The volcanic rocks of the Xiong'er Group are situated in the southern margin of the North China Craton(NCC).Research on the Xiong er Group is important to understand the tectonic evolution of the NCC and the Columbia supercontinent during the Paleoproterozoic.In this study,to constrain the age of the Xiong'er volcanic rocks and identify its tectonic environment,we report zircon LA-ICP-MS data with Hf isotope,whole-rock major and trace element compositions and Sr-Nd-Pb-Hf isotopes of the volcanic rocks of the Xiong'er Group.The Xiong'er volcanic rocks mainly consist of basaltic andesite,andesite.dacite and rhyolite,with minor basalt.Our new sets of data combined with those from previous studies indicate that Xiong'er volcanism should have lasted from 1827 Ma to 1746 Ma as the major phase of the volcanism.These volcanics have extremely low MgO.Cr and Ni contents,are enriched in LREEs and LILEs but depleted in HFSEs(Nb,Ta,and Ti),similar to arc-related volcanic rocks.They are characterized by negative zircon ε_(Hf)_(t) values of-17.4 to 8.8,whole-rock initial ~(87)Sr/~(86)Sr values of 0.7023 to 0.7177 andε_(Nd)(t) values of-10.9 to 6.4.and Pb isotopes(~(206)Pb/~(204)Pb =14.366-16.431,~(207)Pb/~(204)Pb =15.106-15.371,~(208)Pb/~(204)Pb= 32.455-37.422).The available elemental and Sr-Nd-Pb-Hf isotope data suggest that the Xiong'er volcanic rocks were sourced from a mantle contaminated by continental crust.The volcanic rocks of the Xiong'er Group might have been generated by high-degree partial melting of a lithospheric mantle that was originally modified by oceanic subduction in the Archean.Thus,we suggest that the subduction-modified lithospheric mantle occurred in an extensional setting during the breakup of the Columbia supercontinent in the Late Paleoproterozoic,rather than in an arc setting. 相似文献
Rockburst is a common dynamic geological hazard, severely restricting the development and utilization of underground space and resources. As the depth of excavation and mining increases, rockburst tends to occur frequently. Hence, it is necessary to carry out a study on rockburst prediction. Due to the nonlinear relationship between rockburst and its influencing factors, artificial intelligence was introduced. However, the collected data were typically imbalanced. Single algorithms trained by such data have low recognition for minority classes. In order to handle the problem, this paper employed stacking technique of ensemble learning to establish rockburst prediction models. In total, 246 sets of data were collected. In the preprocessing stage, three data mining techniques including principal component analysis, local outlier factor and expectation maximization algorithm were used for dimension reduction, outlier detection and outlier substitution, respectively. Then, the pre-processed data were split into a training set (75%) and a test set (25%) with stratified sampling. Based on the four classical single intelligent algorithms, namely k-nearest neighbors (KNN), support vector machine (SVM), deep neural network (DNN) and recurrent neural network (RNN), four ensemble models (KNN–RNN, SVM–RNN, DNN–RNN and KNN–SVM–DNN–RNN) were built by stacking technique of ensemble learning. The prediction performance of eight models was evaluated, and the differences between single models and ensemble models were analyzed. Additionally, a sensitivity analysis was conducted, revealing the importance of input variables on the models. Finally, the impact of class imbalance on the prediction accuracy and fitting effect of models was quantitatively discussed. The results showed that stacking technique of ensemble learning provides a new and promising way for rockburst prediction, which exhibits unique advantages especially when using imbalanced data.
There is a well-known seesaw pattern of precipitation between the tropical western North Pacific(WNP) and the Yangtze River basin(YRB) during summer. This study identified that this out-of-phase relationship experiences a subseasonal change;that is, the relationship is strong during early summer but much weaker during mid-summer. We investigated the large-scale circulation anomalies responsible for the YRB rainfall anomalies on the subseasonal timescale. It was found that the YRB rainfall is mainly affected by the tropical circulation anomalies during early summer, i.e., the anticyclonic or cyclonic anomaly over the subtropical WNP associated with the precipitation anomalies over the tropical WNP. During mid-summer, the YRB rainfall is mainly affected by the extratropical circulation anomalies in both the lower and upper troposphere. In the lower troposphere, the northeasterly anomaly north of the YRB favors heavier rainfall over the YRB by intensifying the meridional gradient of the equivalent potential temperature over the YRB. In the upper troposphere, the meridional displacement of the Asian westerly jet and the zonally oriented teleconnection pattern along the jet also affect the YRB rainfall. The subseasonal change in the WNP–YRB precipitation relationship illustrated by this study has important implications for the subseasonalto-seasonal forecasting of the YRB rainfall. 相似文献
