Search

The growth dynamics of complex organizations have attracted much interest of econophysicists and sociophysicists in recent years. However, most of the studies are done for developed countries. We investigate the growth dynamics of the primary industry and the population of 2079 counties in mainland China using the data from the China County Statistical Yearbooks from 2000 to 2006. We find that the annual growth rates are distributed according to Student's $t$ distribution with the tail exponent less than 2. We find power-law relationships between the sample standard deviation of the growth rates and the initial size. The scaling exponent is less than 0.5 for the primary industry and close to 0.5 for the population., 8 pages

MDA-MB-231 breast cancer cells have a high invasive potential, yet the mechanisms involved are not known. This study showed that Toll-like receptor 2 (TLR2) was highly expressed in MDA-MB-231 cells and played a critical role in cell invasion. Compared with the poorly invasive MCF-7 cells, MDA-MB-231 cells expressed 10.5-fold more TLR2. Using TLR2 agonist pg-LPS and TLR2 neutralizing antibody, we found that TLR2 activation significantly promoted MDA-MB-231 invasion, whereas TLR2 blockade diminished this capacity. TLR2 activation enhanced the activity of NF-kappaB and induced phosphorylation of TAK1 and IkappaBalpha in the TLR2/NF-kappaB signaling pathway in MDA-MB-231, but not in MCF-7 cells. TLR2 activation increased IL-6, TGF-beta, VEGF and MMP9 secretion, which are associated with TLR2-NF-kappaB signaling. We demonstrated that TLR2 is a critical receptor responsible for NF-kappaB signaling activity and highly invasive capacity of MDA-MB-231 cells.

Much empirical evidence shows that individuals usually exhibit significant homophily in social networks. We demonstrate, however, skill complementarity enhances heterophily in the formation of collaboration networks, where people prefer to forge social ties with people who have professions different from their own. We construct a model to quantify the heterophily by assuming that individuals choose collaborators to maximize utility. Using a huge database of online societies, we find evidence of heterophily in collaboration networks. The results of model calibration confirm the presence of heterophily. Both empirical analysis and model calibration show that the heterophilous feature is persistent along the evolution of online societies. Furthermore, the degree of skill complementarity is positively correlated with their production output. Our work sheds new light on the scientific research utility of virtual worlds for studying human behaviors in complex socioeconomic systems.

People in modern societies form different social networks through numerous means of communication. These communication networks reflect different aspects of human's societal structure. The billing records of calls among mobile phone users enable us to construct a directed calling network (DCN) and its Bonferroni network (SVDCN) in which the preferential communications are statistically validated. Here we perform a comparative investigation of the cliques of the original DCN and its SVDCN constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that the statistical properties of the cliques of the two calling networks are qualitatively similar and the clique members in the DCN and the SVDCN exhibit idiosyncratic behaviors quantitatively. Members in large cliques are found to be spatially close to each other. Based on the clique degree profile of each mobile phone user, the most active users in the two calling networks can be classified in to several groups. The users in different groups are found to have different calling behaviors. Our study unveils interesting communication behaviors among mobile phone users that are densely connected to each other., 18 pages, 10 figures

The dependence of the momentum-dependent symmetry potential on the nuclear collective flows produced in semicentral ${}^{197}\mathrm{Au}+{}^{197}\mathrm{Au}$ collisions at incident energies from 250 to 800A MeV has been investigated within the isospin-dependent quantum molecular dynamics model. It is found that the theoretical results overestimate the values of the experimental data on directed flow of protons in the domain of large rapidities but can reproduce well the one of mass-three cluster. Neutron-proton differential flows and difference of neutron-proton collective flows are sensitive to the momentum-dependent symmetry potential, especially in the domain of larger rapidities and momenta. This sensitivity becomes stronger with increasing cut of the transverse velocity and becomes smaller with increasing incident energies.

Dynamics of pseudoscalar mesons ($\pi$, $\eta$, $K$ and $\overline{K}$ ) and hyperons ($\Lambda$ and $\Sigma$) produced in heavy-ion collisions near threshold energies has been investigated within the Lanzhou quantum molecular dynamics (LQMD) transport model. The in-medium modifications on particle production in dense nuclear matter are implemented in the model through corrections on the elementary cross sections and by inclusion of the meson (hyperon)-nucleon potentials, in which the isospin effects are considered. It is found that the transportation of particles are influenced with the in-medium corrections. The total number of pions is reduced with an isospin, density and momentum dependent pion-nucleon potential. However, the ratios of charged pions is enhanced with inclusion of the potential. The production of eta in the domain of mid-rapidities and high momenta is sensitive to the $\eta$-nucleon potential, but weakly depends on symmetry energy. The attractive antikaon-nucleon potential enhances the subthreshold $\overline{K}$ production and also influences the structure of phase-space distributions. Dynamics of etas, kaons, antikaons and hyperons is also influenced by the pion potential because of collisions between pions and nucleons (resonances). The impacts of mean-field potentials on particle dynamics are investigated, such as the phase-space distributions from rapidity and transverse momentum spectra, inclusive invariant spectra, collective flows etc., Comment: 18 pages, 13 figures. arXiv admin note: text overlap with arXiv:1310.8072

Complex network is not only a powerful tool for the analysis of complex system, but also a promising way to analyze time series. The algorithm of horizontal visibility graph (HVG) maps time series into graphs, whose degree distributions are numerically and analytically investigated for certain time series. We derive the degree distributions of HVGs through an iterative construction process of HVGs. The degree distributions of the HVG and the directed HVG for random series are derived to be exponential, which confirms the analytical results from other methods. We also obtained the analytical expressions of degree distributions of HVGs and in-degree and out-degree distributions of directed HVGs transformed from multifractal binomial measures, which agree excellently with numerical simulations., Comment: 7 pages, 4 figures

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.

This article investigates the correlation structure of the global crude oil market using the daily returns of 71 oil price time series across the world from 1992 to 2012. We identify from the correlation matrix six clusters of time series exhibiting evident geographical traits, which supports Weiner's (1991) regionalization hypothesis of the global oil market. We find that intra-cluster pairs of time series are highly correlated while inter-cluster pairs have relatively low correlations. Principal component analysis shows that most eigenvalues of the correlation matrix locate outside the prediction of the random matrix theory and these deviating eigenvalues and their corresponding eigenvectors contain rich economic information. Specifically, the largest eigenvalue reflects a collective effect of the global market, other four largest eigenvalues possess a partitioning function to distinguish the six clusters, and the smallest eigenvalues highlight the pairs of time series with the largest correlation coefficients. We construct an index of the global oil market based on the eigenfortfolio of the largest eigenvalue, which evolves similarly as the average price time series and has better performance than the benchmark $1/N$ portfolio under the buy-and-hold strategy., 13 Latex pages including 7 figures and 1 table

The production cross sections of superheavy nuclei in hot fusion reactions are investigated systematically. In hot fusion reactions, the capture cross section can be obtained by calculating the weighted average of the transmission probability for different orientations of deformed colliding nuclei. An analytical formula for calculating the value of the fusion probability is proposed, which is suitable for both hot and cold fusion reactions. The orientation effects are considered empirically in calculating the fusion probability. The method proposed in the present work reproduces the measured evaporation residue (ER) cross sections in hot fusion reactions acceptably well. The formula also gives reasonable results for fusion probability in cold fusion reactions. Using this method the evaporation residue cross sections for synthesizing $Z=119$ and 120 are predicted. It is found that for hot fusion reaction's larger maximal ER cross section of the $4n$ channel corresponds to lower optimal incident energy.

The expanding dynamics in central ${}^{129}$ Xe + ${}^{120}$Sn collisions at 50 MeV/nucleon is investigated within the framework of the isospin-dependent quantum molecular dynamics model in combination with the statistical decay code gemini. The nonisotropic distributions in the fragment size and average kinetic energy are reproduced. The collective expansion energy and the Coulomb explosion energy of different fragments are extracted. We focus on the nonisotropic explosion of the colliding system and the difference of explosion energies of H, He, Li, and Be fragments. The radial flow energies are extracted at the polar angle ${\ensuremath{\theta}}_{c.m.}$ = 90${}^{\ensuremath{\circ}}$. From studying the beam energy dependence at 50--125 MeV/nucleon, the threshold energies of the radial flow are investigated. The time evolutions of the density and the collective velocity are investigated. It is found that the radial flow causes the system to expand in the isotropic direction, whereas the residual incident energy causes the system to extend along the longitudinal direction. The Pauli blocking is responsible for the nonisotropic nature of the collective velocity.

Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975–2011) at the state level based on the Random Matrix Theory (RMT).WeidentifyrichereconomicinformationinthelargesteigenvaluesdeviatingfromRMTpredictions for the housing market than forstockmarkets and findthat the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. Wefindthatdramaticincreasesinthesystemicriskareusuallyaccompaniedbyregimeshifts, whichprovide a means of early detection of housing bubbles.

Traders adopt different trading strategies to maximize their returns in financial markets. These trading strategies not only results in specific topological structures in trading networks, which connect the traders with the pairwise buy-sell relationships, but also have potential impacts on market dynamics. Here, we present a detailed analysis on how the market behaviors are correlated with the structures of traders in trading networks based on audit trail data for the Baosteel stock and its warrant at the transaction level from 22 August 2005 to 23 August 2006. In our investigation, we divide each trade day into 48 time windows with a length of five minutes, construct a trading network within each window, and obtain a time series of over 1,100 trading networks. We find that there are strongly simultaneous correlations between the topological metrics (including network centralization, assortative index, and average path length) of trading networks that characterize the patterns of order execution and the financial variables (including return, volatility, intertrade duration, and trading volume) for the stock and its warrant. Our analysis may shed new lights on how the microscopic interactions between elements within complex system affect the system's performance., 3 tables and 5 pages

Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify rich economic information in the largest eigenvalues deviating from RMT predictions and unveil that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. Our results show that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. Our analysis uncovers that dramatic increases in the systemic risk are usually accompanied with regime shifts, which provides a means of early detection of housing bubbles., 8 RevTex pages including 4 eps figures

Humans are heterogenous and the behaviors of individuals could be different from that at the population level. We conduct an in-depth study of the temporal patterns of cellphone conversation activities of 73'339 anonymous cellphone users with the same truncated Weibull distribution of inter-call durations. We find that the individual call events exhibit a pattern of bursts, in which high activity periods are alternated with low activity periods. Surprisingly, the number of events in high activity periods are found to conform to a power-law distribution at the population level, but follow an exponential distribution at the individual level, which is a hallmark of absence of memory in individual call activities. Such exponential distribution is also observed for the number of events in low activity periods. Together with the exponential distributions of inter-call durations within bursts and of the intervals between consecutive bursts, we demonstrate that the individual call activities are driven by two independent Poisson processes, which can be combined within a minimal model in terms of a two-state first-order Markov chain giving very good agreement with the empirical distributions using the parameters estimated from real data for about half of the individuals in our sample. By measuring directly the distributions of call rates across the population, which exhibit power-law tails, we explain the difference with previous population level studies, purporting the existence of power-law distributions, via the "Superposition of Distributions" mechanism: The superposition of many exponential distributions of activities with a power-law distribution of their characteristic scales leads to a power-law distribution of the activities at the population level., 16 pages, 7 figures

We study trade-based manipulation of stock prices from the perspective of complex trading networks constructed by using detailed information of trades. A stock trading network consists of nodes and directed links, where every trader is a node and a link is formed from one trader to the other if the former sells shares to the latter. Specifically, three abnormal network motifs are investigated, which are found to be formed by a few traders, implying potential intention of price manipulation. We further investigate the dynamics of volatility, trading volume, average trade size and turnover around the transactions associated with the abnormal motifs for large, medium and small trades. It is found that these variables peak at the abnormal events and exhibit a power-law accumulation in the pre-event time period and a power-law relaxation in the post-event period. We also find that the cumulative excess returns are significantly positive after buyer-initiated suspicious trades and exhibit a mild price reversal after seller-initiated suspicious trades. These findings can be better understood in favor of price manipulation. Our work shed new lights into the detection of price manipulation resorting to the abnormal motifs of complex trading networks., 14 Latex pages including 5 figures and 2 tables, Submitted to QFL

Energy markets and the associated energy futures markets play a crucial role in global economies. We investigate the statistical properties of the recurrence intervals of daily volatility time series of four NYMEX energy futures, which are defined as the waiting times $\tau$ between consecutive volatilities exceeding a given threshold $q$. We find that the recurrence intervals are distributed as a stretched exponential $P_q(\tau)\sim e^{(a\tau)^{-\gamma}}$, where the exponent $\gamma$ decreases with increasing $q$, and there is no scaling behavior in the distributions for different thresholds $q$ after the recurrence intervals are scaled with the mean recurrence interval $\bar\tau$. These findings are significant under the Kolmogorov-Smirnov test and the Cram{\'e}r-von Mises test. We show that empirical estimations are in nice agreement with the numerical integration results for the occurrence probability $W_q(\Delta{t}|t)$ of a next event above the threshold $q$ within a (short) time interval after an elapsed time $t$ from the last event above $q$. We also investigate the memory effects of the recurrence intervals. It is found that the conditional distributions of large and small recurrence intervals differ from each other and the conditional mean of the recurrence intervals scales as a power law of the preceding interval $\bar\tau(\tau_0)/\bar\tau \sim (\tau_0/\bar\tau)^\beta$, indicating that the recurrence intervals have short-term correlations. Detrended fluctuation analysis and detrending moving average analysis further uncover that the recurrence intervals possess long-term correlations. We confirm that the "clustering" of the volatility recurrence intervals is caused by the long-term correlations well known to be present in the volatility., Comment: 11 pages, 8 figures and 3 tables

To investigate the expressions of brain natriuretic peptide (BNP) and natriuretic peptide receptor (NPR-A) in the cord dorsal horn ganglion (DRG) of rat models of chronic nonbacterial prostatitis (CNP) and the relation of BNP and NPR-A with CNP-induced chronic pain.We established CNP models in 30 healthy clean SD rats using Freund's complete adjuvant, and included another 10 in a sham-operation group. The prostate tissues were subjected to HE staining, and the expressions of BNP and NPR-A in the L5-S2 DRGs were detected by real-time PCR.Higher degree of inflammation was related to longer modeling time. At 3, 7 and 10 days, the expressions of BNP in the CNP models were 2.16 +/- 0.35, 1.61 +/- 0.21 and 1.32 +/- 0.36, and those of NPR-A were 2.75 +/- 0.06, 2.15 +/- 0.15 and 1.04 +/- 0.13, respectively, significantly higher at 3 and 7 days as compared with the sham-operation group (P0.05), but with no statistically significant difference at 10 days.BNP and NPR-A are expressed in the L5-S2 DRGs of SD rats and their expressions can be upregulated by CNP. BNP and NPR-A may be involved in the mechanisms of CNP-induced pain.

Paired-like homodomain transcription factor 3 has been found to be important for the differentiation and survival of midbrain dopaminergic neurons.To determine whether genetic variation in the coding region of the paired-like homodomain transcription factor 3 gene plays a role in Parkinson's disease, genetic analysis was performed in 112 patients with Parkinson's disease.We did not identify any mutations except rs2281983, but when we extended the analysis of rs2281983 and 2 intron variants (rs4919621 and rs3758549) in 336 patients with Parkinson's disease and 244 controls, we found that rs2281983 and rs4919621 appeared to confer susceptibility to Parkinson's disease, especially in early-onset Parkinson's disease and familial Parkinson's disease.

Within the isospin-dependent quantum molecular dynamics model, we investigate the nuclear collective flows produced in semi-central 197Au+197 Au collisions at intermediate energies. The neutron–proton differential flows and difference of neutron–proton collective flows are sensitive to the momentum-dependent symmetry potential. This sensitivity is less affected by both the isoscalar part of nuclear equation of state and in-medium nucleon–nucleon cross sections. Moreover, this sensitivity becomes pronounced with increasing the rapidity cut.

The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a markedly fall during the global financial tsunami and China's economy has also slowed down by about 2\%-3\% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than ten years. However, the structure and dynamics of the Chinese housing market are less studied. Here we perform an extensive study of the Chinese housing market by analyzing ten representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5\% of the house price growth, indicating very high systemic risk in the Chinese housing market. The ten key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest, and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices in different cities., 16 Latex pages including 6 figures and 4 tables

To quantitatively evaluate the effects of dopamine (DA) and noradrenaline (NE) on renal medullary perfusion and the differences in perfusion in the outer and inner medulla using contrast-enhanced ultrasound.Contrast-enhanced ultrasound was performed in 10 dogs with simultaneous renal artery flow (RAF) measurement at the baseline level and during application of 3 different doses of DA and NE. During treatment with the 3 doses of DA, the changes of ultrasound-derived parameters (A, beta and A*beta) in the medulla were similar to the changes in the cortex. As compared with the baseline level, the ratios between the cortex and medulla exhibited no significant difference in A, beta and A*beta during DA treatment (P0.05). No significant difference in ultrasound-derived medullar parameters was noted in dogs with NE treatment from the baseline level (P0.05). However, a progressive decrease in the ratios of A, beta and A*beta between the cortex and medulla was noted during NE treatment in comparison with the baseline level (P0.05). The velocity (beta) and perfusion (A*beta) of blood flow in the medulla decreased progressively from the outer medulla to the inner medulla at baseline (P0.05), while the blood volume (A) remained unchanged (P0.05).The changes of blood flow in both the cortex and medulla are identical during DA treatment but different in the presence of NE. The progressive decrease in perfusion from the outer medulla to the inner medulla is attributed to the decrease in the velocity of blood flow.

The solar oscillations along one coronal loop in AR 11504 are observed simultaneously in white light emission and Doppler velocity by SDO/HMI, and in UV and EUV emissions by SDO/AIA. The technique of the time-distance diagram is used to detect the propagating oscillations of the emission intensities along the loop. We find that although all the oscillation signals were intercorrelated, the low chromospheric oscillation correlated more closely to the oscillations of the transition region and corona than to those of the photosphere. Situated above the sunspot, the oscillation periods were similar to 3 minutes in the UV/EUV emissions; however, moving away from the sunspot and into the quiet Sun, the periods became longer, e. g., up to similar to 5 minutes or more. In addition, along another loop we observe both the high-speed outflows and oscillations, which roughly had a one-to-one corresponding relationship. This indicates that the solar periodic oscillations may modulate the magnetic reconnections between the loops of the high and low altitudes that drive the high-speed outflows along the loop.