Matching methods to produce maps for pest risk analysis to resources

Decision support systems (DSSs) for pest risk mapping are invaluable for guiding pest risk analysts seeking to add maps to pest risk analyses (PRAs). Maps can help identify the area of potential establishment, the area at highest risk and the endangered area for alien plant pests. However, the production of detailed pest risk maps may require considerable time and resources and it is important to match the methods employed to the priority, time and detail required. In this paper, we apply PRATIQUE DSSs to Phytophthora austrocedrae, a pathogen of the Cupressaceae, Thaumetopoea pityocampa, the pine processionary moth, Drosophila suzukii, spotted wing Drosophila, and Thaumatotibia leucotreta, the false codling moth. We demonstrate that complex pest risk maps are not always a high priority and suggest that simple methods may be used to determine the geographic variation in relative risks posed by invasive alien species within an area of concern

Input-driven unsupervised learning in recurrent neural networks

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is an attractor neural network with Hebbian learning (e.g. the Hopfield model). The model simplicity and the locality of the synaptic update rules come at the cost of a limited storage capacity, compared with the capacity achieved with supervised learning algorithms, whose biological plausibility is questionable. Here, we present an on-line learning rule for a recurrent neural network that achieves near-optimal performance without an explicit supervisory error signal and using only locally accessible information, and which is therefore biologically plausible. The fully connected network consists of excitatory units with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the patterns to be memorized are presented on-line as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs ('local fields'). Synapses corresponding to active inputs are modified as a function of the position of the local field with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. An additional parameter of the model allows to trade storage capacity for robustness, i.e. increased size of the basins of attraction. We simulated a network of 1001 excitatory neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction: our results show that, for any given basin size, our network more than doubles the storage capacity, compared with a standard Hopfield network. Our learning rule is consistent with available experimental data documenting how plasticity depends on firing rate. It predicts that at high enough firing rates, no potentiation should occu

Irregular Persistent Activity Induced by Synaptic Excitatory Feedback

Neurophysiological experiments on monkeys have reported highly irregular persistent activity during the performance of an oculomotor delayed-response task. These experiments show that during the delay period the coefficient of variation (CV) of interspike intervals (ISI) of prefrontal neurons is above 1, on average, and larger than during the fixation period. In the present paper, we show that this feature can be reproduced in a network in which persistent activity is induced by excitatory feedback, provided that (i) the post-spike reset is close enough to threshold , (ii) synaptic efficacies are a non-linear function of the pre-synaptic firing rate. Non-linearity between pre-synaptic rate and effective synaptic strength is implemented by a standard short-term depression mechanism (STD). First, we consider the simplest possible network with excitatory feedback: a fully connected homogeneous network of excitatory leaky integrate-and-fire neurons, using both numerical simulations and analytical techniques. The results are then confirmed in a network with selective excitatory neurons and inhibition. In both the cases there is a large range of values of the synaptic efficacies for which the statistics of firing of single cells is similar to experimental data

Supervised Associative Learning in Spiking Neural Network

In this paper, we propose a simple supervised associative learning approach for spiking neural networks. In an excitatory-inhibitory network paradigm with Izhikevich spiking neurons, synaptic plasticity is implemented on excitatory to excitatory synapses dependent on both spike emission rates and spike timings. As results of learning, the network is able to associate not just familiar stimuli but also novel stimuli observed through synchronised activity within the same subpopulation and between two associated subpopulations

Syntectonic crustal melting and high-grade metamorphism in a transpressional regime, Variscan Massif Central, France

Hot collisional orogens are characterized by abundant syn-kinematic granitic magmatism that profoundly affects their tectono-thermal evolutions. Voluminous granitic magmas, emplaced between 360 and 270 Ma, played a visibly important role in the evolution of the Variscan Orogen. In the Limousin region (western Massif Central, France), syntectonic granite plutons are spatially associated with major strike-slip shear zones that merge to the northwest with the South Armorican Shear Zone. This region allowed us to assess the role of magmatism in a hot transpressional orogen. Microstructural data and U/Pb zircon and monazite ages from a mylonitic leucogranite indicate synkinematic emplacement in a dextral transpressional shear zone at 313 ± 4 Ma. Leucogranites are coeval with cordierite-bearing migmatitic gneisses and vertical lenses of leucosome in strike-slip shear zones. We interpret U/Pb monazite ages of 315 ± 4 Ma for the gneisses and 316 ± 2 Ma for the leucosomes as the minimum age of high-grade metamorphism and migmatization respectively. These data suggest a spatial and temporal relationship between transpression, crustal melting, rapid exhumation and magma ascent, and cooling of high-grade metamorphic rocks. Some granites emplaced in the strike-slip shear zone are bounded at their roof by low dip normal faults that strike N-S, perpendicular to the E-W trend of the belt. The abundant crustal magmatism provided a low-viscosity zone that enhanced Variscan orogenic collapse during continued transpression, inducing the development of normal faults in the transpression zone and thrust faults at the front of the collapsed orogen. © 2009 Elsevier B.V. All rights reserved

High-frequency electron paramagnetic resonance investigation of the Fe3+ impurity center in polycrystalline PbTiO3 in its ferroelectric phase

The intrinsic iron(III) impurity center in polycrystalline lead titanate was investigated by means of high-frequency electron paramagnetic resonance (EPR) spectroscopy in order to determine the local-environment sensitive fine structure parameter D. At a spectrometer frequency of 190 GHz, spectral analysis of a powder sample was unambiguously possible. The observed mean value D = +35.28 GHz can be rationalized if Fe3+ ions substitute for Ti4+ at the B-site of the perovskite ABO3 lattice forming a directly coordinated iron - oxygen vacancy defect associate. A consistent fit of the multi-frequency data necessitated use of a distribution of D values with a variance of about 1 GHz. This statistical distribution of values is probably related to more distant defects and vacancies.Comment: 6 pages, 3 figures, 1 table, to appear in J. App. Phys, 96 (2004

Astrocytes: Orchestrating synaptic plasticity?

Synaptic plasticity is the capacity of a preexisting connection between two neurons to change in strength as a function of neural activity. Because synaptic plasticity is the major candidate mechanism for learning and memory, the elucidation of its constituting mechanisms is of crucial importance in many aspects of normal and pathological brain function. In particular, a prominent aspect that remains debated is how the plasticity mechanisms, that encompass a broad spectrum of temporal and spatial scales, come to play together in a concerted fashion. Here we review and discuss evidence that pinpoints to a possible non-neuronal, glial candidate for such orchestration: the regulation of synaptic plasticity by astrocytes

ESR Study of (C_5H_{12}N)_2CuBr_4

ESR studies at 9.27, 95.4, and 289.7 GHz have been performed on (C$_5$H$_{12}$N)$_2$CuBr$_4$ down to 3.7 K. The 9.27 GHz data were acquired with a single crystal and do not indicate the presence of any structural transitions. The high frequency data were collected with a polycrystalline sample and resolved two absorbances, consistent with two crystallographic orientations of the magnetic sites and with earlier ESR studies performed at 300 K. Below $B_{C1}=6.6$ T, our data confirm the presence of a spin singlet ground state.Comment: 2 pages, 4 figs., submitted 23rd International Conference on Low Temperature Physics (LT-23), Aug. 200

Hot electron cooling by acoustic phonons in graphene

We have investigated the energy loss of hot electrons in metallic graphene by means of GHz noise thermometry at liquid helium temperature. We observe the electronic temperature T / V at low bias in agreement with the heat diffusion to the leads described by the Wiedemann-Franz law. We report on $T\propto\sqrt{V}$ behavior at high bias, which corresponds to a T4 dependence of the cooling power. This is the signature of a 2D acoustic phonon cooling mechanism. From a heat equation analysis of the two regimes we extract accurate values of the electron-acoustic phonon coupling constant $\Sigma$ in monolayer graphene. Our measurements point to an important effect of lattice disorder in the reduction of $\Sigma$, not yet considered by theory. Moreover, our study provides a strong and firm support to the rising field of graphene bolometric detectors.Comment: 5 figure