200 research outputs found
Switch between critical percolation modes in city traffic dynamics
Percolation transition is widely observed in networks ranging from biology to
engineering. While much attention has been paid to network topologies, studies
rarely focus on critical percolation phenomena driven by network dynamics.
Using extensive real data, we study the critical percolation properties in city
traffic dynamics. Our results suggest that two modes of different critical
percolation behaviors are switching in the same network topology under
different traffic dynamics. One mode of city traffic (during nonrush hours or
days off) has similar critical percolation characteristics as small world
networks, while the other mode (during rush hours on working days) tends to
behave as a 2D lattice. This switching behavior can be understood by the fact
that the high-speed urban roads during nonrush hours or days off (that are
congested during rush hours) represent effective long-range connections, like
in small world networks. Our results might be useful for understanding and
improving traffic resilience.Comment: 8 pages, 4 figures, Daqing Li, Ziyou Gao and H. Eugene Stanley are
the corresponding authors ([email protected], [email protected],
[email protected]
The Effect of EMU Driver Operating Time on Professional Psychological Quality
Purpose: EMU driver operation time is an important part of the locomotive crew system. To ensure the safe, efficient and accurate operation of the EMU (Electric Multiple Unit), drivers not only need to have good physical and mental health but also must be able to work under the conditions of a scientific, reasonable and humanized organization.Design/methodology/approach: To effectively analyze the actual job of an EMU driver and to avoid impacting the normal work of the drivers, we selected some of the items from the professional mentality test project, which we had found had resulted in short test times and high test reliability and validity.Findings: With a single-driver continuous value multiplied by a time of less than two hours, there were no significant differences; multiplied by more than 4 hours, there was a significant difference in psychological quality; specifically, the multiplied career mental quality level decreased significantly. The EMU single continuous value multiplied by driving time driver should not be more than four hours to receive the full benefit. Originality/value: Based on the different operating times, this study compared the organization of different jobs in different situations. The negative impact of psychological load on EMU driver labor intensity varied
Regulation of Irregular Neuronal Firing by Autaptic Transmission
The importance of self-feedback autaptic transmission in modulating
spike-time irregularity is still poorly understood. By using a biophysical
model that incorporates autaptic coupling, we here show that self-innervation
of neurons participates in the modulation of irregular neuronal firing,
primarily by regulating the occurrence frequency of burst firing. In
particular, we find that both excitatory and electrical autapses increase the
occurrence of burst firing, thus reducing neuronal firing regularity. In
contrast, inhibitory autapses suppress burst firing and therefore tend to
improve the regularity of neuronal firing. Importantly, we show that these
findings are independent of the firing properties of individual neurons, and as
such can be observed for neurons operating in different modes. Our results
provide an insightful mechanistic understanding of how different types of
autapses shape irregular firing at the single-neuron level, and they highlight
the functional importance of autaptic self-innervation in taming and modulating
neurodynamics.Comment: 27 pages, 8 figure
Harnessing the power of the general public for crowdsourced business intelligence: a survey
International audienceCrowdsourced business intelligence (CrowdBI), which leverages the crowdsourced user-generated data to extract useful knowledge about business and create marketing intelligence to excel in the business environment, has become a surging research topic in recent years. Compared with the traditional business intelligence that is based on the firm-owned data and survey data, CrowdBI faces numerous unique issues, such as customer behavior analysis, brand tracking, and product improvement, demand forecasting and trend analysis, competitive intelligence, business popularity analysis and site recommendation, and urban commercial analysis. This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI. It also investigates novel application areas as well as the key challenges and techniques of CrowdBI. Furthermore, we make discussions about the future research directions of CrowdBI
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