**23** Publications

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Proc Natl Acad Sci U S A 2021 Jun;118(22)

Department of Physics, Bar-Ilan University, Ramat-Gan 52900, Israel.

Coupling between networks is widely prevalent in real systems and has dramatic effects on their resilience and functional properties. However, current theoretical models tend to assume homogeneous coupling where all the various subcomponents interact with one another, whereas real-world systems tend to have various different coupling patterns. We develop two frameworks to explore the resilience of such modular networks, including specific deterministic coupling patterns and coupling patterns where specific subnetworks are connected randomly. We find both analytically and numerically that the location of the percolation phase transition varies nonmonotonically with the fraction of interconnected nodes when the total number of interconnecting links remains fixed. Furthermore, there exists an optimal fraction [Formula: see text] of interconnected nodes where the system becomes optimally resilient and is able to withstand more damage. Our results suggest that, although the exact location of the optimal [Formula: see text] varies based on the coupling patterns, for all coupling patterns, there exists such an optimal point. Our findings provide a deeper understanding of network resilience and show how networks can be optimized based on their specific coupling patterns.

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http://dx.doi.org/10.1073/pnas.1922831118 | DOI Listing |

June 2021

Phys Rev E 2021 Jan;103(1-1):012302

School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USA.

The inverse problem of finding the optimal network structure for a specific type of dynamical process stands out as one of the most challenging problems in network science. Focusing on the susceptible-infected-susceptible type of dynamics on annealed networks whose structures are fully characterized by the degree distribution, we develop an analytic framework to solve the inverse problem. We find that, for relatively low or high infection rates, the optimal degree distribution is unique, which consists of no more than two distinct nodal degrees. For intermediate infection rates, the optimal degree distribution is multitudinous and can have a broader support. We also find that, in general, the heterogeneity of the optimal networks decreases with the infection rate. A surprising phenomenon is the existence of a specific value of the infection rate for which any degree distribution would be optimal in generating maximum spreading prevalence. The analytic framework and the findings provide insights into the interplay between network structure and dynamical processes with practical implications.

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http://dx.doi.org/10.1103/PhysRevE.103.012302 | DOI Listing |

January 2021

Opt Lett 2021 Jan;46(1):82-85

We demonstrated a high-power -switched two-stage Ho:YAG master-oscillator power-amplifier (MOPA) system dual-end pumped by Tm:YLF lasers. A new method was introduced by rotating and swapping spatial axial directions of pump beams to improve the beam quality of the Ho:YAG oscillator and first-stage amplifier. Two parallel second-stage Ho:YAG amplifiers were employed to output high power. A total maximum average output power of 332 W at 2091 nm with pulse repetition frequency of 20 kHz was achieved. Then a MOPA system was demonstrated using the Ho:YAG MOPA as the pump source. A maximum average output power of 161 W at 3-5 µm was obtained with 290 W incident Ho pump power, corresponding to beam quality factors of 3.42 and 3.83 for horizontal and vertical directions, respectively.

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http://dx.doi.org/10.1364/OL.413755 | DOI Listing |

January 2021

Appl Energy 2021 Jan 9;281:116043. Epub 2020 Nov 9.

School of Mathematical Sciences, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing, China.

There is increasing interest in CO emissions inequality between and within countries, and concerns about the impacts of COVID-19 on vulnerable groups. In this study, the CO emissions inequality based on the different consumption category data of disaggregated income groups in eight developing countries is analyzed with the application of input-output model. We further examine the effects of the COVID-19 outbreak on CO emissions inequality based on the hypothetical extraction method, and the results reveal that the outbreak has decreased the CO emissions inequality and emissions over time. However, the shared socioeconomic pathway scenario simulation results indicate that long-term CO emissions inequality will persist. Targeted poverty elimination measures improve the utility of the low- and lowest-income groups and reduce CO emissions inequality. Reducing the excessive consumption on the demand side as well as improving the energy efficiency and increasing the share of renewable energy in the energy consumption on the supply side will provide more informed options to achieve multiple desirable outcomes, such as poverty elimination and climate change mitigation.

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http://dx.doi.org/10.1016/j.apenergy.2020.116043 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7651240 | PMC |

January 2021

Sci Total Environ 2020 Jul 17;727:138710. Epub 2020 Apr 17.

School of Mathematical Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China.

This paper explores green development of Yangtze River Delta (YRD) under PREDS (Population-Resources-Environment-Development-Satisfaction) perspective. Based on gray relevance analysis, synergy evaluation model and factor analysis model are constructed with improvement of weight determination and relevance degree calculation. Synergy evaluation results show that for the entire YRD the relevance degree of green development increases strictly. As the synergistic effect of the inner system continues to rise, the green development tend toward equilibrium (2003-2017). The provincial level green development ranking is put forward. The results of factor analysis show that four dimensions' impacts on public satisfaction are different. The prediction of "13th Five-Year Plan" suggests that, improving environmental indicators is the most potential solution to promote green development of YRD. Investment completed in industrial pollution treatment is taken as an example to show how the index will affect satisfaction under different growth rates. It turns out that when the growth rate is below or over the critical value (16%), the influence will go out of the trough and continue to increase, forming a "J" curve.

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http://dx.doi.org/10.1016/j.scitotenv.2020.138710 | DOI Listing |

July 2020

Medicine (Baltimore) 2020 Jan;99(4):e18743

Department of Acupuncture and Moxibustion, Tianjin Gong An Hospital, Tianjin, 300042.

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http://dx.doi.org/10.1097/MD.0000000000018743 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004790 | PMC |

January 2020

Chaos 2019 Jul;29(7):073107

Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA.

Interdependent networks as an important structure of the real system not only include one-to-one dependency relationship but also include more realistic undirected multiple interdependent relationship. The study on interdependent networks plays an important role in designing more resilient real systems. Here, we mainly focus on the case of interdependent networks with a multiple-to-multiple correspondence of interdependent nodes by generalizing feedback and nonfeedback conditions. We develop a new mathematical framework and study numerically and analytically the percolation of interdependent networks with partial multiple-to-multiple dependency links by using percolation theory. By analyzing the process of cascading failure, the size of the giant component and the critical threshold are analytically obtained and testified by simulation results for couple Erdös-Re˙nyi and scale-free networks. The results imply that the system shows a discontinuous phase transition for different coupling strengths. We find that the system becomes more resilient and easy to defend by increasing the coupling strength and the connectivity density. Our model has the potential to shed light on designing more resilient real-world dependent systems.

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http://dx.doi.org/10.1063/1.5093074 | DOI Listing |

July 2019

PLoS One 2018 5;13(9):e0202209. Epub 2018 Sep 5.

Energy Development and Environmental Protection Strategy Research Center, Jiangsu University, Zhenjiang, Jiangsu, China.

Analyzing and predicting the trend of price fluctuation has been receiving more and more attention, as price risk has become the focus of risk control research in heating oil futures market. A novel time series prediction model combined with the complex network method is put forward in the paper. First of all, this paper counts the cumulative time interval of different nodes in the network, and fits its growth trend with the Fourier model. Then a novel price fluctuation prediction model is established based on the effective information such as some topology properties extracted from the network. The results show that the Fourier model can predict the emergence time of new nodes in the next stage, and the established price fluctuation prediction model can infer the names of nodes in the prediction interval, so as to determine the forward-looking behavior of price evolution. Besides, liken to the NAR neural network, the prediction results obtained by the proposed method also show superiority, which has important theoretical value and academic significance for early warning and prediction of price behavior in the heating oil futures market.

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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0202209 | PLOS |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6124714 | PMC |

February 2019

Proc Natl Acad Sci U S A 2018 07 20;115(27):6911-6915. Epub 2018 Jun 20.

Department of Physics, Bar-Ilan University, Ramat-Gan 52900, Israel.

Although detecting and characterizing community structure is key in the study of networked systems, we still do not understand how community structure affects systemic resilience and stability. We use percolation theory to develop a framework for studying the resilience of networks with a community structure. We find both analytically and numerically that interlinks (the connections among communities) affect the percolation phase transition in a way similar to an external field in a ferromagnetic- paramagnetic spin system. We also study universality class by defining the analogous critical exponents and , and we find that their values in various models and in real-world coauthor networks follow the fundamental scaling relations found in physical phase transitions. The methodology and results presented here facilitate the study of network resilience and also provide a way to understand phase transitions under external fields.

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http://dx.doi.org/10.1073/pnas.1801588115 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142202 | PMC |

July 2018

Phys Rev E 2018 May;97(5-1):052117

Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA.

The limited penetrable horizontal visibility graph algorithm was recently introduced to map time series in complex networks. In this work, we extend this algorithm to create a directed-limited penetrable horizontal visibility graph and an image-limited penetrable horizontal visibility graph. We define two algorithms and provide theoretical results on the topological properties of these graphs associated with different types of real-value series. We perform several numerical simulations to check the accuracy of our theoretical results. Finally, we present an application of the directed-limited penetrable horizontal visibility graph to measure real-value time series irreversibility and an application of the image-limited penetrable horizontal visibility graph that discriminates noise from chaos. We also propose a method to measure the systematic risk using the image-limited penetrable horizontal visibility graph, and the empirical results show the effectiveness of our proposed algorithms.

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http://dx.doi.org/10.1103/PhysRevE.97.052117 | DOI Listing |

May 2018

Sci Rep 2018 Mar 23;8(1):5130. Epub 2018 Mar 23.

Center for Polymer Studies and Department of Physics, Boston University, Boston, MA, 02215, USA.

The limited penetrable horizontal visibility algorithm is an analysis tool that maps time series into complex networks and is a further development of the horizontal visibility algorithm. This paper presents exact results on the topological properties of the limited penetrable horizontal visibility graph associated with independent and identically distributed (i:i:d:) random series. We show that the i.i.d: random series maps on a limited penetrable horizontal visibility graph with exponential degree distribution, independent of the probability distribution from which the series was generated. We deduce the exact expressions of mean degree and clustering coefficient, demonstrate the long distance visibility property of the graph and perform numerical simulations to test the accuracy of our theoretical results. We then use the algorithm in several deterministic chaotic series, such as the logistic map, H´enon map, Lorenz system, energy price chaotic system and the real crude oil price. Our results show that the limited penetrable horizontal visibility algorithm is efficient to discriminate chaos from uncorrelated randomness and is able to measure the global evolution characteristics of the real time series.

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http://dx.doi.org/10.1038/s41598-018-23388-1 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5865175 | PMC |

March 2018

PLoS One 2017 22;12(12):e0188816. Epub 2017 Dec 22.

School of Mathematical Science, Taizhou Institute of Sci. & Tech., NUST, Taizhou, Jiangsu, China.

In this paper, based on the panel data of 31 provinces and cities in China from 1991 to 2016, the regional development efficiency matrix of high-end talent is obtained by DEA method, and the matrix is converted into a continuous change of complex networks through the construction of sliding window. Using a series of continuous changes in the complex network topology statistics, the characteristics of regional high-end talent development efficiency system are analyzed. And the results show that the average development efficiency of high-end talent in the western region is at a low level. After 2005, the national regional high-end talent development efficiency network has both short-range relevance and long-range relevance in the evolution process. The central region plays an important intermediary role in the national regional high-end talent development system. And the western region has high clustering characteristics. With the implementation of the high-end talent policies with regional characteristics by different provinces and cities, the relevance of high-end talent development efficiency in various provinces and cities presents a weakening trend, and the geographical characteristics of high-end talent are more and more obvious.

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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0188816 | PLOS |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741225 | PMC |

January 2018

Appl Energy 2017 May 17;194:635-647. Epub 2016 Feb 17.

School of Economics, Nanjing University of Finance and Economics, Nanjing, Jiangsu 210023, China.

This paper attempts to explore carbon tax pilot in Yangtze River Delta (YRD) urban agglomerations based on a novel energy-saving and emission-reduction (ESER) system with carbon tax constraints, which has not yet been discussed in present literature. A novel carbon tax attractor is achieved through the discussion of the dynamic behavior of the new system. Based on the genetic algorithm-back propagation neural network, the quantitative coefficients of the actual system are identified. The scenario analysis results show that, under the same tax rate and constraint conditions, the ESER system in YRD urban agglomerations is superior to the average case in China, in which the impacts on economic growth are almost the same. The former's energy intensity is lower and the shock resistance is stronger. It is found that economic property of YRD urban agglomerations is the main cause for the ESER system of YRD urban agglomerations being superior. In the current YRD urban agglomerations' ESER system, energy intensity cannot be adjusted to an ideal level by commercialization management and government control; however, it is under effective control of carbon tax incentives. Therefore, strengthening the economic property of YRD urban agglomerations and effective utilization of carbon tax incentives could perfectly control energy intensity, without obvious potential negative impact on economic growth.

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http://dx.doi.org/10.1016/j.apenergy.2016.02.041 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7117014 | PMC |

May 2017

Sci Rep 2017 03 24;7:45237. Epub 2017 Mar 24.

Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA.

Strategies adopted by individuals in a social network significantly impact the network, and they strongly affect relationships between individuals in the network. Links between individuals also heavily influence their levels of cooperation. Taking into account the evolution of each individual's connection, we explore how sensitivity and visibility affect the prisoner's dilemma game. The so-called 'sensitivity' and 'visibility' respectively present one's self-protection consciousness and the ability of gaining information. We find that at moderate levels of player sensitivity cooperative behavior increases, but that at high levels it is inhibited. We also find that the heterogeneity of the weight of individuals at the end of the game is higher when sensitivity and visibility are increased, but that the successful-defection-payoff has less impact on the weight of individuals and on the relationship between the heterogeneity of the weight of individuals and the density of cooperators. This framework can be used to clarify the interaction mechanism between the micro-level of individual behavior and the macro-level of individual co-evolutionary processes.

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http://dx.doi.org/10.1038/srep45237 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5364401 | PMC |

March 2017

PLoS One 2016 5;11(10):e0162362. Epub 2016 Oct 5.

Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts, United States of America.

We study the overall topological structure properties of global oil trade network, such as degree, strength, cumulative distribution, information entropy and weight clustering. The structural evolution of the network is investigated as well. We find the global oil import and export networks do not show typical scale-free distribution, but display disassortative property. Furthermore, based on the monthly data of oil import values during 2005.01-2014.12, by applying random matrix theory, we investigate the complex spatiotemporal dynamic from the country level and fitness evolution of the global oil market from a demand-side analysis. Abundant information about global oil market can be obtained from deviating eigenvalues. The result shows that the oil market has experienced five different periods, which is consistent with the evolution of country clusters. Moreover, we find the changing trend of fitness function agrees with that of gross domestic product (GDP), and suggest that the fitness evolution of oil market can be predicted by forecasting GDP values. To conclude, some suggestions are provided according to the results.

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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0162362 | PLOS |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5051899 | PMC |

June 2017

J Math Phys 2016 Mar 7;57(3):031502. Epub 2016 Mar 7.

Department of Mathematics, Southeast University , Nanjing 210096, People's Republic of China.

In this paper, we are concerned with a class of Schrödinger-Poisson systems with the asymptotically linear or asymptotically 3-linear nonlinearity. Under some suitable assumptions on , , , and , we prove the existence, nonexistence, and asymptotic behavior of solutions via variational methods. In particular, the potential is allowed to be sign-changing for the asymptotically linear case.

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http://dx.doi.org/10.1063/1.4941036 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4788608 | PMC |

March 2016

Environ Sci Pollut Res Int 2016 Feb 22;23(4):3621-31. Epub 2015 Oct 22.

Nonlinear Scientific Research Center, Faculty of Science, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.

Air quality depends mainly on changes in emission of pollutants and their precursors. Understanding its characteristics is the key to predicting and controlling air quality. In this study, complex networks were built to analyze topological characteristics of air quality data by correlation coefficient method. Firstly, PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) indexes of eight monitoring sites in Beijing were selected as samples from January 2013 to December 2014. Secondly, the C-C method was applied to determine the structure of phase space. Points in the reconstructed phase space were considered to be nodes of the network mapped. Then, edges were determined by nodes having the correlation greater than a critical threshold. Three properties of the constructed networks, degree distribution, clustering coefficient, and modularity, were used to determine the optimal value of the critical threshold. Finally, by analyzing and comparing topological properties, we pointed out that similarities and difference in the constructed complex networks revealed influence factors and their different roles on real air quality system.

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http://dx.doi.org/10.1007/s11356-015-5596-y | DOI Listing |

February 2016

Chaos 2015 Jan;25(1):013101

Institute for Information Economy, Hangzhou Normal University, Hangzhou 310016, China.

When real networks are considered, coupled networks with connectivity and feedback-dependency links are not rare but more general. Here, we develop a mathematical framework and study numerically and analytically the percolation of interacting networks with feedback-dependency links. For the case that all degree distributions of intra- and inter- connectivity links are Poissonian, we find that for a low density of inter-connectivity links, the system undergoes from second order to first order through hybrid phase transition as coupling strength increases. It implies that the average degree k of inter-connectivity links has a little influence on robustness of the system with a weak coupling strength, which corresponds to the second order transition, but for a strong coupling strength corresponds to the first order transition. That is to say, the system becomes robust as k increases. However, as the average degree k of each network increases, the system becomes robust for any coupling strength. In addition, we find that one can take less cost to design robust system as coupling strength decreases by analyzing minimum average degree kmin of maintaining system stability. Moreover, for high density of inter-connectivity links, we find that the hybrid phase transition region disappears, the first order region becomes larger and second order region becomes smaller. For the case of two coupled scale-free networks, the system also undergoes from second order to first order through hybrid transition as the coupling strength increases. We find that for a weak coupling strength, which corresponds to the second order transitions, feedback dependency links have no effect on robustness of system relative to no-feedback condition, but for strong coupling strength which corresponds to first order or hybrid phase transition, the system is more vulnerable under feedback condition comparing with no-feedback condition. Thus, for designing resilient system, designers should try to avoid the feedback dependency links, because the existence of feedback-dependency links makes the system extremely vulnerable and difficult to defend.

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http://dx.doi.org/10.1063/1.4905202 | DOI Listing |

January 2015

Phys Rev E Stat Nonlin Soft Matter Phys 2013 May 16;87(5):052804. Epub 2013 May 16.

Nonlinear Scientific Research Center, Faculty of Science, Jiangsu University, Zhenjiang 212013, China.

The robustness of a network of networks (NON) under random attack has been studied recently [Gao et al., Phys. Rev. Lett. 107, 195701 (2011)]. Understanding how robust a NON is to targeted attacks is a major challenge when designing resilient infrastructures. We address here the question how the robustness of a NON is affected by targeted attack on high- or low-degree nodes. We introduce a targeted attack probability function that is dependent upon node degree and study the robustness of two types of NON under targeted attack: (i) a tree of n fully interdependent Erdős-Rényi or scale-free networks and (ii) a starlike network of n partially interdependent Erdős-Rényi networks. For any tree of n fully interdependent Erdős-Rényi networks and scale-free networks under targeted attack, we find that the network becomes significantly more vulnerable when nodes of higher degree have higher probability to fail. When the probability that a node will fail is proportional to its degree, for a NON composed of Erdős-Rényi networks we find analytical solutions for the mutual giant component P(∞) as a function of p, where 1-p is the initial fraction of failed nodes in each network. We also find analytical solutions for the critical fraction p(c), which causes the fragmentation of the n interdependent networks, and for the minimum average degree k[over ¯](min) below which the NON will collapse even if only a single node fails. For a starlike NON of n partially interdependent Erdős-Rényi networks under targeted attack, we find the critical coupling strength q(c) for different n. When q>q(c), the attacked system undergoes an abrupt first order type transition. When q≤q(c), the system displays a smooth second order percolation transition. We also evaluate how the central network becomes more vulnerable as the number of networks with the same coupling strength q increases. The limit of q=0 represents no dependency, and the results are consistent with the classical percolation theory of a single network under targeted attack.

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http://dx.doi.org/10.1103/PhysRevE.87.052804 | DOI Listing |

May 2013

Materials (Basel) 2013 Apr 16;6(4):1543-1553. Epub 2013 Apr 16.

Key Laboratory of Semiconductor Materials Science, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China.

We report a new method for growing hexagonal columnar nanograin structured silicon carbide (SiC) thin films on silicon substrates by using graphene-graphitic carbon nanoflakes (GGNs) templates from solid carbon sources. The growth was carried out in a conventional low pressure chemical vapor deposition system (LPCVD). The GGNs are small plates with lateral sizes of around 100 nm and overlap each other, and are made up of nanosized multilayer graphene and graphitic carbon matrix (GCM). Long and straight SiC nanograins with hexagonal shapes, and with lateral sizes of around 200-400 nm are synthesized on the GGNs, which form compact SiC thin films.

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http://dx.doi.org/10.3390/ma6041543 | DOI Listing |

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5452306 | PMC |

April 2013

J Tradit Chin Med 2012 Sep;32(3):471-6

First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300192, China.

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http://dx.doi.org/10.1016/s0254-6272(13)60057-6 | DOI Listing |

September 2012

Phys Rev E Stat Nonlin Soft Matter Phys 2012 Jan 23;85(1 Pt 2):016112. Epub 2012 Jan 23.

Nonlinear Scientific for Research Center, Faculty of Science, Jiangsu University, Zhenjiang, 212013, China.

We study a system composed of two partially interdependent networks; when nodes in one network fail, they cause dependent nodes in the other network to also fail. In this paper, the percolation of partially interdependent networks under targeted attack is analyzed. We apply a general technique that maps a targeted-attack problem in interdependent networks to a random-attack problem in a transformed pair of interdependent networks. We illustrate our analytical solutions for two examples: (i) the probability for each node to fail is proportional to its degree, and (ii) each node has the same probability to fail in the initial time. We find the following: (i) For any targeted-attack problem, for the case of weak coupling, the system shows a second order phase transition, and for the strong coupling, the system shows a first order phase transition. (ii) For any coupling strength, when the high degree nodes have higher probability to fail, the system becomes more vulnerable. (iii) There exists a critical coupling strength, and when the coupling strength is greater than the critical coupling strength, the system shows a first order transition; otherwise, the system shows a second order transition.

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http://dx.doi.org/10.1103/PhysRevE.85.016112 | DOI Listing |

January 2012

Artif Intell Med 2012 Feb 2;54(2):147-9. Epub 2012 Jan 2.

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http://dx.doi.org/10.1016/j.artmed.2011.12.002 | DOI Listing |

February 2012