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Is there any anomaly change of the electron density in the ionosphere before Taiwan earthquakes? The electron density on Taiwan's magnetic latitude is known to be the maximum on the earth especially during the afternoon period (Chen et al., 2000, PCE). A study of its daily variation further reveals that the electron density on Taiwan is relatively stable to reach its maximum during the afternoon period (Liu, Chen and Lin, 2003, JGR). A statistical detection of the anomaly before Taiwan earthquakes shows that an extraordinary decrease in the electron density majorly occurs post noon (Liu and Chen et al., 2001, JGR). Applying the statistical detection to the historical data finds that the probability of such a electron density anomaly is enhanced especially when the effect of magnetic storms is removed. In fact, a statistical analysis concludes that Taiwan's earthquakes of larger magnitude is more likely to experience the anomaly and the earthquakes closer to the ionosonde station has a better chance to be recognized ahead of time. These statistical results have shed light into the study of searching for earthquake precursors.
 
Major cooperative partners include the Institute of System Biology and Bioinformatics of National Central University, Taipei Cathay General Hospital, Chungli Landseed Hospital, and Taipei Medical University. Dr. Tsou also actively participates in the execution of joint research programs between National Central University and Landseed Hospital, and uses data from cohort research to explore the related factors of occurrence and disappearance of metabolism disorder syndrome together with doctors of Landseed Hospital.
 
Professor Takeshi Emura
Developing a personalized prediction formula using Cox proportional hazards model involving high-dimensional genetic factors and dynamic tumour progression status. Copulas are used to model the dependence between survival and tumour progression while a compound covariate is used for summarizing high-dimensional genetic factors. This research is developed with biostatisticians from Academia Sinica, INSERM Biostatistic (France), and Nagoya University (Japan). See the reference Emura et al. (2017 Stat Methods Med Res, doi:10.1177/0962280216688032) for details.

  Last updated: 2017-03-17

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