The earthquake tendency consultations in China, which have been carried out by the China Earthquake Administration for more than 40 yr, are really forward prediction of earthquakes. The results, experiences, and data accumulation are valuable for seismic researches. In this article, the annual, monthly, and weekly predictions produced by the regular earthquake tendency consultations and the rapid postearthquake tendency prediction derived from the irregular ones are presented systematically. In the regular predictions, the areas where earthquakes tend to occur are identified by specific space–time windows. To evaluate the efficiency of the predictions, we apply the R-score method to all the medium-to-short-term efforts. The R-score has been used as a routine tool to test annual predictions in China, in which the hit rate and the percentage of spatial alarms over the whole territory are taken into consideration. Results show that the annual R-scores, during the period of 1990–2020, increased gradually, with the average of 0.293. The examples in 2018 indicate that a considerable proportion of earthquakes with the Ms 5.0 and above were detected by the annual prediction; some earthquakes were detected by the monthly prediction, whereas just only a few earthquakes could be detected by the weekly prediction. The corresponding R-scores are 0.46, 0.11, and 0.002, decreasing obviously with reduction of the prediction time windows, and the smallest one, which is very close to zero, may suggest the minimum time scale for an effective earthquake prediction. We also evaluated efficiency of the irregular predictions by analyzing the practices of 29 Ms≥5.0 earthquakes since January 2019 and found that it is highly possible to do rapid postearthquake tendency prediction in China.
Background: Hepatocellular carcinoma (HCC) is a common malignant cancer. Metastasis plays a critical role in tumor progression, and vascular invasion is considered one of the most crucial factors for HCC metastasis. However, comprehensive analysis focusing on competitive endogenous RNA (ceRNA) and immune infiltration in the vascular invasion of HCC is lacking.Methods: The gene expression profiles of 321 samples, including 210 primary HCC cases and 111 HCC cases with vascular invasion, were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma project, and used in identifying significant differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs). The RNAs associated with vascular invasion were used in constructing a ceRNA network. A multigene-based risk signature was constructed using the least absolute shrinkage and selection operator algorithm. We detected the fractions of 28 immune cell types in HCC through single-sample gene set enrichment analysis (ssGSEA). Finally, the relationship between the ceRNA network and immune cells was determined through correlation analysis and used in clarifying the potential mechanism involved in vascular invasion.Results: Overall, 413 DElncRNAs, 27 DEmiRNAs, and 397 DEmRNAs were recognized in HCC. A specific ceRNA network based on the interaction among 3 lncRNA–miRNA pairs and 24 miRNA–mRNA pairs were established. A ceRNA-based prognostic signature was constructed and used in dividing samples into high- and low-risk subgroups. The signature showed significant efficacy; its 3- and 5-year areas under the receiver operating characteristic curves were 0.712 and 0.653, respectively. ceRNA and ssGSEA integration analysis demonstrated that PART1 (p = 0, R = −0.33) and CDK5R2 (p = 0.01, R = −0.15) were negatively correlated to natural killer cells.Conclusion: This study demonstrated that vascular invasion in HCC might be related to PART1, and its role in regulating CDK5R2 and NK cells. A nomogram was developed to predict the prognosis of patients with HCC and demonstrated the value of the ceRNA network and tumor-infiltrating immune cells value in improving personalized management.
Groundwater radon concentrations can reflect the changes of crustal stress and strain. Scholars and scientific institutions have also recorded groundwater radon precursor anomalies before earthquakes. Therefore, groundwater radon monitoring is an effective means of predicting seismic activities. However, the variation of radon concentrations within groundwater is not only affected by structural factors, but also by environmental factors, such as air pressure, temperature, and rainfall. This causes difficulty in identifying the possible precursor anomalies. Therefore, the EMD-LSTM model is proposed to identify the radon anomalies. This study investigated the time series data of groundwater radon from well #32 located in Sichuan province. Three models (including the LSTM (Long Short-Term Memory) model with auxiliary data, the EMD-LSTM (Empirical Mode Decomposition Long Short-Term Memory) model with auxiliary data, and the EMD-LSTM model without auxiliary data) were developed in order to predict groundwater radon variations. The results indicated that the prediction accuracy of the EMD-LSTM model was much higher than that of the LSTM model, and the EMD-LSTM model without auxiliary data also can obtain an ideal prediction result. Furthermore, the different durations of seismic activities T (T = ±10, ±30, ±50, and ±100) were also investigated by comparing the identification results. The identification rate of the precursor anomalies was the highest when T = ±30. The EMD-LSTM model identified five possible radon anomalies among the seven selected earthquakes. Taking well #32 as an example, we provided a promising method, that was the EMD-LSTM model, to detect the groundwater radon anomalies. It also suggested that the EMD-LSTM model can be used to identify the possible precursor anomalies within future studies.
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