Modelling of urban traffic noise using a systems approach

AbstractIntroductionExposure to noise stress during early life may permanently affect the structure and function of the central nervous system. The aim of this study was to evaluate the effects of prenatal exposure to urban traffic noise on the spatial learning and memory of the rats' offspring and the expression of glucocorticoid receptors (GRs) in their hippocampi.MethodsThree g\roups of pregnant rats were exposed to recorded urban traffic noise for 1, 2 or 4 h/day during the last week of pregnancy. At the age of 45 days, their male offspring were introduced to the Morris water maze (MWM) for assessment of spatial learning and memory. The corticosterone levels were measured in the offspring's sera by radioimmunoassay, and the relative expression of glucocorticoid and mineralocorticoid receptors (MRs) in their hippocampi was evaluated via RT-PCR.ResultsFacing urban traffic noise for 2 and 4 h/day during the third trimester of pregnancy caused the offspring to spend more time and to travel a larger distance than the controls to find the target platform. Analogously, these two groups were inferior to their control counterparts in the probe test. Also, prenatal noise stress elevated the corticosterone concentration in the sera of the rats' offspring and dose-dependently decreased the relative expression of the mRNA of both GRs and MRs in their hippocampi.ConclusionsUrban traffic noise exposure during the last trimester of pregnancy impairs spatial learning and memory of rat offspring and reduces GRs and MRs gene expression in the hippocampus.

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A cellular automaton for urban traffic noise

The Journal of the Acoustical Society of America ◽

10.1121/1.2935960 ◽

2008 ◽

Vol 123 (5) ◽

pp. 3924-3924

Author(s):

Erik Salomons

Keyword(s):

Cellular Automaton ◽

Traffic Noise ◽

Urban Traffic ◽

Urban Traffic Noise

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Urban Traffic Noise Maps under 3D Complex Building Environments on a Supercomputer

Journal of Advanced Transportation ◽

10.1155/2018/7031418 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 5

Author(s):

Ming Cai ◽

Yifan Yao ◽

Haibo Wang

Keyword(s):

Parallel Algorithm ◽

Traffic Noise ◽

Computing Time ◽

Urban Traffic ◽

Shielding Effect ◽

Time Dynamic ◽

Suppression Effect ◽

Complex Building ◽

Urban Traffic Noise ◽

Noise Map

The complexity of the 3D buildings and road networks gives the simulation of urban noise difficulty and significance. To solve the problem of computing complexity, a systematic methodology for computing urban traffic noise maps under 3D complex building environments is presented on a supercomputer. A parallel algorithm focused on controlling the compute nodes of the supercomputer is designed. Moreover, a rendering method is provided to visualize the noise map. In addition, a strategy for obtaining a real-time dynamic noise map is elaborated. Two efficiency experiments are implemented. One experiment involves comparing the expansibility of the parallel algorithm with various numbers of compute nodes and various computing scales to determine the expansibility. With an increase in the number of compute nodes, the computing time increases linearly, and an increased computing scale leads to computing efficiency increases. The other experiment is a comparison of the computing speed between a supercomputer and a normal computer; the computing node of Tianhe-2 is found to be six times faster than that of a normal computer. Finally, the traffic noise suppression effect of buildings is analyzed. It is found that the building groups have obvious shielding effect on traffic noise.

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