Analogues of the Ramanujan--Mordell Theorem

The Ramanujan--Mordell Theorem for sums of an even number of squares is extended to other quadratic forms and quadratic polynomials

Allocation of control and data channels for Large-Scale Wireless Sensor Networks

Both IEEE 802.15.4 and 802.15.4a standards allow for dynamic channel allocation and use of multiple channels available at their physical layers but its MAC protocols are designed only for single channel. Also, sensor's transceivers such as CC2420 provide multiple channels and as shown in [1], [2] and [3] channel switch latency of CC2420 transceiver is just about 200$\mu$s. In order to enhance both energy efficiency and to shorten end to end delay, we propose, in this report, a spectrum-efficient frequency allocation schemes that are able to statically assign control channels and dynamically reuse data channels for Personal Area Networks (PANs) inside a Large-Scale WSN based on UWB technology

Facilitating innovation diffusion in social networks using dynamic norms

Dynamic norms have recently emerged as a powerful method to encourage individuals to adopt an innovation by highlighting a growing trend in its uptake. However, there have been no concrete attempts to understand how this individual-level mechanism might shape the collective population behavior. Here, we develop a framework to examine this by encapsulating dynamic norms within a game-theoretic mathematical model for innovation diffusion. Specifically, we extend a network coordination game by incorporating a probabilistic mechanism where an individual adopts the action with growing popularity, instead of the standard best-response update rule; the probability of such an event captures the population’s “sensitivity” to dynamic norms. Theoretical analysis reveals that sensitivity to dynamic norms is key to facilitating social diffusion. Small increases in sensitivity reduces the advantage of the innovation over status quo or the number of initial innovators required to unlock diffusion, while a sufficiently large sensitivity alone guarantees diffusion

SUSTAINABILITYAND GROWTH OFONLINE KNOWLEDGE COMMUNITIES: EXAMINING THE IMPORTANCE OFPERCEIVED COMMUNITYSUPPORTAND PERCEIVED LEADER SUPPORT

Voluntary behaviors (i.e., knowledge contribution and word of mouth) are important to the sustainability and growth of online knowledge communities. Although previous studies have identified various factors leading to knowledge contribution and related behaviors, the underlying psychological processes have rarely been examined. In particular, previous studies have not examined how characteristics of online knowledge communities influence voluntary behaviors through support perception. This study aims to fill the gap in the literature by developing and testing a model to explain voluntary behaviors in online knowledge communities. To develop the research model, we drew on theories of justice, organizational support, and citizenship behavior to explain the influence of characteristics of online knowledge communities on individuals\u27 voluntary behaviors through their perceptions of support from the community and the leader. The research model was tested on survey data collected from 214 online knowledge community users. The results largely supported our model. In particular, we found that pro-sharing norm and information need fulfillment affect perceived community support. Perceived recognition from leader and perceived co-presence of leader affect perceived leader support. Additionally, perceived community support was found to be important in shaping knowledge contribution and word of mouth. Perceived leader support was found to influence individuals\u27 knowledge contribution behavior. Theoretical and Practical implications are discussed

The integrin reconstruction act

Recreating integrin activation in vitro resolves several long-running controversies

Simulating infrastructure networks in the Yangtze River Delta (China) using generative urban network models

This paper explores the urban-geographical potential of simulation approaches combining spatial and topological processes. Drawing on Vértes et al.'s (2012) economical clustering model, we propose a generative network model integrating factors captured in traditional spatial models (e.g., gravity models) and more recently developed topological models (e.g., actor-oriented stochastic models) into a single framework. In our urban network-implementation of the generative network model, it is assumed that the emergence of inter-city linkages can be approximated through probabilistic processes that speak to a series of contradictory forces. Our exploratory study focuses on the outline of the infrastructure networks connecting prefecture-level cities in the highly urbanized Yangtze River Delta (China). Possible hampering factors in the emergence of these networks include distance and administrative boundaries, while stimulating factors include a measure of city size (population, gross domestic product) and a topological rule stating that the formation of connections between cities sharing nearest neighbors is more likely (i.e., a transitive effect). Based on our results, two wider implications of our research are discussed: (1) it confirms the potential of the proposed method in urban network simulation in that the inclusion of a topological factor alongside geographical factors generates an urban network that better approximates the observed network; (2) it allows exploring the differential extent to which driving forces influence the structure of different urban networks. For instance, in the Yangtze River Delta, transitivity plays a less important role in the Internet-network formation; GDP and boundaries more strongly affect the rail network; and distance decay effects play a more prominent role in the road network

The Effects of Urban Polycentricity on Particulate Matter Emissions From Vehicles: Evidence From 102 Chinese Cities

This article analyzes the impact of the level of urban polycentricity (UP) on particulate matter emissions from vehicles (PMV) across 102 prefecture-level cities in China between 2011 and 2015. We adopt a spatial panel modeling approach to our measures of UP and PMV, controlling for (possible) intervening effects such as population density and economic output. We observe an inverted U-shaped relationship between both measures: When UP is low, an increase in polycentricity is associated with higher levels of PMV; however, when UP reaches a certain threshold, the increase in polycentricity is associated with a reduction in PMV. We find a similar relationship between economic output and PMV and demonstrate how the effects of population density on PMV consist of two opposite processes that likely offset each other. Nonetheless, jointly, population density and UP have a significant effect on PMV. We use our results to discuss policy implications and identify avenues for further research

Light anti-nuclei production in pp collisions at s\sqrt{s}=7 and 14 TeV

A dynamically constrained coalescence model based on the phase space quantization and classical limit method was proposed to investigate the production of light nuclei (anti-nuclei) in non-single diffractive (NSD) pp collisions at $\sqrt{s}$=7 and 14 TeV. This calculation was based on the final hadronic state in the PYTHIA and PACIAE model simulations, the event sample consisted of 1.2$\times 10^8$ events in both simulations. The PACIAE model calculated $\bar D$ yield of 6.247$\times 10^{-5}$ in NSD pp collisions at $\sqrt{s}$=7 TeV is well comparing with the ALICE rough datum of 5.456$\times 10^{-5}$. It indicated the reliability of proposed method in some extent. The yield, transverse momentum distribution, and rapidity distribution of the $\bar D$, $^3{\bar{He}}$, and $_{\bar\Lambda} ^3{\bar H}$ in NSD pp collisions at $\sqrt{s}$=7 and 14 TeV were predicted by PACIAE and PYTHIA model simulations. The yield resulted from PACIAE model simulations is larger than the one from PYTHIA model. This might reflect the role played by the parton and hadron rescatterings.Comment: 5 pages, 2 figure

Evolution of Social Power in Social Networks with Dynamic Topology

The recently proposed DeGroot-Friedkin model describes the dynamical evolution of individual social power in a social network that holds opinion discussions on a sequence of different issues. This paper revisits that model, and uses nonlinear contraction analysis, among other tools, to establish several novel results. First, we show that for a social network with constant topology, each individual's social power converges to its equilibrium value exponentially fast, whereas previous results only concluded asymptotic convergence. Second, when the network topology is dynamic (i.e., the relative interaction matrix may change between any two successive issues), we show that each individual exponentially forgets its initial social power. Specifically, individual social power is dependent only on the dynamic network topology, and initial (or perceived) social power is forgotten as a result of sequential opinion discussion. Last, we provide an explicit upper bound on an individual's social power as the number of issues discussed tends to infinity; this bound depends only on the network topology. Simulations are provided to illustrate our results.The work of Mengbin Ye, Brian D. O. Anderson, and Changbin Yu was supported by the Australian Research Council under Grant DP-130103610 and Grant DP-160104500, by 111-Project D17019, by NSFC Projects 61385702 and 61761136005, and by Data61-CSIRO. The work of Mengbin Ye was supported by an Australian Government Research Training Program Scholarship. The work of Ji Liu and Tamer Bas¸ar was supported by the Office of Naval Research MURI Grant N00014-16-1-2710, and by NSF under Grant CCF 11-11342. Recommended by Associate Editor C. M. Kellett