823 research outputs found
Randomizing world trade. II. A weighted network analysis
Based on the misleading expectation that weighted network properties always
offer a more complete description than purely topological ones, current
economic models of the International Trade Network (ITN) generally aim at
explaining local weighted properties, not local binary ones. Here we complement
our analysis of the binary projections of the ITN by considering its weighted
representations. We show that, unlike the binary case, all possible weighted
representations of the ITN (directed/undirected, aggregated/disaggregated)
cannot be traced back to local country-specific properties, which are therefore
of limited informativeness. Our two papers show that traditional macroeconomic
approaches systematically fail to capture the key properties of the ITN. In the
binary case, they do not focus on the degree sequence and hence cannot
characterize or replicate higher-order properties. In the weighted case, they
generally focus on the strength sequence, but the knowledge of the latter is
not enough in order to understand or reproduce indirect effects.Comment: See also the companion paper (Part I): arXiv:1103.1243
[physics.soc-ph], published as Phys. Rev. E 84, 046117 (2011
Fertimetro, a Principle and Device to Measure Soil Nutrient Availability for Plants by Microbial Degradation Rates on Differently-Spiked Buried Threads
A novel patented method (PCT/IB2012/001157: Squartini, Concheri, Tiozzo, University of Padova) and the corresponding application devices, suitable to measure soil fertility, are presented. The availability or deficiency of specific nutrients for crops is assessed by monitoring the kinetics of progressive weakening of cotton or silk threads due to in situ microbial activity. The method is based on a nutrient-primed incremented substrate degradation principle. Threads are buried as is or pre-impregnated with N or P solutions, and the acceleration of the degradation rate for the N-supplemented or P-supplemented thread, in comparison to the untreated thread, is proportional to the lack of the corresponding nutrient in that soil. Tests were validated on corn crops in plots receiving increasing fertilizer rates in a historical rotation that has been established since 1962. The measurement carried out in May significantly correlated with the subsequent crop yields recorded in October. The analysis allows an early, inexpensive, fast, and reproducible self-assessment at field level to improve fertilization rates. The device is envisaged as a user-friendly tool for agronomy, horticulture, and any environmental applications where organic matter cycling, soil quality, and specific nutrients excess or deficiency are critical considerations
Spatial effects in real networks: measures, null models, and applications
Spatially embedded networks are shaped by a combination of purely topological
(space-independent) and space-dependent formation rules. While it is quite easy
to artificially generate networks where the relative importance of these two
factors can be varied arbitrarily, it is much more difficult to disentangle
these two architectural effects in real networks. Here we propose a solution to
the problem by introducing global and local measures of spatial effects that,
through a comparison with adequate null models, effectively filter out the
spurious contribution of non-spatial constraints. Our filtering allows us to
consistently compare different embedded networks or different historical
snapshots of the same network. As a challenging application we analyse the
World Trade Web, whose topology is expected to depend on geographic distances
but is also strongly determined by non-spatial constraints (degree sequence or
GDP). Remarkably, we are able to detect weak but significant spatial effects
both locally and globally in the network, showing that our method succeeds in
retrieving spatial information even when non-spatial factors dominate. We
finally relate our results to the economic literature on gravity models and
trade globalization
Null Models of Economic Networks: The Case of the World Trade Web
In all empirical-network studies, the observed properties of economic
networks are informative only if compared with a well-defined null model that
can quantitatively predict the behavior of such properties in constrained
graphs. However, predictions of the available null-model methods can be derived
analytically only under assumptions (e.g., sparseness of the network) that are
unrealistic for most economic networks like the World Trade Web (WTW). In this
paper we study the evolution of the WTW using a recently-proposed family of
null network models. The method allows to analytically obtain the expected
value of any network statistic across the ensemble of networks that preserve on
average some local properties, and are otherwise fully random. We compare
expected and observed properties of the WTW in the period 1950-2000, when
either the expected number of trade partners or total country trade is kept
fixed and equal to observed quantities. We show that, in the binary WTW,
node-degree sequences are sufficient to explain higher-order network properties
such as disassortativity and clustering-degree correlation, especially in the
last part of the sample. Conversely, in the weighted WTW, the observed sequence
of total country imports and exports are not sufficient to predict higher-order
patterns of the WTW. We discuss some important implications of these findings
for international-trade models.Comment: 39 pages, 46 figures, 2 table
Reconstructing Mesoscale Network Structures
When facing the problem of reconstructing complex mesoscale network structures, it is generally believed that models encoding the nodes organization into modules must be employed. The present paper focuses on two block structures that characterize the empirical mesoscale organization of many real-world networks, i.e., the bow-tie and the core-periphery ones, with the aim of quantifying the minimal amount of topological information that needs to be enforced in order to reproduce the topological details of the former. Our analysis shows that constraining the network degree sequences is often enough to reproduce such structures, as confirmed by model selection criteria as AIC or BIC. As a byproduct, our paper enriches the toolbox for the analysis of bipartite networks, still far from being complete: both the bow-tie and the core-periphery structure, in fact, partition the networks into asymmetric blocks characterized by binary, directed connections, thus calling for the extension of a recently proposed method to randomize undirected, bipartite networks to the directed case
In vitro analysis of epithelial tolerability and anti-Candida effect of a new lactic acid-based vaginal gel formulation
INTRODUCTION. Vulvovaginal candidiasis (VVC) is the most prevalent vaginal infection in adult women. It is mainly caused by Candida albicans, and it affects 75% of healthy women at least once during their reproductive age; 5-10% of such women have recurrent episodes (RVVC), with more of 4 episodes of acute VVC per year. Symptoms of VVC include itching, burning, swelling and redness of the vaginal mucosa with white vaginal discharge. The urinary system can also be affected, with pain and burning when urinating. This condition seriously damages the well-being and the life quality of the affected women. Since Candida is a commensal fungus of the vaginal mucosa of healthy women, the main question is how the fungus can switch from harmless component of the vaginal microbiota to virulent pathogen. In this work we analyzed the capacity of lactic acid-based vaginal gel formulation Respecta® Balance Gel (RBG) to counteract C. albicans virulence after epithelial cells infection in vitro.
MATERIALS AND METHODS. For the establishment of the in vitro infection model, we used a monolayer of the A-431 vaginal epithelial cell line and two different strains of C. albicans (strain SC5314 and the bioluminescent strain gLUC59). Dose-dependent experiments were performed to test the epithelial tolerability to RBG (IHS srl, Biofarma Group) by monitoring lactate-dehydrogenase (LDH) release from damaged cells. The capacity of RGB to counteract Candida-induced epithelial damage were analysed by monitoring LDH release from cells. Fungal growth and adhesion capacity during vaginal epithelial cells infection in the presence of RGB were evaluated by quantify the Relative Luminescent Units (RLU) and CFU counts, respectively.
RESULTS. Our results show that, at dilution 1:150, RGB is well tolerated by the vaginal epithelium and consequently we used this dose for the subsequent experiments. RBG was able to significantly reduce (by 65%) C. albicans-induced damage of vaginal epithelial cells. This effect was accompanied with the capacity of RGB to significantly reduce Candida adhesion to the epithelium (adhesion reduction by 34%). Intriguingly, no inhibition of fungal growth was observed after 24h of infection in the presence of RGB in our experimental conditions.
DISCUSSION AND CONCLUSIONS. Our results show that RGB significantly reduce C. albicans-induced damage of vaginal epithelial cells. One of the mechanisms underlying this effect is the inhibition of C. albicans adhesion to the vaginal epithelial cells, which may prevent Candida from penetrating and damaging epithelial cells, hence counteract Candida virulence. Collectively our preliminary results suggest that RBG can strengthen the VVC therapy favoring the establishment of an ecosystem that prevent Candida virulence
Randomizing bipartite networks: The case of the World Trade Web
This is the final version. Available from Nature Research via the DOI in this record. Within the last fifteen years, network theory has been successfully applied both to natural sciences and to socioeconomic disciplines. In particular, bipartite networks have been recognized to provide a particularly insightful representation of many systems, ranging from mutualistic networks in ecology to trade networks in economy, whence the need of a pattern detection-oriented analysis in order to identify statistically-significant structural properties. Such an analysis rests upon the definition of suitable null models, i.e. upon the choice of the portion of network structure to be preserved while randomizing everything else. However, quite surprisingly, little work has been done so far to define null models for real bipartite networks. The aim of the present work is to fill this gap, extending a recently-proposed method to randomize monopartite networks to bipartite networks. While the proposed formalism is perfectly general, we apply our method to the binary, undirected, bipartite representation of the World Trade Web, comparing the observed values of a number of structural quantities of interest with the expected ones, calculated via our randomization procedure. Interestingly, the behavior of the World Trade Web in this new representation is strongly different from the monopartite analogue, showing highly non-trivial patterns of self-organization.GROWTHCO
Detecting early signs of the 2007-2008 crisis in the world trade
This is the final version. Available from Nature Research via the DOI in this record. Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008-2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995-2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles.GROWTHCOMSIMPO
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