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The incidence of brain diseases has increased yearly, threatening human life and health seriously. The Electroencephalogram (EEG) has been playing an important role in clinical practice for diagnosing brain diseases. However, due to the interference of noise and the limitations of manual observation, experts need to spend a lot of time and energy on EEG interpretation, and also is affected by subjective factors, which is prone to misjudgment. Therefore, the establishment of EEG-assisted diagnosis system is of great significance for the clinical diagnosis of brain diseases. With the application of artificial intelligence in EEG auxiliary system, researchers have proposed a series of EEG automatic analysis and anomaly detection algorithms based on deep learning. However, the existing algorithms still have some shortcomings such as inadequate extraction of potential spatio-temporal features in EEG signals. In this paper, the method based on GATs-LSTM is proposed. The comparative analysis of the final experiment shows that, It has demonstrated superior performance on the benchmark dataset with sensitive and specificity as 99.21%, 99.73% and 94.15%, 95.67%. The proposed work shows great results on the benchmark datasets and a big potential for clinics as a support system with medical experts monitoring the patients. [ABSTRACT FROM AUTHOR]

In this study, Pediastrum has been observed in the Anjihaihe Formation (E2+3a) shale through organic petrology studies. Additionally, analyses of total organic carbon and rock pyrolysis (Rock–Eval) revealed that the E2+3a shale predominantly comprises oil-bearing type I and II kerogen at a low-maturity stage. The organic matter (OM) in the shale is primarily contributed by Pediastrum, indicating excellent original hydrocarbon generation potential. Hydrous pyrolysis was conducted on a Pediastrum-rich sample, and the liquid product was analyzed using gas chromatography–mass spectrometry (GC–MS) of the saturated fraction. It was discovered that n-C27 might serve as a characteristic biomarker indicating Pediastrum development. During warm and humid climatic conditions, rivers transport significant amounts of freshwater and terrigenous organic matter (OM) into the lake, leading to an increase in felsic minerals and a relative decrease in carbonate minerals. This, in turn, reduces water salinity, resulting in a relative increase in the abundance of Pediastrum. Conversely, during earlier hot and arid climatic conditions, the input of terrigenous OM decreases, and evaporation leads to increased salinity. When the water’s salinity exceeds the “salinity critical point”, the Pediastrum content decreases. Finally, this study presents a formation and evolution model for the E2+3a shale in the Junggar Basin.Graphical Abstract: In this study, Pediastrum has been observed in the Anjihaihe Formation (E2+3a) shale through organic petrology studies. Additionally, analyses of total organic carbon and rock pyrolysis (Rock–Eval) revealed that the E2+3a shale predominantly comprises oil-bearing type I and II kerogen at a low-maturity stage. The organic matter (OM) in the shale is primarily contributed by Pediastrum, indicating excellent original hydrocarbon generation potential. Hydrous pyrolysis was conducted on a Pediastrum-rich sample, and the liquid product was analyzed using gas chromatography–mass spectrometry (GC–MS) of the saturated fraction. It was discovered that n-C27 might serve as a characteristic biomarker indicating Pediastrum development. During warm and humid climatic conditions, rivers transport significant amounts of freshwater and terrigenous organic matter (OM) into the lake, leading to an increase in felsic minerals and a relative decrease in carbonate minerals. This, in turn, reduces water salinity, resulting in a relative increase in the abundance of Pediastrum. Conversely, during earlier hot and arid climatic conditions, the input of terrigenous OM decreases, and evaporation leads to increased salinity. When the water’s salinity exceeds the “salinity critical point”, the Pediastrum content decreases. Finally, this study presents a formation and evolution model for the E2+3a shale in the Junggar Basin. [ABSTRACT FROM AUTHOR]