Logarithmic rate dependence in deforming granular materials

Rate-independence for stresses within a granular material is a basic tenet of many models for slow dense granular flows. By contrast, logarithmic rate dependence of stresses is found in solid-on-solid friction, in geological settings, and elsewhere. In this work, we show that logarithmic rate-dependence occurs in granular materials for plastic (irreversible) deformations that occur during shearing but not for elastic (reversible) deformations, such as those that occur under moderate repetitive compression. Increasing the shearing rate, \Omega, leads to an increase in the stress and the stress fluctuations that at least qualitatively resemble what occurs due to an increase in the density. Increases in \Omega also lead to qualitative changes in the distributions of stress build-up and relaxation events. If shearing is stopped at t=0, stress relaxations occur with \sigma(t)/ \sigma(t=0) \simeq A \log(t/t_0). This collective relaxation of the stress network over logarithmically long times provides a mechanism for rate-dependent strengthening.Comment: 4 pages, 5 figures. RevTeX

Mesoscopic structure conditions the emergence of cooperation on social networks

We study the evolutionary Prisoner's Dilemma on two social networks obtained from actual relational data. We find very different cooperation levels on each of them that can not be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding perfect agreement with the observations in the real networks. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.Comment: Largely improved version, includes an artificial network model that fully confirms the explanation of the results in terms of inter- and intra-community structur

Learning and innovative elements of strategy adoption rules expand cooperative network topologies

Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoners Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems.Comment: 14 pages, 3 Figures + a Supplementary Material with 25 pages, 3 Tables, 12 Figures and 116 reference

Inelastic production of J/ψ mesons in photoproduction and deep inelastic scattering at HERA

A measurement is presented of inelastic photo- and electroproduction of J/ψ mesons in ep scattering at HERA. The data were recorded with the H1 detector in the period from 2004 to 2007. Single and double differential cross sections are determined and the helicity distributions of the J/ψ mesons are analysed. The results are compared to theoretical predictions in the colour singlet model and in the framework of non-relativistic QCD. Calculations in the colour singlet model using a k T factorisation ansatz are able to give a good description of the data, while colour singlet model calculations to next-to-leading order in collinear factorisation underestimate the data

Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death

We analyze the dynamic properties of 10^7 words recorded in English, Spanish and Hebrew over the period 1800--2008 in order to gain insight into the coevolution of language and culture. We report language independent patterns useful as benchmarks for theoretical models of language evolution. A significantly decreasing (increasing) trend in the birth (death) rate of words indicates a recent shift in the selection laws governing word use. For new words, we observe a peak in the growth-rate fluctuations around 40 years after introduction, consistent with the typical entry time into standard dictionaries and the human generational timescale. Pronounced changes in the dynamics of language during periods of war shows that word correlations, occurring across time and between words, are largely influenced by coevolutionary social, technological, and political factors. We quantify cultural memory by analyzing the long-term correlations in the use of individual words using detrended fluctuation analysis.Comment: Version 1: 31 pages, 17 figures, 3 tables. Version 2 is streamlined, eliminates substantial material and incorporates referee comments: 19 pages, 14 figures, 3 table

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs---a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.Comment: 16 pages (4 figures) plus supporting information 8 pages (5 figures

Characteristics of tropospheric ozone depletion events in the Arctic spring: analysis of the ARCTAS, ARCPAC, and ARCIONS measurements and satellite BrO observations

Arctic ozone depletion events (ODEs) are caused by halogen catalyzed ozone loss. In situ chemistry, advection of ozone-poor air mass, and vertical mixing in the lower troposphere are important factors affecting ODEs. To better characterize the ODEs, we analyze the combined set of surface, ozonesonde, and aircraft in situ measurements of ozone and bromine compounds during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS), the Aerosol, Radiation, and Cloud Processes affecting Arctic Climate (ARCPAC), and the Arctic Intensive Ozonesonde Network Study (ARCIONS) experiments (April 2008). Tropospheric BrO columns retrieved from satellite measurements and back trajectory calculations are also used to investigate the characteristics of observed ODEs. In situ observations from these field experiments are inadequate to validate tropospheric BrO columns derived from satellite measurements. In view of this difficulty, we construct an ensemble of tropospheric column BrO estimates from two satellite (OMI and GOME-2) measurements and with three independent methods of calculating stratospheric BrO columns. Furthermore, we select analysis methods that do not depend on the absolute magnitude of column BrO, such as time-lagged correlation analysis of ozone and tropospheric column BrO, to understand characteristics of ODEs. Time-lagged correlation analysis between in situ (surface and ozonesonde) measurements of ozone and satellite derived tropospheric BrO columns indicates that the ODEs are due to either local halogen-driven ozone loss or short-range (∼1 day) transport from nearby regions with ozone depletion. The effect of in situ ozone loss is also evident in the diurnal variation difference between low (10th and 25th percentiles) and higher percentiles of surface ozone concentrations at Alert, Canada. Aircraft observations indicate low-ozone air mass transported from adjacent high-BrO regions. Correlation analyses of ozone with potential temperature and time-lagged tropospheric BrO column show that the vertical extent of local ozone loss is surprisingly deep (1–2 km) at Resolute and Churchill, Canada. The unstable boundary layer during ODEs at Churchill could potentially provide a source of free-tropospheric BrO through convective transport and explain the significant negative correlation between free-tropospheric ozone and tropospheric BrO column at this site

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

Information transmission in oscillatory neural activity

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.Comment: 18 pages, 8 figures, to appear in Biological Cybernetic

Characteristics of tropospheric ozone depletion events in the Arctic spring: analysis of the ARCTAS, ARCPAC, and ARCIONS measurements and satellite BrO observations

Arctic ozone depletion events (ODEs) are caused by halogen catalyzed ozone loss. In situ chemistry, advection of ozone-poor air mass, and vertical mixing in the lower troposphere are important factors affecting ODEs. To better characterize the ODEs, we analyze the combined set of surface, ozonesonde, and aircraft in situ measurements of ozone and bromine compounds during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS), the Aerosol, Radiation, and Cloud Processes affecting Arctic Climate (ARCPAC), and the Arctic Intensive Ozonesonde Network Study (ARCIONS) experiments (April 2008). Tropospheric BrO columns retrieved from satellite measurements and back trajectory calculations are also used to investigate the characteristics of observed ODEs. In situ observations from these field experiments are inadequate to validate tropospheric BrO columns derived from satellite measurements. In view of this difficulty, we construct an ensemble of tropospheric column BrO estimates from two satellite (OMI and GOME-2) measurements and with three independent methods of calculating stratospheric BrO columns. Furthermore, we select analysis methods that do not depend on the absolute magnitude of column BrO, such as time-lagged correlation analysis of ozone and tropospheric column BrO, to understand characteristics of ODEs. Time-lagged correlation analysis between in situ (surface and ozonesonde) measurements of ozone and satellite derived tropospheric BrO columns indicates that the ODEs are due to either local halogen-driven ozone loss or short-range (∼1 day) transport from nearby regions with ozone depletion. The effect of in situ ozone loss is also evident in the diurnal variation difference between low (10th and 25th percentiles) and higher percentiles of surface ozone concentrations at Alert, Canada. Aircraft observations indicate low-ozone air mass transported from adjacent high-BrO regions. Correlation analyses of ozone with potential temperature and time-lagged tropospheric BrO column show that the vertical extent of local ozone loss is surprisingly deep (1–2 km) at Resolute and Churchill, Canada. The unstable boundary layer during ODEs at Churchill could potentially provide a source of free-tropospheric BrO through convective transport and explain the significant negative correlation between free-tropospheric ozone and tropospheric BrO column at this site