Consuming transgenic goats' milk containing the antimicrobial protein lysozyme helps resolve diarrhea in young pigs.

Childhood diarrhea is a significant problem in many developing countries and E. coli is a main causative agent of diarrhea in young children. Lysozyme is an antimicrobial protein highly expressed in human milk, but not ruminant milk, and is thought to help protect breastfeeding children against diarrheal diseases. We hypothesized that consumption of milk from transgenic goats which produce human lysozyme (hLZ-milk) in their milk would accelerate recovery from bacterial-induced diarrhea. Young pigs were used as a model for children and infected with enterotoxigenic E. coli. Once clinical signs of diarrhea developed, pigs were fed hLZ-milk or non-transgenic control goat milk three times a day for two days. Clinical observations and complete blood counts (CBC) were performed. Animals were euthanized and samples collected to assess differences in histology, cytokine expression and bacterial translocation into the mesenteric lymph node. Pigs consuming hLZ-milk recovered from clinical signs of infection faster than pigs consuming control milk, with significantly improved fecal consistency (p = 0.0190) and activity level (p = 0.0350). The CBC analysis showed circulating monocytes (p = 0.0413), neutrophils (p = 0.0219), and lymphocytes (p = 0.0222) returned faster to pre-infection proportions in hLZ-milk fed pigs, while control-fed pigs had significantly higher hematocrit (p = 0.027), indicating continuing dehydration. In the ileum, pigs fed hLZ-milk had significantly lower expression of pro-inflammatory cytokine IL-8 (p = 0.0271), longer intestinal villi (p<0.0001), deeper crypts (p = 0.0053), and a thinner lamina propria (p = 0.0004). These data demonstrate that consumption of hLZ-milk helped pigs recover from infection faster, making hLZ-milk an effective treatment of E. coli-induced diarrhea

How Damage Diversification Can Reduce Systemic Risk

We consider the problem of risk diversification in complex networks. Nodes represent e.g. financial actors, whereas weighted links represent e.g. financial obligations (credits/debts). Each node has a risk to fail because of losses resulting from defaulting neighbors, which may lead to large failure cascades. Classical risk diversification strategies usually neglect network effects and therefore suggest that risk can be reduced if possible losses (i.e., exposures) are split among many neighbors (exposure diversification, ED). But from a complex networks perspective diversification implies higher connectivity of the system as a whole which can also lead to increasing failure risk of a node. To cope with this, we propose a different strategy (damage diversification, DD), i.e. the diversification of losses that are imposed on neighboring nodes as opposed to losses incurred by the node itself. Here, we quantify the potential of DD to reduce systemic risk in comparison to ED. For this, we develop a branching process approximation that we generalize to weighted networks with (almost) arbitrary degree and weight distributions. This allows us to identify systemically relevant nodes in a network even if their directed weights differ strongly. On the macro level, we provide an analytical expression for the average cascade size, to quantify systemic risk. Furthermore, on the meso level we calculate failure probabilities of nodes conditional on their system relevance

Filtering of complex systems using overlapping tree networks

We introduce a technique that is capable to filter out information from complex systems, by mapping them to networks, and extracting a subgraph with the strongest links. This idea is based on the Minimum Spanning Tree, and it can be applied to sets of graphs that have as links different sets of interactions among the system's elements, which are described as network nodes. It can also be applied to correlation-based graphs, where the links are weighted and represent the correlation strength between all pairs of nodes. We applied this method to the European scientific collaboration network, which is composed of all the projects supported by the European Framework Program FP6, and also to the correlation-based network of the 100 highest capitalized stocks traded in the NYSE. For both cases we identified meaningful structures, such as a strongly interconnected community of countries that play important role in the collaboration network, and clusters of stocks belonging to different sectors of economic activity, which gives significant information about the investigated systems.Comment: 6 pages, 4 figure

City of Vancouver EV Infrastructure Strategy Report

The role of the local government in supporting the growth and maintenance of a strong plug‐in electric vehicle market in Vancouver is evaluated in this report. This report identifies areas of action in which a local government, such as Vancouver, can impact their region based on a thorough understanding of the current plug‐in vehicle market, international demonstration projects, and research efforts. Specifically, workplace and public charging is needed to reinforce and fulfill the gaps from home‐based charging in dense urban regions. Local government can encourage investments in workplace and public charging by providing clear regional guidelines for installers and customers, providing appropriate incentives to businesses, allowing for an innovative marketplace in the vehicle charging industry, and collaborating with the regional utility to identify specific opportunities for optimization and encouragement of utility rates and vehicle‐grid interactions

Worldwide spreading of economic crisis

We model the spreading of a crisis by constructing a global economic network and applying the Susceptible-Infected-Recovered (SIR) epidemic model with a variable probability of infection. The probability of infection depends on the strength of economic relations between the pair of countries, and the strength of the target country. It is expected that a crisis which originates in a large country, such as the USA, has the potential to spread globally, like the recent crisis. Surprisingly we show that also countries with much lower GDP, such as Belgium, are able to initiate a global crisis. Using the {\it k}-shell decomposition method to quantify the spreading power (of a node), we obtain a measure of ``centrality'' as a spreader of each country in the economic network. We thus rank the different countries according to the shell they belong to, and find the 12 most central countries. These countries are the most likely to spread a crisis globally. Of these 12 only six are large economies, while the other six are medium/small ones, a result that could not have been otherwise anticipated. Furthermore, we use our model to predict the crisis spreading potential of countries belonging to different shells according to the crisis magnitude.Comment: 13 pages, 4 figures and Supplementary Materia

A k-shell decomposition method for weighted networks

We present a generalized method for calculating the k-shell structure of weighted networks. The method takes into account both the weight and the degree of a network, in such a way that in the absence of weights we resume the shell structure obtained by the classic k-shell decomposition. In the presence of weights, we show that the method is able to partition the network in a more refined way, without the need of any arbitrary threshold on the weight values. Furthermore, by simulating spreading processes using the susceptible-infectious-recovered model in four different weighted real-world networks, we show that the weighted k-shell decomposition method ranks the nodes more accurately, by placing nodes with higher spreading potential into shells closer to the core. In addition, we demonstrate our new method on a real economic network and show that the core calculated using the weighted k-shell method is more meaningful from an economic perspective when compared with the unweighted one.Comment: 17 pages, 6 figure

The Swiss Board Directors Network in 2009

We study the networks formed by the directors of the most important Swiss boards and the boards themselves for the year 2009. The networks are obtained by projection from the original bipartite graph. We highlight a number of important statistical features of those networks such as degree distribution, weight distribution, and several centrality measures as well as their interrelationships. While similar statistics were already known for other board systems, and are comparable here, we have extended the study with a careful investigation of director and board centrality, a k-core analysis, and a simulation of the speed of information propagation and its relationships with the topological aspects of the network such as clustering and link weight and betweenness. The overall picture that emerges is one in which the topological structure of the Swiss board and director networks has evolved in such a way that special actors and links between actors play a fundamental role in the flow of information among distant parts of the network. This is shown in particular by the centrality measures and by the simulation of a simple epidemic process on the directors network.Comment: Submitted to The European Physical Journal

«Smart City» in Socio-Political Projection (The Case of Barcelona)

This article reveals the process of becoming a “smart city” based on the materials of Barcelona. The socio-political aspects of the use of “smart city” technologies in the information and communication era are revealed.The authors use of the system method made it possible to study the technologies of the “smart city” in aggregate, and the use of the comparative method made it possible to establish the specifics of the development of Barcelona during the tenure of Mayor Xavier Trias and Ada Colau. The authors draw attention to the reasons for the recognition of the capital of Catalonia as the most high-tech city in the world in 2015. It is emphasized that Barcelona has made a rapid breakthrough in a relatively short period of time, turning into a post-industrial city. It is noted that the driver of Barcelona’s transformation was the holding of the XXV Summer Olympic Games in 1992, which essentially changed the appearance of the city.The authors point to the additional opportunities in city management that the information and communication revolution led to and the speed of the Internet penetration rate. It is emphasized that information and communication technologies led to the transformation of a rigidly vertical bureaucratic system of exercising power and set the vector of its transition to a horizontal (network model) based on the effects of high technologies.It is noted that the modern model of exercising power in Barcelona presupposes the active involvement of citizens in the processes of city management, based on the use of technological platforms that simplify coworking processes.As a result of the study, the authors come to the conclusion that the contemporary paradigm of the “smart city” involves the involvement of citizens as active participants in decisionmaking and planning. Attention is focused on the formation of two models of urban governance in Barcelona, differing in the dynamics of the exercise of power and the prevalence of tendencies from “top to bottom” (mayors of the city of K. Trias) and from “bottom to top” (mayor of the city A. Colau). The authors emphasize that modern Barcelona is not only a flagship of technological development, but also a city with democratic traditions and a high level of humancentered orientation

The association of fat and other macronutrients with breast cancer: a case-control study from Greece.

The Greek diet is characterized by a high total fat but low saturated fat intake. In a hospital-based case-control study of female breast cancer conducted in Athens (1989-91), 820 patients with confirmed cancer of the breast were compared with 795 orthopaedic patient controls and 753 hospital visitor controls, matched to the cases by age and interviewer. Diet was ascertained through a semiquantitative food frequency questionnaire; macronutrient intakes were estimated from the nutrient content of a selected typical portion size for each specified food item, summed for all items. Logistic regression was used to analyse the data, controlling for demographic and reproductive risk factors for breast cancer as well as for total energy intake and mutual confounding influences among nutrients. There was no significant or suggestive association of total protein, total fat, categories of fat or total carbohydrates with breast cancer risk. Thus, the mutually adjusted relative risk per quintile and (in parenthesis) 95% confidence interval were: for protein, 1.06 (0.94-1.20); saturated fat, 0.99 (0.89-1.11); monounsaturated fat, 0.97 (0.88-1.07), polyunsaturated fat, 1.05 (0.97-1.13); and total carbohydrates, 1.03 (0.94-1.12). In alternative analytical approaches only total protein appeared to be positively associated to the occurrence of breast cancer with some consistency, but the results were far from statistically significant. These findings do not support a role for fat or other energy-generating nutrients in the aetiology of breast cancer

Explosive Percolation in the Human Protein Homology Network

We study the explosive character of the percolation transition in a real-world network. We show that the emergence of a spanning cluster in the Human Protein Homology Network (H-PHN) exhibits similar features to an Achlioptas-type process and is markedly different from regular random percolation. The underlying mechanism of this transition can be described by slow-growing clusters that remain isolated until the later stages of the process, when the addition of a small number of links leads to the rapid interconnection of these modules into a giant cluster. Our results indicate that the evolutionary-based process that shapes the topology of the H-PHN through duplication-divergence events may occur in sudden steps, similarly to what is seen in first-order phase transitions.Comment: 13 pages, 6 figure