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More accurate multivariate load forecasting is conducive to integrated energy system planning optimization and economic operation. In this paper, based on the consideration of exogenous factors such as weather, endogenous factors are added into the prediction, and a short-term prediction model for integrated energy multivariate load based on endo-exogenous uncertainty is established using fine-tuned transfer learning. The LSTM pre-training model is first initially established using genetic algorithm and exogenous factors such as weather. Then the exogenous uncertainty of the pre-training model and the knowledge of endogenous uncertainty in the target model are combined using fine-tuned transfer learning to continuously optimize the basic parameters of the prediction model to obtain the final multivariate load prediction model. The performance of the four models is comprehensively evaluated after the historical load validation of the integrated energy system in Beijing, China. Compared with the traditional LSTM multivariate load forecasting model, the MAPE of the proposed model in this paper is reduced by 21.03 %, 13.00 %, and 24.39 % for electricity, heat, and cooling load forecasting, respectively. • The coupling mechanism between multiple energy sources of the integrated energy system is analyzed. • An endogenous-exogenous uncertainty method is proposed to extract the dynamic coupling relationship between multiple loads. • An endogenous-exogenous uncertainty-based GA-LSTM multivariate load prediction model is developed. • Optimizing model parameters using fine-tuned migration learning to deepen the impact of endo-exogenous uncertainty. [ABSTRACT FROM AUTHOR]

In order to establish a regional database on natural radioactivity, a series of measurements of 713 atmospheric aerosol samples collected on filters over a two-year period (2018–2019) in center of Beijing, northeastern China have been performed to analyze 7Be and 210Pb activity concentrations. The mean activity concentrations of 7Be and 210Pb were found to be 7.10 ± 2.44 mBq m−3 and 2.93 ± 1.52 mBq m−3, respectively. Both the radionuclides exhibited strong seasonal variations, with maximum concentration of 7Be occurring in the spring and that of 210Pb in the winter. The concentration of both the radionuclides was minimum in the rainy summer. Higher 7Be concentration in the spring was mainly caused by the stratosphere to troposphere exchange. Higher 210Pb concentration during winter was maybe attributed to the combustion processes in heating systems and the ingression of continental air masses resulted from winds originating from northwest. The dependence of the activity concentrations of 7Be and 210Pb with meteorological parameters such as rainfall, temperature, and humidity was studied through linear correlation analysis. Statistically significant negative correlations were observed between 7Be and 210Pb activity concentrations with rainfall, respectively, which suggested that the removal mechanisms of these two radionuclides were similar. Lead-210 showed statistically significant correlations with temperature, humidity and PM 10. A comparison of the data obtained in the present study for Beijing with the northern hemisphere literature values of 7Be and 210Pb in the atmospheric aerosols showed that the values were smaller than the ones observed in the present study. Overall, the study provides an improved understanding of the temporal variability and correlation of 7Be and 210Pb concentrations in the atmosphere in center of Beijing, northeastern China. • Regional database on7Be and 210Pb activity concentrations in the atmospheric aerosols in center of Beijing was established. • Rainfall is suggested as the major removal means for 7Be and 210Pb from the atmosphere. • Causal factors for the temporal variability of7Be and 210Pb activity concentrations were identified. • Correlations of temperature, relative humidity and PM 10 with 7Be and 210Pb were explored. • Correlation between 7Be and 210Pb activity concentrations was studied. [ABSTRACT FROM AUTHOR]

To explore the effect of mindfulness intervention on the psychological resilience and professional identity of nursing undergraduates during the epidemic and its mechanisms, and to provide strong evidence for improving the mental health status and professional identity of nursing undergraduates. Methods One hundred and eight nursing students were randomly selected from a pre-survey conducted at a university in Beijing from April 25-30, 2021, of whom 52 were placed in the intervention group for a combined online and offline mindfulness intervention, whereas 56 were placed in the control group and received no intervention. The Resilience Style Questionnaire (RSQ) and Professional Identity for Nurse Students Questionnaire (PINSQ) were used to assess the levels of psychological resilience and professional identity of members in both groups before intervention, 1 week after intervention, and 3 months after intervention (followup). SAS 9.4 software was used to evaluate the intervention effect using generalized estimating equations, and the Process test was used to analyze the mediating effect of psychological resilience. Results After intervention, the psychological resilience of the intervention group was higher than that of the control group (P < 0.05); at follow -up, there was no statistically significant difference in psychological resilience between the intervention group and the control group (P > 0.05). The psychological resilience of students in the intervention group increased after intervention and at follow -up compared to before intervention (P < 0.05), but decreased at follow-up compared to after intervention (P < 0.05); there was no change in the level of psychological resilience of control students at each time point (P > 0.05). After intervention, the professional identity score of the intervention group was higher than that of the control group (P < 0.05), and at follow-up time, the professional identity of the intervention group was higher than that of the control group (P < 0.01). The increase in professional identity at each time point in the intervention group was statistically significant (P < 0.05), while there was no statistically significant difference in professional identity in the control group at each time points (P > 0.05). Mindfulness intervention affected professional identity by affecting psychological resilience levels, with a mediation effect ratio of 23.67%. Conclusions A mindfulness intervention could effectively improve the psychological resilience and professional identity levels of nursing undergraduates during the epidemic, providing a basis for subsequent psychological interventions and research. [ABSTRACT FROM AUTHOR]

Soil conservation and water retention are important metrics for designating key ecological functional areas and ecological red line (ERL) areas. However, research on the quantitative identification of dominant environmental factors in different ecological red line areas remains relatively inadequate, which is unfavorable for the zone-based management of ecological functional areas. This paper presents a case study of Beijing's ERL areas. In order to objectively reflect the ecological characteristics of ERL areas in Beijing, which is mainly dominated by mountainous areas, the application of remote sensing data at a high resolution is important for the improvement of model calculation and spatial heterogeneity. Based on multi-source remote sensing data, meteorological and soil observations as well as soil erosion and water yield were calculated using the revised universal soil loss equation (RUSLE) and integrated valuation of ecosystem services and tradeoffs (InVEST) model. Combining the influencing factors, including slope, precipitation, land use type, vegetation coverage, geomorphological type, and elevation, a quantitative attribution analysis was performed on soil erosion and water yield in Beijing's ERL areas using the geographical detector. The power of each influencing factor and their interaction factors in explaining the spatial distribution of soil erosion or water yield varied significantly among different ERL areas. Vegetation coverage was the dominant factor affecting soil erosion in Beijing's ERL areas, explaining greater than 30% of its spatial heterogeneity. Land use type could explain the spatial heterogeneity of water yield more than 60%. In addition, the combination of vegetation coverage and slope was found to significantly enhance the spatial distribution of soil erosion (>55% in various ERL areas). The superposition of land use type and slope explained greater than 70% of the spatial distribution for water yield in ERL areas. The geographical detector results indicated that the high soil erosion risk areas and high water yield areas varied significantly among different ERL areas. Thus, in efforts to enhance ERL protection, focus should be placed on the spatial heterogeneity of soil erosion and water yield in different ERL areas. [ABSTRACT FROM AUTHOR]