Self-organized critical neural networks

A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters.Comment: 5 pages RevTeX, 7 figures PostScrip

Surface spin-flop transition in a uniaxial antiferromagnetic Fe/Cr superlattice induced by a magnetic field of arbitrary direction

We studied the transition between the antiferromagnetic and the surface spin-flop phases of a uniaxial antiferromagnetic [Fe(14 \AA)/Cr(11 \AA]$_{\rm x20}$ superlattice. For external fields applied parallel to the in-plane easy axis, the layer-by-layer configuration, calculated in the framework of a mean-field one-dimensional model, was benchmarked against published polarized neutron reflectivity data. For an in-plane field $H$ applied at an angle $\psi \ne 0$ with the easy axis, magnetometry shows that the magnetization $M$ vanishes at H=0, then increases slowly with increasing $H$. At a critical value of $H$, a finite jump in $M(H)$ is observed for $\psi<5^{\rm o}$, while a smooth increase of $M$ $vs$ $H$ is found for $\psi>5^{\rm o}$. A dramatic increase in the full width at half maximum of the magnetic susceptibility is observed for $\psi \ge 5^{\rm o}$. The phase diagram obtained from micromagnetic calculations displays a first-order transition to a surface spin-flop phase for low $\psi$ values, while the transition becomes continuous for $\psi$ greater than a critical angle, $\psi_{\rm max} \approx 4.75^{\rm o}$. This is in fair agreement with the experimentally observed results.Comment: 24 pages, 7 figure

Comparison of chemical characteristics of 495 biomass burning plumes intercepted by the NASA DC-8 aircraft during the ARCTAS/CARB-2008 field campaign

This paper compares measurements of gaseous and particulate emissions from a wide range of biomass-burning plumes intercepted by the NASA DC-8 research aircraft during the three phases of the ARCTAS-2008 experiment: ARCTAS-A, based out of Fairbanks, Alaska, USA (3 April to 19 April 2008); ARCTAS-B based out of Cold Lake, Alberta, Canada (29 June to 13 July 2008); and ARCTAS-CARB, based out of Palmdale, California, USA (18 June to 24 June 2008). Approximately 500 smoke plumes from biomass burning emissions that varied in age from minutes to days were segregated by fire source region and urban emission influences. The normalized excess mixing ratios (NEMR) of gaseous (carbon dioxide, acetonitrile, hydrogen cyanide, toluene, benzene, methane, oxides of nitrogen and ozone) and fine aerosol particulate components (nitrate, sulfate, ammonium, chloride, organic aerosols and water soluble organic carbon) of these plumes were compared. A detailed statistical analysis of the different plume categories for different gaseous and aerosol species is presented in this paper. The comparison of NEMR values showed that CH4 concentrations were higher in air-masses that were influenced by urban emissions. Fresh biomass burning plumes mixed with urban emissions showed a higher degree of oxidative processing in comparison with fresh biomass burning only plumes. This was evident in higher concentrations of inorganic aerosol components such as sulfate, nitrate and ammonium, but not reflected in the organic components. Lower NOx NEMRs combined with high sulfate, nitrate and ammonium NEMRs in aerosols of plumes subject to long-range transport, when comparing all plume categories, provided evidence of advanced processing of these plumes

Nucleation of jet engine oil vapours is a large source of aviation-related ultrafine particles

Large airports are a major source of ultrafine particles, which spread across densely populated residential areas, affecting air quality and human health. Jet engine lubrication oils are detectable in aviation-related ultrafine particles, however, their role in particle formation and growth remains unclear. Here we show the volatility and new-particle-formation ability of a common synthetic jet oil, and the quantified oil fraction in ambient ultrafine particles downwind of Frankfurt International Airport, Germany. We find that the oil mass fraction is largest in the smallest particles (10-18 nm) with 21% on average. Combining ambient particle-phase concentration and volatility of the jet oil compounds, we determine a lower-limit saturation ratio larger than 1 × 105 for ultra-low volatility organic compounds. This indicates that the oil is an efficient nucleation agent. Our results demonstrate that jet oil nucleation is an important mechanism that can explain the abundant observations of high number concentrations of non-refractory ultrafine particles near airports

Boolean Dynamics with Random Couplings

This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d, the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.Comment: 69 pages, 16 figures, Submitted to Springer Applied Mathematical Sciences Serie

Evaporation of sulfate aerosols at low relative humidity

Evaporation of sulfuric acid from particles can be important in the atmospheres of Earth and Venus. However, the equilibrium constant for the dissociation of H2SO4 to bisulfate ions, which is the one of the fundamental parameters controlling the evaporation of sulfur particles, is not well constrained. In this study we explore the volatility of sulfate particles at very low relative humidity. We measured the evaporation of sulfur particles versus temperature and relative humidity in the CLOUD chamber at CERN. We modelled the observed sulfur particle shrinkage with the ADCHAM model. Based on our model results, we conclude that the sulfur particle shrinkage is mainly governed by H2SO4 and potentially to some extent by SO3 evaporation. We found that the equilibrium constants for the dissociation of H2SO4 to HSO4-(KH2SO4) and the dehydration of H2SO4 to SO3 ((x) K-SO3) are K H2SO4 = 2-4 x 10(9) mol kg(-1) and (x) K SO3 >= 1.4 x 10(10) at 288.8 +/- 5 K.Peer reviewe

Comparison of the chemical evolution and characteristics of 495 biomass burning plumes intercepted by the NASA DC-8 aircraft during the ARCTAS/CARB-2008 field campaign

This paper compares measurements of gaseous and particulate emissions from a wide range of biomass-burning plumes intercepted by the NASA DC-8 research aircraft during the three phases of the ARCTAS-2008 experiment: ARCTAS-A, based out of Fairbanks, Alaska USA (3 April to 19 April 2008); ARCTAS-B based out of Cold Lake, Alberta, Canada (29 June to 13 July 2008); and ARCTAS-CARB, based out of Palmdale, California, USA (18 June to 24 June 2008). Extensive investigations of boreal fire plume evolution were undertaken during ARCTAS-B, where four distinct fire plumes that were intercepted by the aircraft over a range of down-wind distances (0.1 to 16 hr transport times) were studied in detail. Based on these analyses, there was no evidence for ozone production and a box model simulation of the data confirmed that net ozone production was slow (on average 1 ppbv h−1 in the first 3 h and much lower afterwards) due to limited NOx. Peroxyacetyl nitrate concentrations (PAN) increased with plume age and the box model estimated an average production rate of ~80 pptv h−1 in the first 3 h. Like ozone, there was also no evidence for net secondary inorganic or organic aerosol formation. There was no apparent increase in aerosol mass concentrations in the boreal fire plumes due to secondary organic aerosol (SOA) formation; however, there were indications of chemical processing of the organic aerosols. In addition to the detailed studies of boreal fire plume evolution, about 500 smoke plumes intercepted by the NASA DC-8 aircraft were segregated by fire source region. The normalized excess mixing ratios (i.e. ΔX/ΔCO) of gaseous (carbon dioxide, acetonitrile, hydrogen cyanide, toluene, benzene, methane, oxides of nitrogen (NOx), ozone, PAN) and fine aerosol particulate components (nitrate, sulfate, ammonium, chloride, organic aerosols and water soluble organic carbon) of these plumes were compared

On the composition of ammonia-sulfuric-acid ion clusters during aerosol particle formation

The formation of particles from precursor vapors is an important source of atmospheric aerosol. Research at the Cosmics Leaving OUtdoor Droplets (CLOUD) facility at CERN tries to elucidate which vapors are responsible for this new-particle formation, and how in detail it proceeds. Initial measurement campaigns at the CLOUD stainless-steel aerosol chamber focused on investigating particle formation from ammonia (NH3) and sulfuric acid (H2SO4). Experiments were conducted in the presence of water, ozone and sulfur dioxide. Contaminant trace gases were suppressed at the technological limit. For this study, we mapped out the compositions of small NH3–H2SO4 clusters over a wide range of atmospherically relevant environmental conditions. We covered [NH3] in the range from 10. Positively charged clusters grew on average by Δm/Δn = 1.05 and were only observed at sufficiently high [NH3] / [H2SO4]. The H2SO4 molecules of these clusters are partially neutralized by NH3, in close resemblance to the acid–base bindings of ammonium bisulfate. Supported by model simulations, we substantiate previous evidence for acid–base reactions being the essential mechanism behind the formation of these clusters under atmospheric conditions and up to sizes of at least 2 nm. Our results also suggest that electrically neutral NH3–H2SO4 clusters, unobservable in this study, have generally the same composition as ionic clusters for [NH3] / [H2SO4] > 10. We expect that NH3–H2SO4 clusters form and grow also mostly by Δm/Δn > 1 in the atmosphere's boundary layer, as [NH3] / [H2SO4] is mostly larger than 10. We compared our results from CLOUD with APi-TOF measurements of NH3–H2SO4 anion clusters during new-particle formation in the Finnish boreal forest. However, the exact role of NH3–H2SO4 clusters in boundary layer particle formation remains to be resolved

Experimental investigation of ion-ion recombination under atmospheric conditions

We present the results of laboratory measurements of the ion–ion recombination coefficient at different temperatures, relative humidities and concentrations of ozone and sulfur dioxide. The experiments were carried out using the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at CERN, the walls of which are made of conductive material, making it possible to measure small ions. We produced ions in the chamber using a 3.5 GeV c−1 beam of positively charged pions (π+) generated by the CERN Proton Synchrotron (PS). When the PS was switched off, galactic cosmic rays were the only ionization source in the chamber. The range of the ion production rate varied from 2 to 100 cm−3 s−1, covering the typical range of ionization throughout the troposphere. The temperature ranged from −55 to 20 °C, the relative humidity (RH) from 0 to 70 %, the SO2 concentration from 0 to 40 ppb, and the ozone concentration from 200 to 700 ppb. The best agreement of the retrieved ion–ion recombination coefficient with the commonly used literature value of 1.6 × 10−6 cm3 s−1 was found at a temperature of 5 °C and a RH of 40 % (1.5 ± 0.6) × 10−6 cm3 s−1. At 20 °C and 40 % RH, the retrieved ion–ion recombination coefficient was instead (2.3 ± 0.7) × 10−6 cm3 s−1. We observed no dependency of the ion–ion recombination coefficient on ozone concentration and a weak variation with sulfur dioxide concentration. However, we observed a more than fourfold increase in the ion–ion recombination coefficient with decreasing temperature. We compared our results with three different models and found an overall agreement for temperatures above 0 °C, but a disagreement at lower temperatures. We observed a strong increase in the recombination coefficient for decreasing relative humidities, which has not been reported previously