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As one of the main components of the Earth orientation parameters, short-term prediction of the geodetic polar motion series is crucial in the field of deep-space exploration, high-precision positioning, and timing services, which require high real-time performance. Additionally, its middle- and long-term prediction is equally important in climate forecasting and geodynamics research. In this study, we propose the combined BiLSTM+ARIMA model, which is based on bidirectional long- and short-term memory (BiLSTM) and autoregression integrated moving average (ARIMA). First, ensemble empirical mode decomposition (EEMD) is performed as a filter to decompose the polar motion time series to obtain low- and high-frequency signals. The EOP14 C04 time series provided by International Earth Rotation and Reference Systems Service and decomposed by EEMD includes low-frequency signals like the long-term trend, decadal oscillation, Chandler wobble, and prograde annual wobble, along with shorter-period high-frequency signals. Second, low- and high-frequency signals are predicted using BiLSTM and ARIMA models, respectively. Finally, the low- and high-frequency signal forecast components are reconstructed to obtain geodetic polar motion predictions. In middle- and long-term polar motion prediction, the results show that the proposed model can improve the prediction accuracy by up to 42% and 17%, respectively. This demonstrated that the BiLSTM+ARIMA model can effectively improve the accuracy of polar motion prediction. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to investigate the genetic etiology of epilepsy in children, and to analyze the nature of genetic variation, the function of related genes, and the genotype-phenotype relationship. Moreover, the impact of the genetic diagnosis on prognosis and prenatal diagnosis will be discussed.Methods: We recruited 218 pediatric epilepsy patients with onset ages ranging from postnatal 5 days to 3 years during a three-year collection period. WES was conducted only for the probands to screen for possible candidate genes.Results: A total of 55 patients (25.2%) had positive genetic diagnoses. Autosomal dominant gene variants were the most common (34/55; 61.8%) and de novo variants (31/34; 91.2%) consistent with an autosomal dominant mode of inheritance. Among 64 variants identified in 35 genes, 33 (51.6%) were novel, previously unreported. Ion channel genes play critical roles in the pathogenesis of epilepsy, accounting for 58.8% (20/34) of the variants. A total of 31 (56.4%) families chose to have a prenatal diagnosis in subsequent pregnancies based on the genetic diagnosis.Conclusion: Our data suggest that applying WES in patients with epilepsy of unknown etiology can improve counseling and management. Early establishment of genetic diagnosis was necessary for counseling on recurrence risk and prenatal diagnosis. A large number of unreported variants were detected, widening the known spectrum of genetic variation related to epilepsy risk. [ABSTRACT FROM AUTHOR]