Classifying continuous, real-time e-nose sensor data using a bio-inspired spiking network modelled on the insect olfactory system

In many application domains, conventional e-noses are frequently outperformed in both speed and accuracy by their biological counterparts. Exploring potential bio-inspired improvements, we note a number of neuronal network models have demonstrated some success in classifying static datasets by abstracting the insect olfactory system. However, these designs remain largely unproven in practical settings, where sensor data is real-time, continuous, potentially noisy, lacks a precise onset signal and accurate classification requires the inclusion of temporal aspects into the feature set. This investigation therefore seeks to inform and develop the potential and suitability of biomimetic classifiers for use with typical real-world sensor data. Taking a generic classifier design inspired by the inhibition and competition in the insect antennal lobe, we apply it to identifying 20 individual chemical odours from the timeseries of responses of metal oxide sensors. We show that four out of twelve available sensors and the first 30 s(10%) of the sensors’ continuous response are sufficient to deliver 92% accurate classification without access to an odour onset signal. In contrast to previous approaches, once training is complete, sensor signals can be fed continuously into the classifier without requiring discretization. We conclude that for continuous data there may be a conceptual advantage in using spiking networks, in particular where time is an essential component of computation. Classification was achieved in real time using a GPU-accelerated spiking neural network simulator developed in our group

Gα16, a G Protein α Subunit Specifically Expressed in Hematopoietic Cells

Signal-transduction pathways mediated by guanine nucleotide-binding regulatory proteins (G proteins) determine many of the responses of hematopoietic cells. A recently identified gene encoding a G protein α subunit, Gα16, is specifically expressed in human cells of the hematopoietic lineage. The Gα16 cDNA encodes a protein with predicted Mr of 43,500, which resembles the Gq class of α subunits and does not include a pertussis toxin ADP-ribosylation site. In comparison with other G protein α subunits, the Gα16 predicted protein has distinctive amino acid sequences in the amino terminus, the region A guanine nucleotide-binding domain, and in the carboxyl-terminal third of the protein. Cell lines of myelomonocytic and T-cell phenotype express the Gα16 gene, but no expression is detectable in two B-cell lines or in nonhematopoietic cell lines. Gα16 gene expression is down-regulated in HL-60 cells induced to differentiate to neutrophils with dimethyl sulfoxide. Antisera generated from synthetic peptides that correspond to two regions of Gα16 specifically react with a protein of 42- to 43-kDa in bacterial strains that overexpress Gα16 and in HL-60 membranes. This protein is decreased in membranes from dimethyl sulfoxide-differentiated HL-60 cells and is not detectable in COS cell membranes. The restricted expression of this gene suggests that Gα16 regulates cell-type-specific signal-transduction pathways, which are not inhibited by pertussis toxin

Precise Control of Molecular Self-Diffusion in Isoreticular and Multivariate Metal-Organic Frameworks.

Understanding the factors that affect self-diffusion in isoreticular and multivariate (MTV) MOFs is key to their application in drug delivery, separations, and heterogeneous catalysis. Here, we measure the apparent self-diffusion of solvents saturated within the pores of large single crystals of MOF-5, IRMOF-3 (amino-functionalized MOF-5), and 17 MTV-MOF-5/IRMOF-3 materials at various mole fractions. We find that the apparent self-diffusion coefficient of N,N-dimethylformamide (DMF) may be tuned linearly between the diffusion coefficients of MOF-5 and IRMOF-3 as a function of the linker mole fraction. We compare a series of solvents at saturation in MOF-5 and IRMOF-3 to elucidate the mechanism by which the linker amino groups tune molecular diffusion. The ratio of the self-diffusion coefficients for solvents in MOF-5 to those in IRMOF-3 is similar across all solvents tested, regardless of solvent polarity. We conclude that average pore aperture, not solvent-linker chemical interactions, is the primary factor responsible for the different diffusion dynamics upon introduction of an amino group to the linker

Coherent control of plasma dynamics

Coherent control of a system involves steering an interaction to a final coherent state by controlling the phase of an applied field. Plasmas support coherent wave structures that can be generated by intense laser fields. Here, we demonstrate the coherent control of plasma dynamics in a laser wakefield electron acceleration experiment. A genetic algorithm is implemented using a deformable mirror with the electron beam signal as feedback, which allows a heuristic search for the optimal wavefront under laser-plasma conditions that is not known a priori. We are able to improve both the electron beam charge and angular distribution by an order of magnitude. These improvements do not simply correlate with having the `best' focal spot, since the highest quality vacuum focal spot produces a greatly inferior electron beam, but instead correspond to the particular laser phase that steers the plasma wave to a final state with optimal accelerating fields

From Markovian to pairwise epidemic models and the performance of moment closure approximations

Many if not all models of disease transmission on networks can be linked to the exact state-based Markovian formulation. However the large number of equations for any system of realistic size limits their applicability to small populations. As a result, most modelling work relies on simulation and pairwise models. In this paper, for a simple SIS dynamics on an arbitrary network, we formalise the link between a well known pairwise model and the exact Markovian formulation. This involves the rigorous derivation of the exact ODE model at the level of pairs in terms of the expected number of pairs and triples. The exact system is then closed using two different closures, one well established and one that has been recently proposed. A new interpretation of both closures is presented, which explains several of their previously observed properties. The closed dynamical systems are solved numerically and the results are compared to output from individual-based stochastic simulations. This is done for a range of networks with the same average degree and clustering coefficient but generated using different algorithms. It is shown that the ability of the pairwise system to accurately model an epidemic is fundamentally dependent on the underlying large-scale network structure. We show that the existing pairwise models are a good fit for certain types of network but have to be used with caution as higher-order network structures may compromise their effectiveness

Infrared Evolution and Phase Structure of a Gauge Theory Containing Different Fermion Representations

We study the evolution of an asymptotically free vectorial SU($N$) gauge theory from the ultraviolet to the infrared and the resultant phase structure in the general case in which the theory contains fermions transforming according to several different representations of the gauge group. We discuss the sequential fermion condensation and dynamical mass generation that occur, and comment on the effect of bare fermion mass terms.Comment: 13 pages, late

Localized Control of Curie Temperature in Perovskite Oxide Film by Capping-layer- induced Octahedral Distortion

With reduced dimensionality, it is often easier to modify the properties of ultra-thin films than their bulk counterparts. Strain engineering, usually achieved by choosing appropriate substrates, has been proven effective in controlling the properties of perovskite oxide films. An emerging alternative route for developing new multifunctional perovskite is by modification of the oxygen octahedral structure. Here we report the control of structural oxygen octahedral rotation in ultra-thin perovskite SrRuO3 films by the deposition of a SrTiO3 capping layer, which can be lithographically patterned to achieve local control. Using a scanning Sagnac magnetic microscope, we show increase in the Curie temperature of SrRuO3 due to the suppression octahedral rotations revealed by the synchrotron x-ray diffraction. This capping-layer-based technique may open new possibilities for developing functional oxide materials.Comment: Main-text 5 pages, SI 6 pages. To appear in Physical Review Letter