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Random graph models, originally conceived to study the structure of networks and the emergence of their properties, have become an indispensable tool for experimental algorithmics. Amongst them, hyperbolic random graphs form a well-accepted family, yielding realistic complex networks while being both mathematically and algorithmically tractable. We introduce two generators MemGen and HyperGen for the G_{alpha,C}(n) model, which distributes n random points within a hyperbolic plane and produces m=n*d/2 undirected edges for all point pairs close by; the expected average degree d and exponent 2*alpha+1 of the power-law degree distribution are controlled by alpha>1/2 and C. Both algorithms emit a stream of edges which they do not have to store. MemGen keeps O(n) items in internal memory and has a time complexity of O(n*log(log n) + m), which is optimal for networks with an average degree of d=Omega(log(log n)). For realistic values of d=o(n / log^{1/alpha}(n)), HyperGen reduces the memory footprint to O([n^{1-alpha}*d^alpha + log(n)]*log(n)). In an experimental evaluation, we compare HyperGen with four generators among which it is consistently the fastest. For small d=10 we measure a speed-up of 4.0 compared to the fastest publicly available generator increasing to 29.6 for d=1000. On commodity hardware, HyperGen produces 3.7e8 edges per second for graphs with 1e6 < m < 1e12 and alpha=1, utilising less than 600MB of RAM. We demonstrate nearly linear scalability on an Intel Xeon Phi.
In order to promote the accessibility of biodiversity data in historic and contemporary literature, we introduce a new interdisciplinary project called BIOfid (FID=Fachinformationsdienst, a service for providing specialized information). The project aims at a mobilization of data available in print only by combining digitization of scientific biodiversity literature with the development of innovative text mining tools for complex, eventually semantic searches throughout the complete text corpus. A major prerequisite for the development of such search tools is the provision of sophisticated anatomy ontologies on the one hand, and of complete lists of species names (currently considered valid as well as all synonyms) at a global scale on the other hand. In the initial stage, we chose examples from German publications of the past 250 years dealing with the geographic distribution and ecology of vascular plants (Tracheophyta), birds (Aves), as well as moths and butterflies (Lepidoptera) in Germany. These taxa have been prioritized according to current demands of German research groups (about 50 sites) aiming at analyses and modeling of distribution patterns and their changes through time. In the long term, we aim at providing data and open source software applicable for any taxon and geographic region. For this purpose, a platform for open access journals for long-term availability of professional e-journals will be established. All generated data will also be made accessible through GFBio (German Federation for Biological Data). BIOfid is supported by the LIS-Scientific Library Services and Information Systems program of the German Research Foundation (DFG).
We present results on transverse momentum (pT) and rapidity (y) differential production cross sections, mean transverse momentum and mean transverse momentum square of inclusive J/ψ and ψ(2S) at forward rapidity (2.5 < y < 4) as well as ψ(2S)-to-J/ψ cross section ratios. These quantities are measured in pp collisions at center of mass energies s√=5.02 and 13 TeV with the ALICE detector. Both charmonium states are reconstructed in the dimuon decay channel, using the muon spectrometer. A comprehensive comparison to inclusive charmonium cross sections measured at s√=2.76, 7 and 8 TeV is performed. A comparison to non-relativistic quantum chromodynamics and fixed-order next-to-leading logarithm calculations, which describe prompt and non-prompt charmonium production respectively, is also presented. A good description of the data is obtained over the full pT range, provided that both contributions are summed. In particular, it is found that for pT > 15 GeV/c the non-prompt contribution reaches up to 50% of the total charmonium yield.
We explore space improvements in LRP, a polymorphically typed call-by-need functional core language. A relaxed space measure is chosen for the maximal size usage during an evaluation. It Abstracts from the details of the implementation via abstract machines, but it takes garbage collection into account and thus can be seen as a realistic approximation of space usage. The results are: a context lemma for space improving translations and for space equivalences; all but one reduction rule of the calculus are shown to be space improvements, and the exceptional one, the copy-rule, is shown to increase space only moderately.
Several further program transformations are shown to be space improvements or space equivalences, in particular the translation into machine expressions is a space equivalence. These results are a step Forward in making predictions about the change in runtime space behavior of optimizing transformations in callbyneed functional languages.
Motivated by tools for automaed deduction on functional programming languages and programs, we propose a formalism to symbolically represent $\alpha$-renamings for meta-expressions. The formalism is an extension of usual higher-order meta-syntax which allows to $\alpha$-rename all valid ground instances of a meta-expression to fulfill the distinct variable convention. The renaming mechanism may be helpful for several reasoning tasks in deduction systems. We present our approach for a meta-language which uses higher-order abstract syntax and a meta-notation for recursive let-bindings, contexts, and environments. It is used in the LRSX Tool -- a tool to reason on the correctness of program transformations in higher-order program calculi with respect to their operational semantics. Besides introducing a formalism to represent symbolic $\alpha$-renamings, we present and analyze algorithms for simplification of $\alpha$-renamings, matching, rewriting, and checking $\alpha$-equivalence of symbolically $\alpha$-renamed meta-expressions.
We introduce rewriting of meta-expressions which stem from a meta-language that uses higher-order abstract syntax augmented by meta-notation for recursive let, contexts, sets of bindings, and chain variables. Additionally, three kinds of constraints can be added to meta-expressions to express usual constraints on evaluation rules and program transformations. Rewriting of meta-expressions is required for automated reasoning on programs and their properties. A concrete application is a procedure to automatically prove correctness of program transformations in higher-order program calculi which may permit recursive let-bindings as they occur in functional programming languages. Rewriting on meta-expressions can be performed by solving the so-called letrec matching problem which we introduce. We provide a matching algorithm to solve it. We show that the letrec matching problem is NP-complete, that our matching algorithm is sound and complete, and that it runs in non-deterministic polynomial time.
We present an implementation of an interpreter LRPi for the call-by-need calculus LRP, based on a variant of Sestoft's abstract machine Mark 1, extended with an eager garbage collector. It is used as a tool for exact space usage analyses as a support for our investigations into space improvements of call-by-need calculi.
The amyloid precursor protein (APP) was discovered in the 1980s as the precursor protein of the amyloid A4 peptide. The amyloid A4 peptide, also known as A-beta (Aβ), is the main constituent of senile plaques implicated in Alzheimer’s disease (AD). In association with the amyloid deposits, increasing impairments in learning and memory as well as the degeneration of neurons especially in the hippocampus formation are hallmarks of the pathogenesis of AD. Within the last decades much effort has been expended into understanding the pathogenesis of AD. However, little is known about the physiological role of APP within the central nervous system (CNS). Allocating APP to the proteome of the highly dynamic presynaptic active zone (PAZ) identified APP as a novel player within this neuronal communication and signaling network. The analysis of the hippocampal PAZ proteome derived from APP-mutant mice demonstrates that APP is tightly embedded in the underlying protein network. Strikingly, APP deletion accounts for major dysregulation within the PAZ proteome network. Ca2+-homeostasis, neurotransmitter release and mitochondrial function are affected and resemble the outcome during the pathogenesis of AD. The observed changes in protein abundance that occur in the absence of APP as well as in AD suggest that APP is a structural and functional regulator within the hippocampal PAZ proteome. Within this review article, we intend to introduce APP as an important player within the hippocampal PAZ proteome and to outline the impact of APP deletion on individual PAZ proteome subcommunities.