On the formation of structure in growing networks

Based on the formation of triad junctions, the proposed mechanism generates networks that exhibit extended rather than single power law behavior. Triad formation guarantees strong neighborhood clustering and community-level characteristics as the network size grows to infinity. The asymptotic behavior is of interest in the study of directed networks in which (i) the formation of links cannot be described according to the principle of preferential attachment; (ii) the in-degree distribution fits a power law for nodes with a high degree and an exponential form otherwise; (iii) clustering properties emerge at multiple scales and depend on both the number of links that newly added nodes establish and the probability of forming triads; and (iv) groups of nodes form modules that feature less links to the rest of the nodes.Comment: 17 pages, 9 figures, we apply the proposed mechanism to generate network realizations that resemble the degree distribution and clustering properties of an empirical network with no directed cycles (i.e., when the model parameter n=0), updated reference

Power-law weighted networks from local attachments

This letter introduces a mechanism for constructing, through a process of distributed decision-making, substrates for the study of collective dynamics on extended power-law weighted networks with both a desired scaling exponent and a fixed clustering coefficient. The analytical results show that the connectivity distribution converges to the scaling behavior often found in social and engineering systems. To illustrate the approach of the proposed framework we generate network substrates that resemble steady state properties of the empirical citation distributions of (i) publications indexed by the Institute for Scientific Information from 1981 to 1997; (ii) patents granted by the U.S. Patent and Trademark Office from 1975 to 1999; and (iii) opinions written by the Supreme Court and the cases they cite from 1754 to 2002.Comment: 18 pages, 3 figures; Proceedings of the IEEE Conference on Decision and Control and the European Control Conference, Orlando, FL, Dec. 2011; Added references; We modified the model in order to take into account extended power-law distributions which better fit to the citations data sets; Added proofs of theorems; Shorten version; Updated plo

VHE Gamma-Ray Induced Pair Cascades in Blazars and Radio Galaxies: Application to NGC 1275

Recent blazar detections by HESS, MAGIC, and VERITAS suggest that very-high-energy (VHE, E > 100 GeV) gamma-rays may be produced in most, if not all, types of blazars, including those that possess intense circumnuclear radiation fields. In this paper, we investigate the interaction of nuclear VHE gamma-rays with the circumnuclear radiation fields through gamma-gamma absorption and pair production, and the subsequent Compton-supported pair cascades. We have developed a Monte-Carlo code to follow the spatial development of the cascade in full 3-dimensional geometry, and calculate the radiative output due to the cascade as a function of viewing angle with respect to the primary VHE gamma-ray beam (presumably the jet axis of the blazar). We show that even for relatively weak magnetic fields, the cascades can be efficiently isotropized, leading to substantial off-axis cascade emission peaking in the Fermi energy range at detectable levels for nearby radio galaxies. We demonstrate that this scenario can explain the Fermi flux and spectrum of the radio galaxy NGC 1275.Comment: Accepted for publication in The Astrophysical Journa

Network synchronization of groups

In this paper we study synchronized motions in complex networks in which there are distinct groups of nodes where the dynamical systems on each node within a group are the same but are different for nodes in different groups. Both continuous time and discrete time systems are considered. We initially focus on the case where two groups are present and the network has bipartite topology (i.e., links exist between nodes in different groups but not between nodes in the same group). We also show that group synchronous motions are compatible with more general network topologies, where there are also connections within the groups

Sensitivity analysis and calibration of a soil carbon model (SoilGen2) in two contrasting loess forest soils

To accurately estimate past terrestrial carbon pools is the key to understanding the global carbon cycle and its relationship with the climate system. SoilGen2 is a useful tool to obtain aspects of soil properties (including carbon content) by simulating soil formation processes; thus it offers an opportunity for both past soil carbon pool reconstruction and future carbon pool prediction. In order to apply it to various environmental conditions, parameters related to carbon cycle process in SoilGen2 are calibrated based on six soil pedons from two typical loess deposition regions (Belgium and China). Sensitivity analysis using the Morris method shows that decomposition rate of humus (<i>k</i><sub>HUM</sub>), fraction of incoming plant material as leaf litter (fr<sub>ecto</sub>) and decomposition rate of resistant plant material (<i>k</i><sub>RPM</sub>) are the three most sensitive parameters that would cause the greatest uncertainty in simulated change of soil organic carbon in both regions. According to the principle of minimizing the difference between simulated and measured organic carbon by comparing quality indices, the suited values of <i>k</i><sub>HUM</sub>, (fr<sub>ecto</sub> and <i>k</i><sub>RPM</sub> in the model are deduced step by step and validated for independent soil pedons. The difference of calibrated parameters between Belgium and China may be attributed to their different vegetation types and climate conditions. This calibrated model allows more accurate simulation of carbon change in the whole pedon and has potential for future modeling of carbon cycle over long timescales

Spatial Patterns and Sequential Sampling Plans for Estimating Densities of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs are an emerging threat to soybean (Fabales: Fabaceae) in the North Central Region of the United States. Consequently, region-specific scouting recommendations for stink bugs are needed. The aim of this study was to characterize the spatial pattern and to develop sampling plans to estimate stink bug population density in soybean fields. In 2016 and 2017, 125 fields distributed across nine states were sampled using sweep nets. Regression analyses were used to determine the effects of stink bug species [Chinavia hilaris (Say) (Hemiptera: Pentatomidae) and Euschistus spp. (Hemiptera: Pentatomidae)], life stages (nymphs and adults), and field locations (edge and interior) on spatial pattern as represented by variance–mean relationships. Results showed that stink bugs were aggregated. Sequential sampling plans were developed for each combination of species, life stage, and location and for all the data combined. Results for required sample size showed that an average of 40–42 sample units (sets of 25 sweeps) would be necessary to achieve a precision of 0.25 for stink bug densities commonly encountered across the region. However, based on the observed geographic gradient of stink bug densities, more practical sample sizes (5–10 sample units) may be sufficient in states in the southeastern part of the region, whereas impractical sample sizes (\u3e100 sample units) may be required in the northwestern part of the region. Our findings provide research-based sampling recommendations for estimating densities of these emerging pests in soybean