information structure. Therefore, syntactic data are of little help when one wants to narrow down the interpretation of terms such as “focus”, “topic”, etc

Universal superposition codes: capacity regions of compound quantum broadcast channel with confidential messages

We derive universal codes for transmission of broadcast and confidential messages over classical-quantum-quantum and fully quantum channels. These codes are robust to channel uncertainties considered in the compound model. To construct these codes we generalize random codes for transmission of public messages, to derive a universal superposition coding for the compound quantum broadcast channel. As an application, we give a multi-letter characterization of regions corresponding to the capacity of the compound quantum broadcast channel for transmitting broadcast and confidential messages simultaneously. This is done for two types of broadcast messages, one called public and the other common

Water self-sufficiency with separate treatment of household rainwater and greywater

This paper is based on an academic work conducted by a group of students of the Engineering Project course within the Chemical Engineering Degree at the Engineering School of Barcelona. The objective of the exercise was to design a rainwater harvesting and greywater recycling system for a detached house and calculate the number of people that could be self-sufficient. Local rainfall, roof area for collecting rainwater and daily water consumption per inhabitant were considered. The effective amount of rainwater and purified greywater was also obtained. In this design, the rainwater is filtered, stored and preserved in a tank, and disinfected with UV light. A small quantity can be made drinkable. The greywater is filtered, treated in a biological reactor, flocculated, sedimented and finally disinfected with UV light.Postprint (published version

Resource cost results for one-way entanglement distillation and state merging of compound and arbitrarily varying quantum sources

We consider one-way quantum state merging and entanglement distillation under compound and arbitrarily varying source models. Regarding quantum compound sources, where the source is memoryless, but the source state an unknown member of a certain set of density matrices, we continue investigations begun in the work of Bjelakovi\'c et. al. [Universal quantum state merging, J. Math. Phys. 54, 032204 (2013)] and determine the classical as well as entanglement cost of state merging. We further investigate quantum state merging and entanglement distillation protocols for arbitrarily varying quantum sources (AVQS). In the AVQS model, the source state is assumed to vary in an arbitrary manner for each source output due to environmental fluctuations or adversarial manipulation. We determine the one-way entanglement distillation capacity for AVQS, where we invoke the famous robustification and elimination techniques introduced by R. Ahlswede. Regarding quantum state merging for AVQS we show by example, that the robustification and elimination based approach generally leads to suboptimal entanglement as well as classical communication rates.Comment: Improved presentation. Close to the published version. Results unchanged. 25 pages, 0 figure

Domain organization of long autotransporter signal sequences

Bacterial autotransporters represent a diverse family of proteins that autonomously translocate across the inner membrane of Gram-negative bacteria via the Sec complex and across the outer bacterial membrane. They often possess exceptionally long N-terminal signal sequences. We analyzed 90 long signal sequences of bacterial autotransporters and members of the two-partner secretion pathway in silico and describe common domain organization found in 79 of these sequences. The domains are in agreement with previously published experimental data. Our algorithmic approach allows for the systematic identification of functionally different domains in long signal sequences. Keywords: bacterial autotransporter, sequence analysis, pattern, protein targeting, signal peptide, protein traffickin

Molecular similarity for machine learning in drug development : poster presentation

Poster presentation In pharmaceutical research and drug development, machine learning methods play an important role in virtual screening and ADME/Tox prediction. For the application of such methods, a formal measure of similarity between molecules is essential. Such a measure, in turn, depends on the underlying molecular representation. Input samples have traditionally been modeled as vectors. Consequently, molecules are represented to machine learning algorithms in a vectorized form using molecular descriptors. While this approach is straightforward, it has its shortcomings. Amongst others, the interpretation of the learned model can be difficult, e.g. when using fingerprints or hashing. Structured representations of the input constitute an alternative to vector based representations, a trend in machine learning over the last years. For molecules, there is a rich choice of such representations. Popular examples include the molecular graph, molecular shape and the electrostatic field. We have developed a molecular similarity measure defined directly on the (annotated) molecular graph, a long-standing established topological model for molecules. It is based on the concepts of optimal atom assignments and iterative graph similarity. In the latter, two atoms are considered similar if their neighbors are similar. This recursive definition leads to a non-linear system of equations. We show how to iteratively solve these equations and give bounds on the computational complexity of the procedure. Advantages of our similarity measure include interpretability (atoms of two molecules are assigned to each other, each pair with a score expressing local similarity; this can be visualized to show similar regions of two molecules and the degree of their similarity) and the possibility to introduce knowledge about the target where available. We retrospectively tested our similarity measure using support vector machines for virtual screening on several pharmaceutical and toxicological datasets, with encouraging results. Prospective studies are under way