Effect of edge removal on topological and functional robustness of complex networks

We study the robustness of complex networks subject to edge removal. Several network models and removing strategies are simulated. Rather than the existence of the giant component, we use total connectedness as the criterion of breakdown. The network topologies are introduced a simple traffic dynamics and the total connectedness is interpreted not only in the sense of topology but also in the sense of function. We define the topological robustness and the functional robustness, investigate their combined effect and compare their relative importance to each other. The results of our study provide an alternative view of the overall robustness and highlight efficient ways to improve the robustness of the network models.Comment: 21 pages, 9 figure

A Universal Model of Global Civil Unrest

Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, we analyze records of civil unrest of 170 countries during the period 1919-2008. We demonstrate that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.Comment: 8 pages, 3 figure

Historical trends in iodine and selenium in soil and herbage at the Park Grass experiment, Rothamsted Research, UK

Long term trends in iodine and selenium retention in soil, and uptake by herbage, were investigated in archived samples from the Park Grass Experiment, initiated in 1856 at Rothamsted, UK. Soil (0-23 cm) and herbage samples from plots receiving various mineral fertilisers and organic manures, with and without lime, were analysed for Se and iodine (I) to assess the effect of soil amendment, annual rainfall, crop yield and changes in soil chemistry from 1876 to 2008. Comparing soil from limed and un-limed control (unfertilized) plots, TMAH-extractable Se and I concentrations both diverged, with time, with greater retention in un-limed plots; differences in concentration amounted to 92 and 1660 µg kg-1 for Se and I respectively after 105 yr. These differences were broadly consistent with estimated additions from rainfall and dry deposition. Offtake of both elements in herbage was negligible compared to soil concentrations and annual inputs (<0.003% of total soil I and <0.006% of total soil Se). A positive correlation was observed between I and Se concentrations in herbage, suggesting some common factors controlling bioavailability. A growth-dilution effect for I and Se was suggested by the positive correlation between growing season rainfall (GSR) and herbage yield together with soil-to-plant transfer factors decreasing with yield. Phosphate and sulphate fertilizers reduced I and Se herbage concentrations, both through ion competition and increased herbage yield. Results suggest that in intensive agriculture with soil pH control, the I requirement of grazing animals is not likely to be met by herbage alone

Topological fractal networks introduced by mixed degree distribution

Several fundamental properties of real complex networks, such as the small-world effect, the scale-free degree distribution, and recently discovered topological fractal structure, have presented the possibility of a unique growth mechanism and allow for uncovering universal origins of collective behaviors. However, highly clustered scale-free network, with power-law degree distribution, or small-world network models, with exponential degree distribution, are not self-similarity. We investigate networks growth mechanism of the branching-deactivated geographical attachment preference that learned from certain empirical evidence of social behaviors. It yields high clustering and spectrums of degree distribution ranging from algebraic to exponential, average shortest path length ranging from linear to logarithmic. We observe that the present networks fit well with small-world graphs and scale-free networks in both limit cases (exponential and algebraic degree distribution respectively), obviously lacking self-similar property under a length-scale transformation. Interestingly, we find perfect topological fractal structure emerges by a mixture of both algebraic and exponential degree distributions in a wide range of parameter values. The results present a reliable connection among small-world graphs, scale-free networks and topological fractal networks, and promise a natural way to investigate universal origins of collective behaviors.Comment: 14 pages, 6 figure

An easy-to-machine electrochemical flow microreactor: efficient synthesis of isoindolinone and flow functionalization

Flow electrochemistry is an efficient methodology to generate radical intermediates. An electrochemical flow microreactor has been designed and manufactured to improve the efficiency of electrochemical flow reactions. With this device only little or no supporting electrolytes are needed, making processes less costly and enabling easier purification. This is demonstrated by the facile synthesis of amidyl radicals used in intramolecular hydroaminations to produce isoindolinones. The combination with inline mass spectrometry facilitates a much easier combination of chemical steps in a single flow proces

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

Design, Construction and Cloning of Truncated ORF2 and tPAsp-PADRE-Truncated ORF2 Gene Cassette From Hepatitis E Virus in the pVAX1 Expression Vector

Background: Hepatitis E Virus (HEV) is the causative agent of enterically transmitted acute hepatitis and has high mortality rate of up to 30% among pregnant women. Therefore, development of a novel vaccine is a desirable goal. Objectives: The aim of this study was to construct tPAsp-PADRE-truncated open reading frame 2 (ORF2) and truncated ORF2 DNA plasmid, which can assist future studies with the preparation of an effective vaccine against Hepatitis E Virus. Materials and Methods: A synthetic codon-optimized gene cassette encoding tPAsp-PADRE-truncated ORF2 protein was designed, constructed and analyzed by some bioinformatics software. Furthermore, a codon-optimized truncated ORF2 gene was amplified by the polymerase chain reaction (PCR), with a specific primer from the previous construct. The constructs were sub-cloned in the pVAX1 expression vector and finally expressed in eukaryotic cells. Results: Sequence analysis and bioinformatics studies of the codon-optimized gene cassette revealed that codon adaptation index (CAI), GC content, and frequency of optimal codon usage (Fop) value were improved, and performance of the secretory signal was confirmed. Cloning and sub-cloning of the tPAsp-PADRE-truncated ORF2 gene cassette and truncated ORF2 gene were confirmed by colony PCR, restriction enzymes digestion and DNA sequencing of the recombinant plasmids pVAX-tPAsp-PADRE-truncated ORF2 (aa 112-660) and pVAX-truncated ORF2 (aa 112-660). The expression of truncated ORF2 protein in eukaryotic cells was approved by an Immunofluorescence assay (IFA) and the reverse transcriptase polymerase chain reaction (RT-PCR) method. Conclusions: The results of this study demonstrated that the tPAsp-PADRE-truncated ORF2 gene cassette and the truncated ORF2 gene in recombinant plasmids are successfully expressed in eukaryotic cells. The immunogenicity of the two recombinant plasmids with different formulations will be evaluated as a novel DNA vaccine in future investigations

Heritability of "small-world" networks in the brain: A graph theoretical analysis of resting-state EEG functional connectivity.

Recent studies have shown that resting-state functional networks as studied with fMRI, EEG, and MEG may be so-called small-world networks. We investigated to what extent the characteristic features of small-world networks are genetically determined. To represent functional connectivity between brain areas, we measured resting EEG in 574 twins and their siblings and calculated the synchronization likelihood between each pair of electrodes. We applied a threshold to obtain a binary graph from which we calculated the clustering coefficient C (describing local interconnectedness) and average path length L (describing global interconnectedness) for each individual. Modeling of MZ and DZ twin and sibling resemblance indicated that across various frequency bands 46-89% of the individual differences in C and 37-62% of the individual differences in L are heritable. It is asserted that C, L, and a small-world organization are viable markers of genetic differences in brain organization. © 2007 Wiley-Liss, Inc

Influence of wiring cost on the large-scale architecture of human cortical connectivity

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain

A Study of Brain Networks Associated with Swallowing Using Graph-Theoretical Approaches

Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI) was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, 23.1±1.52 years of age). To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia. © 2013 Luan et al