In this paper, we introduce a general framework for co-infection as cooperative SIR dynamics. We first solve analytically CGCG model [1] and then the generalized model in symmetric scenarios. We calculate transition points, order parameter, i.e. total number of infected hosts. Also we show analytically there is a saddle-node bifurcation for two cooperative SIR dynamics and the transition is hybrid. Moreover, we investigate where symmetric solution is stable for initial fluctuations. Then we study asymmetric cases of parameters. The more asymmetry, for the primary and secondary infection rates of one pathogen in comparison to the other pathogen, can lead to the less infected hosts, the higher epidemic threshold and continuous transitions. Our model and results for coinfection in combination with super-infection [2] can open a road to model disease ecology.

Jumps are discontinuous variations in time series and one expects that the higher jump activity will cause higher uncertainty in the stochastic behavior of measured time series. Here we study jump events in beat-to-beat fluctuations in the heart rates of healthy subjects, as well as those with congestive heart failure (CHF). The analysis shows that the interbeat time series belong to the class of non-continuous stochastic processes. The estimated drift and diffusion coefficients and jump characteristics of healthy and CHF subjects reveal the distinguishability of two subjects.

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Innovation is fundamental for development and provides a competitive advantage for societies. It is the process of creating more complex technologies, ideas, or protocols from existing ones. While innovation may be created by single agents (i.e. individuals or organisations), it is often a result of social interactions between agents exchanging and combining complementary expertise and perspectives. The structure of social networks impacts this knowledge exchange process. To study the role of social network structures on the creation of new technologies, we design an evolutionary mechanistic model combining self-creation and social learning. We find that social heterogeneity allows agents to leverage the benefits of diversity and to develop technologies of higher complexity. Social heterogeneity, however, reduces the group ability to innovate. Not only the social structure but also the openness of agents to collaborate affect innovation. We find that interdisciplinary interactions lead to more complex technologies benefiting the entire group but also increase the inequality in the innovation output. Lower openness to interdisciplinary collaborations may be compensated by a higher ability to collaborate with multiple peers, but low openness also neutralises the intrinsic benefits of network heterogeneity. Our findings indicate that social network heterogeneity has contrasting effects on microscopic (local) and macroscopic (group) levels, suggesting that the emergence of innovation leaders may suppress the overall group performance.

Background & aim: Neonatal hyperbilirubinemia is most common reason to re-admission in hospital. The mother's basic disorders are access and effects on this phenomenon. The aim of this study is to determinate and relation of hypertension, age and drug addiction in mothers on neonatal hyperbilirubinemia. Methods:In this analytical descriptive study which done in 2018, the 300 mother's documents which refer to hospital for hospitalization their babies were studied. The questionnaire regarding maternal and their neonates were completed. Mothers and neonates information, degree of icterus, mother's hypertension and drug addiction history, family icterus history, kind of delivery, mother and neonate body weight, familiar wedding and number of labor were collected and evaluated. All data were evaluated statistically by SPSS and MINITAB method . Results:The results of this study showed that the affection chance in neonates with mother's 21-30, 31-35 years old and 36 years old and up compare to neonates with their mothers under 20 years old (reference sheet) were about 2.95, 2.15 and 1.92 manifold respectively. The affection chance for hyperbilirubinemia in neonates with their mothers which have hypertension was 4 manifold compared to neonates with normal mothers. The affection chance for hyperbilirubinemia in neonates with their preterm mothers (less than 38 weeks) was 1.76 manifold mothers with complete term( more than 38 weeks). The affection chance for hyperbilirubinemia in neonates with their mothers which delivered naturally 1.56 manifold compared to mothers which labored her babies by cesarean section. There is to calculate probability of hyperbilirubinemia in neonates with using of predictive alternatives of mother's age in delivery time, pregnancy hypertension, pregnancy age and type of delivery with logistic regression presentation Conclusion:This study explained that the mother's age in delivery time, pregnancy hypertension, age of gestation and type of labor have effects on neonatal hyperbilirubinemia. The fitting of logistic regression model on studying data and optimization operations showed that the mother's age under 20 years, without hypertension, term gestation and cesarean delivery have reduce hyperbilirubinemia probability to 26% in neonates.