Synchronization in complete networks of reaction-diffusion equations of FitzHugh-Nagumo type with nonlinear coupling

The synchronization in complete network consisting of nodes is studied in this paper. Each node is connected to all other ones by nonlinear coupling and is represented by a reaction-diffusion system of FitzHugh-Nagumo type which can be obtained by simplifying the famous Hodgkin-Huxley model. From this complete network, the sufficient condition on the coupling strength to achieve the synchronization is found. The result shows that the networks with bigger in-degrees of nodes synchronize more easily. The paper also presents the numerical simulations for theoretical result and shows a compromise between the theoretical and numerical results.

Horizon-K Farsightedness in Criminal Networks

We study the criminal networks that will emerge in the long run when criminals are neither myopic nor completely farsighted but have some limited degree of farsightedness. We adopt the horizon-K farsighted set to answer this question. We find that in criminal networks with n criminals, the set consisting of the complete network is a horizon-K farsighted set whenever the degree of farsightedness of the criminals is larger than or equal to (n−1). Moreover, the complete network is the unique horizon-(n−1) farsighted set. Hence, the predictions obtained in case of completely farsighted criminals still hold when criminals are much less farsighted.

How Equitable Are the Distributions of the Physical Activity and Accessibility Benefits of Bicycle Infrastructure?

BackgroundCycling for transport provides many health and social benefits – including physical activity and independent access to jobs, education, social opportunities, health care and other services (accessibility). However, inequalities exist for some population groups in the opportunity to reach everyday destinations, and public transport stops, by bicycle – owing in part to their greater aversion to riding in amongst motor vehicle traffic. Health equity can therefore be improved by providing separated cycleway networks that give people the opportunity to access places by bicycle using traffic-free routes. The aim of this study was to assess the health equity benefits of two bicycle infrastructure development scenarios – a single cycleway, and a complete network of cycleways – by examining the distribution of physical activity and accessibility benefits across gender, age and income groups.MethodsTravel survey data collected from residents in Sydney (Australia) were used to train a predictive transport mode choice model, which was then used to forecast the impact of the two scenarios on transport mode choice, physical activity and accessibility. Accessibility was measured using a utility-based accessibility measure derived from the mode choice model. The distribution of forecast physical activity and accessibility benefits was then calculated across gender, age and income groups.ResultsThe modelled physical activity and accessibility measures improve in both intervention scenarios. However, in the single cycleway scenario, the benefits are greatest for the male, high-income and older age groups. In the complete network scenario, the benefits are more equally distributed. Forecast increases in cycling time are largely offset by decreases in walking time – though the latter is typically low-intensity physical activity, which confers a lesser health benefit than moderate-intensity cycling.ConclusionsSeparated cycleway infrastructure can be used to improve health equity by providing greater opportunities for transport cycling in population groups more averse to riding amongst motor vehicle traffic. Disparities in the opportunity to access services and economic/social activities by bicycle – and incorporate more physical activity into everyday travel – could be addressed with connected, traffic-free cycleway networks that cater to people of all genders, ages and incomes.

A method for assessing robustness of the results of a star-shaped network meta-analysis under the unidentifiable consistency assumption

Background In a star-shaped network, pairwise comparisons link treatments with a reference treatment (often placebo or standard care), but not with each other. Thus, comparisons between non-reference treatments rely on indirect evidence, and are based on the unidentifiable consistency assumption, limiting the reliability of the results. We suggest a method of performing a sensitivity analysis through data imputation to assess the robustness of results with an unknown degree of inconsistency. Methods The method involves imputation of data for randomized controlled trials comparing non-reference treatments, to produce a complete network. The imputed data simulate a situation that would allow mixed treatment comparison, with a statistically acceptable extent of inconsistency. By comparing the agreement between the results obtained from the original star-shaped network meta-analysis and the results after incorporating the imputed data, the robustness of the results of the original star-shaped network meta-analysis can be quantified and assessed. To illustrate this method, we applied it to two real datasets and some simulated datasets. Results Applying the method to the star-shaped network formed by discarding all comparisons between non-reference treatments from a real complete network, 33% of the results from the analysis incorporating imputed data under acceptable inconsistency indicated that the treatment ranking would be different from the ranking obtained from the star-shaped network. Through a simulation study, we demonstrated the sensitivity of the results after data imputation for a star-shaped network with different levels of within- and between-study variability. An extended usability of the method was also demonstrated by another example where some head-to-head comparisons were incorporated. Conclusions Our method will serve as a practical technique to assess the reliability of results from a star-shaped network meta-analysis under the unverifiable consistency assumption.

Assimilation in networks promoting common pool resource conservation

This study investigates how assimilation in social comparison (i.e., changing behaviors in order to fit in with a group) impacts individual behaviors in the extraction of a common pool resource in different network structures (i.e., empty network, star, circle, and complete network). Our results suggest that over-exploitation is more likely to happen when there is a presence of assimilation in comparison. However, it is possible to incentivize resource conservation since the assimilation effect on individual conservation behavior highly depends on the network structures. Thus, promoting assimilation to a centralized network or networks with fewer connections is a good way to encourage resource conservation. More particularly, in a decentralized network with fewer connections (e.g., a circle network), assimilation in social comparison (e.g., feedback on their behaviors and the average behaviors of their neighbors) could help to promote resource conservation. A centralized network is useful in diffusing information and promoting assimilation in comparison by incentivizing the resource conservation of the central agents.

Finding the Network Structure of Rwandan Interbank Market

The objective of this paper was to analyze the topology of interbank network in Rwanda for policy formulation. Our main result is that interbank market network in Rwanda is described by a core- periphery model with some level of completeness of interbank market in Rwanda. As policy implication, any risk from a bank is more easily shared within the interbank market network provided that there is nearly a complete network. This is an indication that the risk of instability of the financial system in Rwanda originating from interbank market is limited.

Sidewalk extraction using aerial and street view images

A reliable, punctual, and spatially accurate dataset of sidewalks is vital for identifying where improvements can be made upon urban environment to enhance multi-modal accessibility, social cohesion, and residents' physical activity. This paper develops a synthetically new spatial procedure to extract the sidewalk by integrating the detected results from aerial and street view imagery. We first train neural networks to extract sidewalks from aerial images, and then use pre-trained models to restore occluded and missing sidewalks from street view images. By combining the results from both data sources, a complete network of sidewalks can be produced. Our case study includes four counties in the U.S., and both precision and recall reach about 0.9. The street view imagery helps restore the occluded sidewalks and largely enhances the sidewalk network's connectivity by linking 20% of dangles.

Strategies for Collecting Social Network Data

This chapter provides an overview of social network data collection strategies. We begin by outlining the primary principles of sampling and measurement design, then describing how those combine into what is labeled the “boundary specification problem” for social network research. We accompany these definitions with examples of how these elements are applied across ego, partial, and complete network designs. Next, the chapter turns to the primary ways that network data have been evaluated, highlighting both the implications of those evaluations for their use in network analyses and various strategies for how the identified limitations can be leveraged for optimal data and analytic quality. The chapter concludes by addressing some of the ethical considerations that are unique to the gathering and analyses of social network data.

TRANSFORMATION OF INTERNATIONAL INFORMATION AGENCIES

The functions of the IA system are provided by its structure. The development of the structure is associated with the emergence of new components, formats, structural links, the expansion of specialization and integration, an increase in the number of multi-format materials and the creation of interactive services. The regulator of structural ties in the system today is the presence of market relations and competition. This also determines the typology of modern information Internet agencies. Their division according to various criteria (territorial characteristics, specialization, etc.) is a necessary condition for the formation of a full-fledged system. Constant changes at different levels of this global mechanism indicate that the process is not yet complete. Network agencies continue to experiment with the format and develop the technological capabilities of their own Internet resources.