Prediction of Smoothed Sunspot Number Using Dynamic Relations Between the Sun and Planets

Dynamic parameters of sun and planet interaction for predicting sunspot

Statistical mechanics of ecosystem assembly

We introduce a toy model of ecosystem assembly for which we are able to map out all assembly pathways generated by external invasions. The model allows to display the whole phase space in the form of an assembly graph whose nodes are communities of species and whose directed links are transitions between them induced by invasions. We characterize the process as a finite Markov chain and prove that it exhibits a unique set of recurrent states (the endstate of the process), which is therefore resistant to invasions. This also shows that the endstate is independent on the assembly history. The model shares all features with standard assembly models reported in the literature, with the advantage that all observables can be computed in an exact manner.Comment: Accepted for publication in Physical Review Letter

Resting respiratory tract dendritic cells preferentially stimulate T helper cell Type 2(Th2) responses and require obligatory cytokine signals for induction of Th1 immunity

Consistent with their role in host defense, mature dendritic cells (DCs) from central lymphoid organs preferentially prime for T helper cell type 1 (Th1)-polarized immunity. However, the “default” T helper response at mucosal surfaces demonstrates Th2 polarity, which is reflected in the cytokine profiles of activated T cells from mucosal lymph nodes. This study on rat respiratory tract DCs (RTDCs) provides an explanation for this paradox. We demonstrate that freshly isolated RTDCs are functionally immature as defined in vitro, being surface major histocompatibility complex (MHC) II lo, endocytosishi, and mixed lymphocyte reactionlo, and these cells produce mRNA encoding interleukin (IL)-10. After ovalbumin (OVA)-pulsing and adoptive transfer, freshly isolated RTDCs preferentially stimulated Th2-dependent OVA-specific immunoglobulin (Ig)G1 responses, and antigen-stimulated splenocytes from recipient animals produced IL-4 in vitro. However, preculture with granulocyte/macrophage colony stimulating factor increased their in vivo IgG priming capacity by 2–3 logs, inducing production of both Th1- and Th2-dependent IgG subclasses and high levels of IFN-γ by antigen-stimulated splenocytes. Associated phenotypic changes included upregulation of surface MHC II and B7 expression and IL-12 p35 mRNA, and downregulation of endocytosis, MHC II processing– associated genes, and IL-10 mRNA expression. Full expression of IL-12 p40 required additional signals, such as tumor necrosis factor α or CD40 ligand. These results suggest that the observed Th2 polarity of the resting mucosal immune system may be an inherent property of the resident DC population, and furthermore that mobilization of Th1 immunity relies absolutely on the provision of appropriate microenvironmental costimuli

Modeling the evolution of weighted networks

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement mechanism coupled to the local network growth. That coupling can be generalized in order to include the effect of additional randomness and non-linearities which can be present in real-world networks. The model generates weighted graphs exhibiting the statistical properties observed in several real-world systems. In particular, the model yields a non-trivial time evolution of vertices properties and scale-free behavior with exponents depending on the microscopic parameters characterizing the coupling rules. Very interestingly, the generated graphs spontaneously achieve a complex hierarchical architecture characterized by clustering and connectivity correlations varying as a function of the vertices' degree

Global protected area impacts

Protected areas (PAs) dominate conservation efforts. They will probably play a role in future climate policies too, as global payments may reward local reductions of loss of natural land cover. We estimate the impact of PAs on natural land cover within each of 147 countries by comparing outcomes inside PAs with outcomes outside. We use ‘matching’ (or ‘apples to apples’) for land characteristics to control for the fact that PAs very often are non-randomly distributed across their national landscapes. Protection tends towards land that, if unprotected, is less likely than average to be cleared. For 75 per cent of countries, we find protection does reduce conversion of natural land cover. However, for approximately 80 per cent of countries, our global results also confirm (following smaller-scale studies) that controlling for land characteristics reduces estimated impact by half or more. This shows the importance of controlling for at least a few key land characteristics. Further, we show that impacts vary considerably within a country (i.e. across a landscape): protection achieves less on lands far from roads, far from cities and on steeper slopes. Thus, while planners are, of course, constrained by other conservation priorities and costs, they could target higher impacts to earn more global payments for reduced deforestation

Weighted evolving networks: coupling topology and weights dynamics

We propose a model for the growth of weighted networks that couples the establishment of new edges and vertices and the weights' dynamical evolution. The model is based on a simple weight-driven dynamics and generates networks exhibiting the statistical properties observed in several real-world systems. In particular, the model yields a non-trivial time evolution of vertices' properties and scale-free behavior for the weight, strength and degree distributions.Comment: 4 pages, 4 figure

Resolution limit in community detection

Detecting community structure is fundamental to clarify the link between structure and function in complex networks and is used for practical applications in many disciplines. A successful method relies on the optimization of a quantity called modularity [Newman and Girvan, Phys. Rev. E 69, 026113 (2004)], which is a quality index of a partition of a network into communities. We find that modularity optimization may fail to identify modules smaller than a scale which depends on the total number L of links of the network and on the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined. The probability that a module conceals well-defined substructures is the highest if the number of links internal to the module is of the order of \sqrt{2L} or smaller. We discuss the practical consequences of this result by analyzing partitions obtained through modularity optimization in artificial and real networks.Comment: 8 pages, 3 figures. Clarification of definition of community in Section II + minor revision

Trajectories for the 1976 - 1980 Grand Tour opportunities. Volume 3 - Trajectory data for alternate Grand Tour missions

Tabulating trajectory data for alternate Grand Tour missions from earth for period 1976 to 198

Search in weighted complex networks

We study trade-offs presented by local search algorithms in complex networks which are heterogeneous in edge weights and node degree. We show that search based on a network measure, local betweenness centrality (LBC), utilizes the heterogeneity of both node degrees and edge weights to perform the best in scale-free weighted networks. The search based on LBC is universal and performs well in a large class of complex networks.Comment: 14 pages, 5 figures, 4 tables, minor changes, added a referenc

Empirical study on clique-degree distribution of networks

The community structure and motif-modular-network hierarchy are of great importance for understanding the relationship between structures and functions. In this paper, we investigate the distribution of clique-degree, which is an extension of degree and can be used to measure the density of cliques in networks. The empirical studies indicate the extensive existence of power-law clique-degree distributions in various real networks, and the power-law exponent decreases with the increasing of clique size.Comment: 9 figures, 4 page