(Quantum) Space-Time as a Statistical Geometry of Lumps in Random Networks

In the following we undertake to describe how macroscopic space-time (or rather, a microscopic protoform of it) is supposed to emerge as a superstructure of a web of lumps in a stochastic discrete network structure. As in preceding work (mentioned below), our analysis is based on the working philosophy that both physics and the corresponding mathematics have to be genuinely discrete on the primordial (Planck scale) level. This strategy is concretely implemented in the form of \tit{cellular networks} and \tit{random graphs}. One of our main themes is the development of the concept of \tit{physical (proto)points} or \tit{lumps} as densely entangled subcomplexes of the network and their respective web, establishing something like \tit{(proto)causality}. It may perhaps be said that certain parts of our programme are realisations of some early ideas of Menger and more recent ones sketched by Smolin a couple of years ago. We briefly indicate how this \tit{two-story-concept} of \tit{quantum} space-time can be used to encode the (at least in our view) existing non-local aspects of quantum theory without violating macroscopic space-time causality.Comment: 35 pages, Latex, under consideration by CQ

Brian2GeNN: accelerating spiking neural network simulations with graphics hardware

“Brian” is a popular Python-based simulator for spiking neural networks, commonly used in computational neuroscience. GeNN is a C++-based meta-compiler for accelerating spiking neural network simulations using consumer or high performance grade graphics processing units (GPUs). Here we introduce a new software package, Brian2GeNN, that connects the two systems so that users can make use of GeNN GPU acceleration when developing their models in Brian, without requiring any technical knowledge about GPUs, C++ or GeNN. The new Brian2GeNN software uses a pipeline of code generation to translate Brian scripts into C++ code that can be used as input to GeNN, and subsequently can be run on suitable NVIDIA GPU accelerators. From the user’s perspective, the entire pipeline is invoked by adding two simple lines to their Brian scripts. We have shown that using Brian2GeNN, two non-trivial models from the literature can run tens to hundreds of times faster than on CPU

(Quantum) Space-Time as a Statistical Geometry of Fuzzy Lumps and the Connection with Random Metric Spaces

We develop a kind of pregeometry consisting of a web of overlapping fuzzy lumps which interact with each other. The individual lumps are understood as certain closely entangled subgraphs (cliques) in a dynamically evolving network which, in a certain approximation, can be visualized as a time-dependent random graph. This strand of ideas is merged with another one, deriving from ideas, developed some time ago by Menger et al, that is, the concept of probabilistic- or random metric spaces, representing a natural extension of the metrical continuum into a more microscopic regime. It is our general goal to find a better adapted geometric environment for the description of microphysics. In this sense one may it also view as a dynamical randomisation of the causal-set framework developed by e.g. Sorkin et al. In doing this we incorporate, as a perhaps new aspect, various concepts from fuzzy set theory.Comment: 25 pages, Latex, no figures, some references added, some minor changes added relating to previous wor

Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters

Mass Loss Evolution and the Formation of Detached Shells around TP-AGB Stars

The origin of the so called 'detached shells' around AGB stars is not fully understood, but two common hypotheses state that these shells form either through the interaction of distinct wind phases or an eruptive mass loss associated with a He-shell flash. We present a model of the formation of detached shells around thermal pulse asymptotic giant branch (TP-AGB) stars, based on detailed modelling of mass loss and stellar evolution, leading to a combination of eruptive mass loss and wind interaction. The purpose of this paper is first of all to connect stellar evolution with wind and mass loss evolution and demonstrate its consistency with observations, but also to show how thin detached shells around TP-AGB stars can be formed. Previous attempts to link mass loss evolution with the formation of detached shells were based on approximate prescriptions for the mass loss and have not included detailed modelling of the wind formation as we do here. (abridged)Comment: 16 pages, 15 figures. Accepted for publication in Astronomy & Astrophysic

The assessment of the near infrared identification of Carbon stars. I. The Local Group galaxies WLM, IC 10 and NGC 6822

{The selection of AGB C and M stars from NIR colours has been done in recent years using adjustable criteria that are in needs of standardization if one wants to compare, in a coherent manner, properties of various populations.} We intend to assess the NIR colour technique to identify C and M stars. We compare the NIR colours of several C stars previously identified from spectroscopy or narrow band techniques in WLM, IC 10 and NGC 6822. We demonstrate that very few M stars have $(J-K)_0 > 1.4$ but a non negligible number of C stars are bluer than this limit. Thus, counts of M and C stars based on such limit do not produce pure samples. C/M ratios determined from NIR colours must be regarded as underestimates mainly because the M numbers include many warm C stars and also K stars if no blue limit is considered.Comment: A&A accepted 18.07.200

Convolution of multifractals and the local magnetization in a random field Ising chain

The local magnetization in the one-dimensional random-field Ising model is essentially the sum of two effective fields with multifractal probability measure. The probability measure of the local magnetization is thus the convolution of two multifractals. In this paper we prove relations between the multifractal properties of two measures and the multifractal properties of their convolution. The pointwise dimension at the boundary of the support of the convolution is the sum of the pointwise dimensions at the boundary of the support of the convoluted measures and the generalized box dimensions of the convolution are bounded from above by the sum of the generalized box dimensions of the convoluted measures. The generalized box dimensions of the convolution of Cantor sets with weights can be calculated analytically for certain parameter ranges and illustrate effects we also encounter in the case of the measure of the local magnetization. Returning to the study of this measure we apply the general inequalities and present numerical approximations of the D_q-spectrum. For the first time we are able to obtain results on multifractal properties of a physical quantity in the one-dimensional random-field Ising model which in principle could be measured experimentally. The numerically generated probability densities for the local magnetization show impressively the gradual transition from a monomodal to a bimodal distribution for growing random field strength h.Comment: An error in figure 1 was corrected, small additions were made to the introduction and the conclusions, some typos were corrected, 24 pages, LaTeX2e, 9 figure

Geosmin suppresses defensive behaviour and elicits unusual neural responses in honey bees.

Geosmin is an odorant produced by bacteria in moist soil. It has been found to be extraordinarily relevant to some insects, but the reasons for this are not yet fully understood. Here we report the first tests of the effect of geosmin on honey bees. A stinging assay showed that the defensive behaviour elicited by the bee's alarm pheromone component isoamyl acetate (IAA) is strongly suppressed by geosmin. Surprisingly, the suppression is, however, only present at very low geosmin concentrations, and disappears at higher concentrations. We investigated the underlying mechanisms at the level of the olfactory receptor neurons by means of electroantennography, finding the responses to mixtures of geosmin and IAA to be lower than to pure IAA, suggesting an interaction of both compounds at the olfactory receptor level. Calcium imaging of the antennal lobe (AL) revealed that neuronal responses to geosmin decreased with increasing concentration, correlating well with the observed behaviour. Computational modelling of odour transduction and coding in the AL suggests that a broader activation of olfactory receptor types by geosmin in combination with lateral inhibition could lead to the observed non-monotonic increasing-decreasing responses to geosmin and thus underlie the specificity of the behavioural response to low geosmin concentrations

Examining the ribonuclease H primer grip of HIV-1 reverse transcriptase by charge neutralization of RNA/DNA hybrids

The crystal structure of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) bound to an RNA/DNA hybrid reveals an extensive network of contacts with the phosphate backbone of the DNA strand ∼4–9 bp downstream from the ribonuclease H (RNase H) catalytic center. Collectively designated as ‘the RNase H primer grip’, this motif contains a phosphate binding pocket analogous to the human and Bacillus halodurans RNases H. The notion that the RNase H primer grip mediates the trajectory of RNA/DNA hybrids accessing the RNase H active site suggests that locally neutralizing the phosphate backbone may be exploited to manipulate nucleic acid flexibility. To examine this, we introduced single and tandem methylphosphonate substitutions through the region of the DNA primer contacted by the RNase H primer grip and into the RNase H catalytic center. The ability of mutant hybrids to support RNase H and DNA polymerase activity was thereafter examined. In addition, site-specific chemical footprinting was used to evaluate movement of the DNA polymerase and RNase H domains. We show here that minor alteration to the RNase H primer can have a dramatic effect on enzyme positioning, and discuss these findings in light of recent crystallography of human RNase H containing an RNA/DNA hybrid

Carbon stars in the X-shooter Spectral Library

We provide a new collection of spectra of 35 carbon stars obtained with the ESO/VLT X-shooter instrument as part of the X-shooter Spectral Library project. The spectra extend from 0.3$\mu$m to 2.4$\mu$m with a resolving power above $\sim$ 8000. The sample contains stars with a broad range of (J-K) color and pulsation properties located in the Milky Way and the Magellanic Clouds. We show that the distribution of spectral properties of carbon stars at a given (J-K) color becomes bimodal (in our sample) when (J-K) is larger than about 1.5. We describe the two families of spectra that emerge, characterized by the presence or absence of the absorption feature at 1.53$\mu$m, generally associated with HCN and C$_2$H$_2$. This feature appears essentially only in large-amplitude variables, though not in all observations. Associated spectral signatures that we interpret as the result of veiling by circumstellar matter, indicate that the 1.53$\mu$m feature might point to episodes of dust production in carbon-rich Miras.Comment: 29 pages, 21 figures, 9 tables, Accepted for publication in A&