SUMMARY We investigated the detection capability of global earthquakes immediately after the occurrence of a large earthquake. We stacked global earthquake sequences after occurrences of large earthquakes obtained from the Harvard centroid‐moment tensor catalogue, and applied a statistical model that represents an observed magnitude–frequency distribution of earthquakes to the stacked sequence. The temporal variation in model parameters, which corresponds to the detection capability of earthquakes, was estimated using a Bayesian approach. We found that the detection capability of global earthquakes is lower than normal for several hours after the occurrence of large earthquakes; for instance, the duration of lowered detection capability of global earthquakes after the occurrence of an earthquake with a magnitude of seven or larger is estimated to be approximately 12 hr.

[1] Aftershock decay is often correlated with the modified Omori's law: dN/dt = t À1 (1 + t/c) Àp , where dN/dt is the occurrence rate of aftershocks with magnitudes greater than a lower cutoff m, t is time since a mainshock, t and c are characteristic times, and p is an exponent. Extending this approach, we derive two possibilities: (1) c is a constant independent of m and t scales with m and (2) c scales with m and t is a constant independent of m. These two are tested by using aftershock sequences of four relatively recent and large earthquakes in Japan. We first determine for each sequence the threshold magnitude above which all aftershocks are completely recorded and use only events above this magnitude. Then, visual inspection of the decay curves and statistical analysis shows that the second possibility is the better approximation for our sequences. This means that the power law decay of smaller aftershocks starts after larger times from the mainshock. We find a close association of our second result with a solution obtained for a damage mechanics model of aftershock decay. The time delays associated with aftershocks, according to the second possibility, can be understood as the times needed to nucleate microcracks (aftershocks). Our result supports the idea that the c value is a real consequence of aftershock dynamics associated with damage evolution.

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TiO2/CH3NH3PbI3-based photovoltaic devices were fabricated by a spin-coating method using a mixture solution of niobium(V) ethoxide, and the effects of niobium (Nb) addition to TiO2 layers were investigated. The lattice distance and energy gap of the TiO2 were almost same after Nb addition. The elemental mapping and sheet resistance measurements indicated a wide distribution of Nb and Ti, and a decrease in sheet resistance by Nb addition. The external quantum efficiency and internal quantum efficiency increased by Nb addition to compact TiO2 and mesoporous TiO2 layers, which resulted in an increase in the current density and conversion efficiency of the cell.

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[1] We study the correlation between the phase of the moon and the occurrences of acoustic emissions (AEs) monitored at the Underground Research Laboratory in Canada. On 9 December 1997, a significant increase of AEs began and this activity decayed with time day by day. During the period of the decay, we observed that the activity often increased. Most of these increases corresponded with moments of new or full moon. We investigate whether the increase of AEs is correlated with the moments of new or full moon using a statistical method. We consider two models concerned with the daily occurrence rate of AEs. In the first model, the existence of the correlation is not assumed. In the second model, the existence is assumed. Using AIC (Akaike Information Criterion), it is shown that the second model is a significantly better fit to the observed time series of AEs.

We propose a method to estimate the probability of earthquake growth to a catastrophic one immediately after observing its initiation, for practical usage in an earthquake early warning system. This method is essentially an application of the conditional probability theory, where the magnitude‐frequency relation plays a crucial role. We apply it to the Nankai trough region, Japan, where a catastrophic earthquake is expected in the near future. Based on the historical catalogue, we estimate the probability density of magnitude using a Bayesian approach. We then estimate the probability of earthquake growth to a catastrophic one. If the observed earthquake magnitude reaches 6.5, the estimated probability that the final magnitude exceeds 7.5 is 25–41%. According to previous studies, the time taken for the magnitude to increase from 6.5 to 7.5 is approximately 10–15 seconds. Our method is highly beneficial in that it enables an earlier alarm to be issued.