Real-Time Tsunami Prediction System Using DONET

We constructed a real-time tsunami prediction system using the Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET). This system predicts the arrival time of a tsunami, the maximum tsunami height, and the inundation area around coastal target points by extracting the proper fault models from 1,506 models based on the principle of tsunami amplification. Since DONET2, installed in the Nankai earthquake rupture zone, was constructed in 2016, it has been used in addition to DONET1 installed in the Tonankai earthquake rupture zone; we revised the system using both DONET1 and DONET2 to improve the accuracy of tsunami prediction. We introduced a few methods to improve the prediction accuracy. One is the selection of proper fault models from the entire set of models considering the estimated direction of the hypocenter using seismic and tsunami data. Another is the dynamic selection of the proper DONET observatories: only DONET observatories located between the prediction point and tsunami source are used for prediction. Last is preparation for the linked occurrence of double tsunamis with a time-lag. We describe the real-time tsunami prediction system using DONET and its implementation for the Shikoku area

Development of a Practical Evaluation Method for Tsunami Debris and Its Accumulation

Tsunami-related fires may occur in the inundation area during a huge tsunami disaster, and woody debris produced by the tsunami can cause the fires to spread. To establish a practical method for evaluating tsunami-related fire predictions, we previously developed a method for evaluating the tsunami debris thickness distribution that uses tsunami computation results and static parameters for tsunami numerical analysis. We then used this evaluation method to successfully reproduce the tsunami debris accumulation trend. We then developed an empirical building fragility function that relates the production of debris not only to inundation depth but also to the topographic gradient and the proportion of robust buildings. Using these empirical evaluation models, along with conventional tsunami numerical analysis data, we carried out a practical tsunami debris prediction for Owase City, Mie Prefecture, a potential disaster area for a Nankai Trough mega-earthquake. This prediction analysis method can reveal hazards which go undetected by a conventional tsunami inundation analysis. These results indicate that it is insufficient to characterize the tsunami hazard by inundation area and inundation depth alone when predicting the hazard of a huge tsunami; moreover, more practically, it is necessary to predict the hazard based on the effect of tsunami debris

Development of a Practical Evaluation Method for Tsunami Debris and Its Accumulation

Tsunami-related fires may occur in the inundation area during a huge tsunami disaster, and woody debris produced by the tsunami can cause the fires to spread. To establish a practical method for evaluating tsunami-related fire predictions, we previously developed a method for evaluating the tsunami debris thickness distribution that uses tsunami computation results and static parameters for tsunami numerical analysis. We then used this evaluation method to successfully reproduce the tsunami debris accumulation trend. We then developed an empirical building fragility function that relates the production of debris not only to inundation depth but also to the topographic gradient and the proportion of robust buildings. Using these empirical evaluation models, along with conventional tsunami numerical analysis data, we carried out a practical tsunami debris prediction for Owase City, Mie Prefecture, a potential disaster area for a Nankai Trough mega-earthquake. This prediction analysis method can reveal hazards which go undetected by a conventional tsunami inundation analysis. These results indicate that it is insufficient to characterize the tsunami hazard by inundation area and inundation depth alone when predicting the hazard of a huge tsunami; moreover, more practically, it is necessary to predict the hazard based on the effect of tsunami debris

NAS Parallel Benchmark Results on ADENART

This paper reports NAS Parallel Benchmark results on parallel machine ADENART, which has been developed through collaboration between Kyoto University and Matsushita Electric Industrial Co.[KKT]. The results show that ADENART has comparable or two/three times power of Y-MP/1, though it is very compact as a deskside machine and consumes only about several KWhs of electric power. 1 Introduction Parallel machine ADENART had been developed until 1990, through collaboration between Kyoto University and Matsushita Electric Industrial Co.. Its original idea was already proposed by the first author in the beginning of 1980's under the academic name ADENA(changed from previous ADINA). A dozen of systems had been produced to support CAD research in the company and academic research in some Japanese universities. Our university uses one of them for computational physics and mathematics, developing of parallel algorithms and software development. On the last summer, we tried to test NAS Parallel ..

Highly sensitive detection of a <i>HER2</i> 12-base pair duplicated insertion mutation in lung cancer using the Eprobe-PCR method

<div><p>Somatic mutation in human epidermal growth factor receptor-related 2 gene (<i>HER2</i>) is one of the driver mutations in lung cancer. <i>HER2</i> mutations are found in about 2% of lung adenocarcinomas (ADCs). Previous reports have been based mainly on diagnostic screening by Sanger sequencing or next-generation sequencing (NGS); however, these methods are time-consuming and complicated. We developed a rapid, simple, sensitive mutation detection assay for detecting <i>HER2</i> 12 base pair-duplicated insertion mutation based on the Eprobe-mediated PCR method (Eprobe-PCR) and validated the sensitivity of this assay system for clinical diagnostics. We examined 635 tumor samples and analyzed <i>HER2</i> mutations using the Eprobe-PCR method, NGS, and Sanger sequencing. In a serial dilution study, the Eprobe-PCR was able to detect mutant plasmid DNA when its concentration was reduced to 0.1% by mixing with wild-type DNA. We also confirmed amplification of the mutated plasmid DNA with only 10 copies per reaction. In ADCs, Eprobe-PCR detected the <i>HER2</i> mutation in 2.02% (9/446), while Sanger sequencing detected it in 1.57% (7/446). Eprobe-PCR was able to detect the mutation in two samples that were undetectable by Sanger sequencing. All non-ADC samples were wild-type. There were no discrepancies between frozen and formalin-fixed paraffin-embedded tissues in the nine samples. <i>HER2</i> mutations detected by NGS data validated the high sensitivity of the method. Therefore, this new technique can lead to precise molecular-targeted therapies.</p></div

Comparison of Eprobe-PCR and Sanger methods.

<p>The left half of Fig 3 shows the amplification curves of Eprobe-PCR, and the right half shows the electrogram of Sanger sequencing. “4Peaks” was used to view and edit the sequence trace files (<a href="http://nucleobytes.com/4peaks/" target="_blank">http://nucleobytes.com/4peaks/</a>).</p

Sensitivity of Eprobe-PCR for detecting <i>HER2</i> 12-bp duplicated insertion.

<p>MT: <i>HER2</i> 12-bp duplicated insertion mutation type, WT: <i>HER2</i> wild type, NTC: No template control (diluted water). (a) Evaluation of mutated genome amplification. The blue line indicates MT only plasmid DNA at 10,000 copies per reaction, red: 1,000, green: 100, purple: 10, light blue: 1, orange: WT plasmid DNA, black: NTC. The light blue line shows no amplification. It overlaps with WT and NTC lines. (b) Sensitivity of 12-bp duplicated insertion detection in heterogenetic conditions. The blue line indicates MT only plasmid DNA at 10,000 copies per reaction, red: 1,000, green: 100, purple: 10, light blue: 1, orange: WT plasmid DNA, black: NTC (diluted water). The total copy number for each was adjusted to 10,000 copies per reaction. The light blue line shows no amplification. It overlaps WT and NTC lines. (c) Cp (crossing point) values of two experiments (a) and (b) were calculated by the second derivative maximum method in the LightCycler480. The data were then transferred to Microsoft Excel (Microsoft, Redmond, WA, USA) and Cp values were evaluated.</p

Primer sets and Eprobe design for <i>HER2</i> mutation detection.

<p>Schematic diagram of primers for the detection of the <i>HER2</i> 12-bp duplicated insertion by Eprobe-PCR. The orange box is the duplicated insertion. The forward primer for detection of the mutant-type allele contains the full sequence of <i>HER2</i> across the region known to be a frequent insertion site. The green bar is the Eprobe. The 3’ end-filled circle Eprobe shows the blocker that prevents primer extension during PCR.</p