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Against the backdrop of increasingly severe global climate change, the risk of rainstorm-induced waterlogging has become the primary threat to the safety of historic and cultural districts worldwide. This paper focuses on the historic and cultural districts of Beijing, China, and explores techniques and methods for identifying extreme rainstorm warnings in cultural heritage areas. Refined warning and forecasting have become important non-engineering measures to enhance these districts' waterlogging prevention control and emergency management capabilities. This paper constructs a rainstorm-induced waterlogging risk warning model tailored for Beijing's historical and cultural districts. This model system encompasses three sets of models: a building waterlogging early-warning model, a road waterlogging early-warning model, and a public evacuation early-warning model. During the construction of the model, the core concepts and determination methods of "1 h rainfall intensity water logging index" and "the waterlogging risk index in historical and cultural districts" were proposed. The construction and application of the three models take into full account the correlation between rainfall intensity and rainwater accumulation, while incorporating the characteristics of flood resilience in buildings, roads, and the society in districts. This allows for a precise grading of warning levels, leading to the formulation of corresponding warning response measures. Empirical tests have shown that the construction method proposed in this paper is reliable. The innovative results not only provide a new perspective and method for the early-warning of rainstorm-induced waterlogging, but also offer scientific support for emergency planning and response in historical and cultural districts. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the baseline levels of serotype-specific IgG antibodies to Streptococcus pneumoniae (S. pneumoniae) and assess their impact on the assessment of vaccine immunogenicity. Methods: We used a subset of serum samples from a randomized controlled trial. The blood of 584 healthy participants was collected on day 0 before and day 28 after the 23-valent pneumococcal polysaccharide vaccine (PPSV23) vaccination. Serotype-specific IgG against PPSV23-covered serotypes were measured by the World Health Organization (WHO) reference enzyme-linked immunosorbent assay (ELISA). Vaccine immunogenicity was compared using conversion rates (proportion of participants with IgG levels following immunization that are 2-fold greater than the baseline) and geometric mean fold rises (GMFRs) between the two groups, which were grouped according to pre-vaccination (baseline) IgG antibody levels. Results: Our data showed that over half of individuals have baseline IgG levels for 15 out of 23 serotypes above 1.3 µg/mL, and geometric mean concentrations (GMCs) were generally higher in the elderly group and the female group; significant differences were found in 15 serotypes for vaccine immunogenicity based on the seroconversion rate or GMFRs between individuals with baseline IgG ≥ 1.3 µg/mL and individuals with baseline IgG < 1.3 µg/mL. The seroconversion rate decreased with the increase of baseline IgG levels according to a linear regression model. Conclusions: The assessment of vaccine immunogenicity could be impacted by the fact that many adults had high baseline antibody levels. This study is registered in the Chinese Clinical Trial Registry, number NCT05298800. [ABSTRACT FROM AUTHOR]

For curbing the global climate crisis, China has set an ambitious target of peak carbon emissions by 2030. Beijing, the capital of China, has implemented a carbon reduction policy since 2012. Using the reduced and generalized forms of the Environmental Kuznets Curve (EKC), we deduce that both the cubic EKC and the genetic algorithm-based EKC have an N-shape. The first turning point of the three-order EKC occurs around 2011, demonstrating the effectiveness of the carbon reduction policy. However, the time series model predicts that Beijing will reach the second turning point around 2026, when the gross domestic product (GDP) is about CNY 5000 billion and carbon emissions will begin to increase again. Interpretable machine learning is proposed to explore the socio-economic drivers in carbon emissions, indicating that total energy consumption and GDP contribute the most. Therefore, we should accelerate the upgrading of energy consumption and adjust the industrial structure, thus facilitating Beijing to its peak carbon emissions and achieving carbon neutrality. [ABSTRACT FROM AUTHOR]

In 1972, Nobel laureate Youyou Tu's research team conducted clinical trials on the dried material of Artemisia annua L. from Beijing extracted by ether and then treated with alkali (called "ether neutral dry"), which showed that artemisinin was not the only antimalarial component contained. The biosynthesis of sesquiterpenoids in A. annua has increased exponentially after unremitting cultivation efforts, and the plant resources are now quite different from those in the 1970s. In consideration of emerging artemisinin resistance, it is of great theoretical and practical value to further study the antimalarial activity of A. annua and explore its causes. The purpose of this study is to clarify scientific questions, such as "What ingredients are synergistic with artemisinin in A. annua?", and "Are there non-artemisinin antimalarial ingredients in A. annua?". In this paper, Beijing wild A. annua was used as a control and two representative cultivation species of A. annua were selected to evaluate the antimalarial activity of the herbal medicine. The antimalarial activity of different extracts on mice was studied using the Peters' four-day suppressive test. UPLC-Q-TOF-MS was used to obtain mass spectrum data for all samples, and a UNIFI platform was used for identification. A multivariate statistical method was used to screen the different compounds with positive correlations. The antimalarial activity of different components from the ether extract and alkali treatments was determined and antimalarial components other than artemisinin were obtained. A total of 24 flavonoids, 68 sesquiterpenoids and 21 other compounds were identified. Compounds associated with differential antimalarial activity were identified. The material basis for the antimalarial activity of A. annua was clarified. The antimalarial components of A. annua include two categories: first, artemisinin and non-artemisinin antimalarial active components, of which the non-artemisinin antimalarial active components may include 5α-hydroperoxy-eudesma-4(15),11-diene; second, several antimalarial synergistic ingredients in A. annua, including arteanniun B, arteanniun B analogues and polymethoxy flavonoids. [ABSTRACT FROM AUTHOR]

Simple Summary: The Xinjiang Uyghur autonomous region is the most important area for cotton production in China, where recycling of cotton stalks (CS) as a useful resource should be encouraged. This article investigated the technical feasibility of CS as a feed and fertilizer based on the transformation of P. brevitarsis larvae. Decomposition inoculant, fermentation duration, and cattle manure ratio were considered the key factors affecting the transformation capability of P. brevitarsis larvae on CS. The research showed that 40–50% of cattle manure, 0.1% VT inoculant, and a fermentation duration of 25–30 days were the optimal technical parameters. The protein content of the larval body was as high as 52.49%, and the fat content was 11.7%. The organic matter content of frass (larvae dung-sand) was 54.8%, and the content of total nitrogen, phosphorus, and potassium (TNPK) was 9.04%, which is twice more than that of the organic fertilizer standard (NY525-2021, Beijing, China, TNPK ≥ 4.0%). The application of CS as feed (larval body) and fertilizer (larvae dung-sand) is feasible, promoting the utilization of both CS and cattle manure. Cotton stalks (CS) are a potential agricultural biomass resource. We investigated the use of CS as a feed for Proteatia brevitarsis Lewis larvae and the resulting frass (larvae dung-sand) as a fertilizer. Based on a three-factor experiment (decomposition inoculant, fermentation duration, and cattle manure ratio), the optimal parameters for the transformation of CS using P. brevitarsis larvae were determined as 40–50% of cattle manure, the use of VT inoculant and a fermentation duration of 25–30 days. Regarding the products of the transformation, the protein content of the larval body was as high as 52.49%, and the fat content was 11.7%, which is a suitable-quality insect protein source. The organic matter content of larvae dung-sand was 54.8%, and the content of total nitrogen, phosphorus, and potassium (TNPK) was 9.04%, which is twice more than that of the organic fertilizer standard (NY525-2021, Beijing, China, TNPK ≥ 4.0%), and larvae dung-sand has the potential of fertilizer application. Therefore, CS as a feed and fertilizer based on the transformation of P. brevitarsis larvae is feasible, and it is a highly efficient way to promote the utilization of both CS and cattle manure. [ABSTRACT FROM AUTHOR]

In order to ensure an ongoing and long-term breeding progress of soybean, stable sources of major quality traits across multi-environments need to be identified. Here, a panel of 135 soybean genotypes was tested in three different Chinese environments, including Beijing, Anhui, and Hainan during the 2017 and 2018 growing seasons to identify stable genotypes for cultivation under varying environmental conditions. The weighted average of absolute scores biplot (WAASB) for the best linear unbiased predictions of the genotype-environment interaction and multi-trait stability index (MTSI) were utilized to determine the stability of the soybeans for seven seed composition traits viz; protein content, oil content, and five fatty acids (palmitic, stearic, oleic, linoleic, and linolenic acids). Based on the WAASB index, the following genotypes were identified as stable genotypes for some specific traits; ZDD12828 and ZDD12832 for protein content, WDD01583 and WDD03025 for oil content, ZDD23040 for palmitic acid, WDD00033 for stearic acid, ZDD23822 for oleic acid, ZDD11183 for linoleic acid, and ZDD08489 for linolenic acid. Furthermore, based on MTSI at a selection intensity of 10%, 14 soybean genotypes were selected for their average performance and stability. Overall, the MTSI was shown to be a powerful and simple tool for identifying superior genotypes in terms of both performance and stability, hence, identifying stable soybean genotypes for future breeding programs of quality traits. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO2 emission and toxic air pollution (CO and NO2). We use column-averaged dry-air mole fractions of CO2 and CO (XCO2 and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO2 column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO2 emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO2 and XCO, and XNO2 (ΔXCO2, ΔXCO, and ΔXNO2) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO2 anomalies derived from FTS time series data provide the ΔXCO to ΔXCO2 ratio (the correlation slope). The ΔXCO to ΔXCO2 ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO2 ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO2 emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO2 over the same time period was estimated to be 15% in Beijing from the XCO2 anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO2 observation provides a 21.6% decline in NO2. The NO2 to CO2 correlation indicates a 38.2% decline in the CO2 traffic emission sector. Overall, the reduction in anthropogenic CO2 emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing. [ABSTRACT FROM AUTHOR]