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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]

Fifteen pediatric cases of suspected Japanese encephalitis (JE) were reported in Beijing Children's Hospital during the late summer of 2013. The clinical manifestations in most cases included high fever, seizures, and abnormal magnetic resonance imaging findings. Twelve of 15 cases were laboratory-confirmed as JE cases by pathogen identification. Epidemiological investigations showed that five of the 12 laboratory-confirmed patients had an incomplete JE vaccination history. Follow-up investigations after discharge indicated that seven laboratory-confirmed JE patients without JE vaccinations had relatively poor prognoses, with an average Modified Rankin Scale (MRS) score of 2.6 when compared with the other five laboratory-confirmed, JE-vaccinated patients with an average MRS score of 0.5. The observation of pediatric JE cases among those with a history of JE vaccination warrants further attention. [ABSTRACT FROM AUTHOR]

Abstract: Shigella sonnei has become the dominant serotype causing shigellosis in Asian countries in recent years. In this study, we characterize the increasing trend of antibiotic resistance profiles and genotypes of S. sonnei isolates in the Beijing area. From January 2002 to December 2007, a total of 1108 Shigella isolates including 362 S. sonnei were recovered from diarrhea patients at the 302nd Hospital in Beijing. While the frequency of S. flexneri gradually decreased, S. sonnei gradually increased and became the dominant species. A total of 362 S. sonnei isolates were further analyzed for their antimicrobial profiles and 272 revived isolates were selected for genotyping analysis, respectively. High-level antimicrobial resistances were observed in sulfamethoxazole/trimethoprim (94.5%), ampicillin (40.3%), piperacillin (36.5%), and ceftriaxone (12.8%) with significant single- and multiple-drug resistance increase trends from 2002 to 2007 (P = 0.0000). Pulsed-field gel electrophoresis analysis indicated that 263 (96.7%) S. sonnei belonged to 1 clonal genotype A, which were further divided into A1–A6 subtypes. While subtype A2 was dominant in the early stage of study years, subtype A4 started to emerge and increased significantly in later years. Antimicrobial resistance rates are statistically different among the 6 subtypes (P = 0.0000), and A4 possessed the highest resistance rates to ampicillin (83.7%) and piperacillin (81.4%). Subtype A3 was highly clustered in inpatients compared to other subtypes (P = 0.0145). This study indicates that a clonal S. sonnei strain has become dominant in the Beijing area, and subtype A4 is responsible for increased antibiotic resistance. [Copyright &y& Elsevier]