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We investigate temporal variations of the polarization anomaly of surface waves (Rayleigh and Love) relative to an isotropic medium, before and after the 2008 June 13, Iwate-Miyagi Nairiku earthquake (Mw = 6.9) in Japan, using passive image interferometry. We use continuous data records of 20 high-sensitivity three-component seismic stations (National Institute for Earth Sciences and Disaster Resilience--NIED Hi-net) from mid-2007 to the end of 2009. We compute cross-correlations of ambient seismic noise between each pair of stations, in the frequency range of 0.08-0.22 Hz. The temporal variations of the surface wave polarization show slow and weak variations due to seasonal changes to which rapid and strong variations are superposed at the time of the earthquake, and more surprisingly, also a month and a half before the earthquake. Strong changes in the polarization of surface waves might be related to changes in the distribution of crack orientation affecting seismic anisotropy. [ABSTRACT FROM AUTHOR]

This article deals with unemployment situation in two distinct social contexts, the metropolitan regions of Sao Paulo, Brazil and Tokyo, Japan. Empirical data come from two sample surveys, conducted in both metropolis, and based upon a comparative research design.

A recent work by Kimura et al. (Earth Planets Space 71:27, 2019. 10.1186/s40623-019-1006-x) (hereafter referred to as K19) claims to provide the first observational constraints on the prompt elastogravity signals (PEGS) induced by an earthquake. To make their claim, the authors argue that the observations shown in Vallée et al. (Science 358:1164–1168, 2017. 10.1126/science.aao0746) (hereafter referred to as V17) are spurious and their modeling inaccurate. Here we show that K19's claim is invalid because it is based on flawed data processing. In fact, K19's analysis involves an incomplete correction of the instrument response of broadband seismic sensors, which essentially dismisses low-frequency components of the data that are critical for the detection of intrinsically low-frequency signals such as PEGS. As a direct consequence, signals are much more difficult to observe than in V17, where the low part of the signal spectrum is carefully taken into account. This deficient data processing also explains why the signal amplitude reported by K19 after stacking data from multiple stations is lower than the individual signals reported by V17. Moreover, failing to take appropriate measures of data quality control, K19 used signals from low-quality sensors to call into question the signals detected by high-quality sensors. Finally, K19 use an inadequate simulation approach to model PEGS, in which the important effect of the ground acceleration induced by gravity changes is ignored. In summary, K19 do not show any viable arguments to question the observations and modeling of PEGS presented in V17. [ABSTRACT FROM AUTHOR]