Classification and stability of simple homoclinic cycles in R^5

The paper presents a complete study of simple homoclinic cycles in R^5. We find all symmetry groups Gamma such that a Gamma-equivariant dynamical system in R^5 can possess a simple homoclinic cycle. We introduce a classification of simple homoclinic cycles in R^n based on the action of the system symmetry group. For systems in R^5, we list all classes of simple homoclinic cycles. For each class, we derive necessary and sufficient conditions for asymptotic stability and fragmentary asymptotic stability in terms of eigenvalues of linearisation near the steady state involved in the cycle. For any action of the groups Gamma which can give rise to a simple homoclinic cycle, we list classes to which the respective homoclinic cycles belong, thus determining conditions for asymptotic stability of these cycles.Comment: 34 pp., 4 tables, 30 references. Submitted to Nonlinearit

Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity

Brain-inspired computation can revolutionize information technology by introducing machines capable of recognizing patterns (images, speech, video) and interacting with the external world in a cognitive, humanlike way. Achieving this goal requires first to gain a detailed understanding of the brain operation, and second to identify a scalable microelectronic technology capable of reproducing some of the inherent functions of the human brain, such as the high synaptic connectivity (~104) and the peculiar time-dependent synaptic plasticity. Here we demonstrate unsupervised learning and tracking in a spiking neural network with memristive synapses, where synaptic weights are updated via brain-inspired spike timing dependent plasticity (STDP). The synaptic conductance is updated by the local time-dependent superposition of pre-and post-synaptic spikes within a hybrid one-transistor/one-resistor (1T1R) memristive synapse. Only 2 synaptic states, namely the low resistance state (LRS) and the high resistance state (HRS), are sufficient to learn and recognize patterns. Unsupervised learning of a static pattern and tracking of a dynamic pattern of up to 4 Ã\u97 4 pixels are demonstrated, paving the way for intelligent hardware technology with up-scaled memristive neural networks

Motor-based bodily self is selectively impaired in eating disorders

BACKGROUND: Body representation disturbances in body schema (i.e. unconscious sensorimotor body representations for action) have been frequently reported in eating disorders. Recently, it has been proposed that body schema relies on adequate functioning of the motor system, which is strongly implicated in discriminating between one’s own and someone else’s body. The present study aimed to investigate the motor-based bodily self in eating disorders and controls, in order to examine the role of the motor system in body representation disturbances at the body schema level. METHODS: Female outpatients diagnosed with eating disorders (N = 15), and healthy controls (N = 18) underwent a hand laterality task, in which their own (self-stimuli) and someone else’s hands (other-stimuli) were displayed at different orientations. Participants had to mentally rotate their own hand in order to provide a laterality judgement. Group differences in motor-based bodily self-recognition—i.e. whether a general advantage occurred when implicitly processing self- vs. other-stimuli − were evaluated, by analyzing response times and accuracy by means of mixed ANOVAs. RESULTS: Patients with eating disorders did not show a temporal advantage when mentally rotating self-stimuli compared to other-stimuli, as opposed to controls (F(1, 31) = 5.6, p = 0.02; eating disorders-other = 1092 ±256 msec, eating disorders-self = 1097±254 msec; healthy controls-other = 1239±233 msec, healthy controls -self = 1192±232 msec). CONCLUSIONS: This study provides initial indication that high-level motor functions might be compromised as part of body schema disturbances in eating disorders. Further larger investigations are required to test motor system abnormalities in the context of body schema disturbance in eating disorders

Reduced ventricular proliferation in the foetal cortex following maternal inflammation in the mouse

It has been well established that maternal inflammation during pregnancy alters neurological function in the offspring, but its impact on cortical development and long-term consequences on the cytoarchitecture is largely unstudied. Here we report that lipopolysaccharide-induced systemic maternal inflammation in C57Bl/6 mice at embryonic Day 13.5 of pregnancy, as early as 8 h after challenge, caused a significant reduction in cell proliferation in the ventricular zone of the developing cerebral cortex, as revealed by quantification of anti-phospho-Histone H3 immunoreactivity and bromodeoxyuridine pulse labelling. The angle of mitotic cleavage, determined from analysis of haematoxylin and eosin staining, cyclin E1 gene expression and the pattern of β-catenin immunoreactivity were also altered by the challenge, which suggests a change from symmetric to asymmetric division in the radial progenitor cells. Modifications of cortical lamination and gene expression patterns were detected at post-natal Day 8 suggesting prolonged consequences of these alterations during embryonic development. Cellular uptake of proteins from the cerebrospinal fluid was observed in brains from lipopolysaccharide-treated animals in radial progenitor cells. However, the foetal blood–brain barrier to plasma proteins remained intact. Together, these results indicate that maternal inflammation can disrupt the ventricular surface and lead to decreased cellular proliferation. Changes in cell density in Layers IV and V at post-natal Day 8 show that these initial changes have prolonged effects on cortical organization. The possible shift in the fate of progeny and the resulting alterations in the relative cell numbers in the cerebral cortex following a maternal inflammatory response shown here will require further investigation to determine the long-term consequences of inflammation on the development of neuronal circuitry and behaviour

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Search for direct stau production in events with two hadronic tau-leptons in root s=13 TeV pp collisions with the ATLAS detector

A search for the direct production of the supersymmetric partners ofτ-leptons (staus) in final stateswith two hadronically decayingτ-leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of139fb−1, recorded with the ATLAS detector at the LargeHadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected StandardModel background is observed. Limits are derived in scenarios of direct production of stau pairs with eachstau decaying into the stable lightest neutralino and oneτ-lepton in simplified models where the two staumass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidencelevel for a massless lightest neutralino

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5 degrees grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (V-cmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r(2) = 0.76; Nash-Sutcliffe modeling efficiency, MEF = 0.76) and ecosystem respiration (ER, r(2) = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r(2) = 0.42, MEF = 0.14) and and net ecosystem CO2 exchange (NEE, r(2) = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r(2) values (0.57-0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r(2) values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r(2) <0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized V-cmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V-cmax value.Peer reviewe

Developing a predictive modelling capacity for a climate change-vulnerable blanket bog habitat: Assessing 1961-1990 baseline relationships

Aim: Understanding the spatial distribution of high priority habitats and developing predictive models using climate and environmental variables to replicate these distributions are desirable conservation goals. The aim of this study was to model and elucidate the contributions of climate and topography to the distribution of a priority blanket bog habitat in Ireland, and to examine how this might inform the development of a climate change predictive capacity for peat-lands in Ireland. Methods: Ten climatic and two topographic variables were recorded for grid cells with a spatial resolution of 1010 km, covering 87% of the mainland land surface of Ireland. Presence-absence data were matched to these variables and generalised linear models (GLMs) fitted to identify the main climatic and terrain predictor variables for occurrence of the habitat. Candidate predictor variables were screened for collinearity, and the accuracy of the final fitted GLM was evaluated using fourfold cross-validation based on the area under the curve (AUC) derived from a receiver operating characteristic (ROC) plot. The GLM predicted habitat occurrence probability maps were mapped against the actual distributions using GIS techniques. Results: Despite the apparent parsimony of the initial GLM using only climatic variables, further testing indicated collinearity among temperature and precipitation variables for example. Subsequent elimination of the collinear variables and inclusion of elevation data produced an excellent performance based on the AUC scores of the final GLM. Mean annual temperature and total mean annual precipitation in combination with elevation range were the most powerful explanatory variable group among those explored for the presence of blanket bog habitat. Main conclusions: The results confirm that this habitat distribution in general can be modelled well using the non-collinear climatic and terrain variables tested at the grid resolution used. Mapping the GLM-predicted distribution to the observed distribution produced useful results in replicating the projected occurrence of the habitat distribution over an extensive area. The methods developed will usefully inform future climate change predictive modelling for Irelan