Analyzing Trails in Complex Networks

Even more interesting than the intricate organization of complex networks are the dynamical behavior of systems which such structures underly. Among the many types of dynamics, one particularly interesting category involves the evolution of trails left by moving agents progressing through random walks and dilating processes in a complex network. The emergence of trails is present in many dynamical process, such as pedestrian traffic, information flow and metabolic pathways. Important problems related with trails include the reconstruction of the trail and the identification of its source, when complete knowledge of the trail is missing. In addition, the following of trails in multi-agent systems represent a particularly interesting situation related to pedestrian dynamics and swarming intelligence. The present work addresses these three issues while taking into account permanent and transient marks left in the visited nodes. Different topologies are considered for trail reconstruction and trail source identification, including four complex networks models and four real networks, namely the Internet, the US airlines network, an email network and the scientific collaboration network of complex network researchers. Our results show that the topology of the network influence in trail reconstruction, source identification and agent dynamics.Comment: 10 pages, 16 figures. A working manuscript, comments and criticisms welcome

Gravitational lens effect of a holonomy corrected Schwarzschild black hole

In this paper we study the gravitational lensing effect for the Schwarzschild solution with holonomy corrections. We use two types of approximation methods to calculate the deflection angle, namely the weak and strong field limits. For the first method, we calculate the deflection angle up to the fifth order of approximation and show the influence of the parameter $\lambda$ (in terms of loop quantum gravity) on it. In addition, we construct expressions for the magnification, the position of the lensed images and the time delay as functions of the coefficients from the deflection angle expansion. We find that $\lambda$ increases the deflection angle. In the strong field limit, we use a logarithmic approximation to compute the deflection angle. We then write four observables, in terms of the coefficients $b_1$, $b_2$ and $u_m$, namely: the asymptotic position approached by a set of images $\theta_{\infty}$, the distance between the first image and the others $s$, the ratio between the flux of the first image and the flux of all other images $r_m$, and the time delay between two photons $\Delta T_{2,1}$. We then use the experimental data of the black hole Sagittarius $A^{\star}$ and calculate the observables and the coefficients of the logarithmic expansion. We find that the parameter $\lambda$ increases the deflection angle, the separation between the lensed images and the delay time between them. In contrast, it decreases the brightness of the first image compared to the others.Comment: 26 pages, 17 figure

Joint toxicity of cadmium and ionizing radiation on zooplankton carbon incorporation, growth and mobility

The risk of exposure to radioactive elements is seldom assessed considering mixture toxicity, potentially over- or underestimating biological and ecological effects on ecosystems. This study investigated how three end points, carbon transfer between phytoplankton and Daphnia magna, D. magna mobility and growth, responded to exposure to γ-radiation in combination with the heavy metal cadmium (Cd), using the MIXTOX approach. Observed effects were compared with mixture effects predicted by concentration addition (CA) and independent action (IA) models and with deviations for synergistic/antagonistic (S/A), dose-level (DL), and dose-ratio (DR) dependency interactions. Several patterns of response were observed depending on the end point tested. DL-dependent deviation from the IA model was observed for carbon incorporation with antagonism switching to synergism at higher doses, while the CA model indicated synergism, mainly driven by effects at high doses of γ-radiation. CA detected antagonism regarding acute immobilization, while IA predicted DR-dependency. Both CA and IA also identified antagonism for daphnid growth. In general, effects of combinations of γ-radiation and Cd seem to be antagonistic at lower doses, but synergistic at the higher range of the doses tested. Our results highlight the importance of investigating the effects of exposure to γ-radiation in a multistressor context

Thyroid hormone receptor binding to DNA and T(3)-dependent transcriptional activation are inhibited by uremic toxins

BACKGROUND: There is a substantial clinical overlap between chronic renal failure (CRF) and hypothyroidism, suggesting the presence of hypothyroidism in uremic patients. Although CRF patients have low T(3 )and T(4 )levels with normal thyroid-stimulating hormone (TSH), they show a higher prevalence of goiter and evidence for blunted tissue responsiveness to T(3 )action. However, there are no studies examining whether thyroid hormone receptors (TRs) play a role in thyroid hormone dysfunction in CRF patients. To evaluate the effects of an uremic environment on TR function, we investigated the effect of uremic plasma on TRβ1 binding to DNA as heterodimers with the retinoid X receptor alpha (RXRα) and on T(3)-dependent transcriptional activity. RESULTS: We demonstrated that uremic plasma collected prior to hemodialysis (Pre-HD) significantly reduced TRβ1-RXRα binding to DNA. Such inhibition was also observed with a vitamin D receptor (VDR) but not with a peroxisome proliferator-activated receptor gamma (PPARγ). A cell-based assay confirmed this effect where uremic pre-HD ultrafiltrate inhibited the transcriptional activation induced by T(3 )in U937 cells. In both cases, the inhibitory effects were reversed when the uremic plasma and the uremic ultrafiltrate were collected and used after hemodialysis (Post-HD). CONCLUSION: These results suggest that dialyzable toxins in uremic plasma selectively block the binding of TRβ1-RXRα to DNA and impair T(3 )transcriptional activity. These findings may explain some features of hypothyroidism and thyroid hormone resistance observed in CRF patients

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs---a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.Comment: 16 pages (4 figures) plus supporting information 8 pages (5 figures

Population structure, adaptation and divergence of the meadow spittlebug, Philaenus spumarius (Hemiptera, Aphrophoridae), revealed by genomic and morphological data

Understanding patterns of population differentiation and gene flow in insect vectors of plant diseases is crucial for the implementation of management programs of disease. We investigated morphological and genome-wide variation across the distribution range of the spittlebug Philaenus spumarius (Linnaeus, 1758) (Hemiptera, Auchenorrhyncha, Aphrophoridae), presently the most important vector of the plant pathogenic bacterium Xylella fastidiosa Wells et al., 1987 in Europe. We found genome-wide divergence between P. spumarius and a very closely related species, P. tesselatus Melichar, 1899, at RAD sequencing markers. The two species may be identified by the morphology of male genitalia but are not differentiated at mitochondrial COI, making DNA barcoding with this gene ineffective. This highlights the importance of using integrative approaches in taxonomy. We detected admixture between P. tesselatus from Morocco and P. spumarius from the Iberian Peninsula, suggesting gene-flow between them. Within P. spumarius, we found a pattern of isolation-by-distance in European populations, likely acting alongside other factors restricting gene flow. Varying levels of co-occurrence of different lineages, showing heterogeneous levels of admixture, suggest other isolation mechanisms. The transatlantic populations of North America and Azores were genetically closer to the British population analyzed here, suggesting an origin from North-Western Europe, as already detected with mitochondrial DNA. Nevertheless, these may have been produced through different colonization events. We detected SNPs with signatures of positive selection associated with environmental variables, especially related to extremes and range variation in temperature and precipitation. The population genomics approach provided new insights into the patterns of divergence, gene flow and adaptation in these spittlebugs and led to several hypotheses that require further local investigation.Peer reviewe

Observation of the decay Bc→J/ψK+K−π+B_c \rightarrow J/\psi K^+ K^- \pi^+

The decay $B_c\rightarrow J/\psi K^+ K^- \pi^+$ is observed for the first time, using proton-proton collisions collected with the LHCb detector corresponding to an integrated luminosity of 3fb$^{-1}$. A signal yield of $78\pm14$ decays is reported with a significance of 6.2 standard deviations. The ratio of the branching fraction of \B_c \rightarrow J/\psi K^+ K^- \pi^+ decays to that of $B_c \rightarrow J/\psi \pi^+$ decays is measured to be $0.53\pm 0.10\pm0.05$, where the first uncertainty is statistical and the second is systematic.Comment: 18 pages, 2 figure