Accurately simulating occurrence dates of spring flowering and autumn leaf coloration of ornamental plants is of significant importance for revealing phenological response of urban vegetation to climate change and predicting the optimum timing for flower and foliage viewing. This study employed the Unified Forcing Model (UniForc) and Unified Chilling Model (UniChill) to fit the first flowering and 50% flowering dates of 20 plant species from 1979 to 2019 in Beijing Botanical Garden, and the Low Temperature and Photoperiod Multiplicative Model (TPM) to fit the first leaf coloration and 100% coloration dates of 10 plant species. The errors of optimum models in simulation and prediction were evaluated. Results show that spring flowering of ornamental plants is mainly driven by forcing temperature during ecodormancy and growth periods, but less restricted by chilling temperature during endodormancy period. First leaf coloration of ornamental plants is mainly driven by the process of leaf senescence induced by daily minimum temperature decrease, and 100% leaf coloration is mainly driven by the process of leaf senescence induced by photoperiod shortening. The average simulated root-mean square errors (RMSE) for first flowering and 50% flowering are 3.7 days and 3.2 days, respectively, and simulated RMSEs for the two spring phenophases show good interspecific synchronization. The average simulated RMSEs for first leaf coloration and 100% leaf coloration are 9.4 days and 5.6 days, respectively, but simulated RMSEs for the two autumn phenophases do not display interspecific synchronization. Simulated RMSEs of flowering dates and leaf coloration dates of various plants correlate significantly and positively with their standard deviation of interannual variations. The simulated and extrapolating RMSEs of optimum spring and autumn process-based models are very close, indicating that the models have high robustness. 

A low-resource anisotropic magnetoresistance-based vector magnetometer for space science applications is presented. The proposed vector magnetometer can detect magnetic fields in a range of ±65000 nT, has a –3 dB bandwidth of DC to 10 Hz, and a noise power spectral density of ≤0.2 nT/Hz^1/2@1 Hz. Furthermore, the device has a non-linearity error of ≤3.6%oo over the entire range and non-orthogonality error of ≤1.2%oo. The vector magnetometer was equip on a Chinese Feng-Yun meteorological satellite (FY-3E) whose orbit was a sun synchronous orbit. The first in-flight science results show that the sensor can detect transient physical signals with amplitudes of 20–60 nT.

Based on the sea surface currents data of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in March 2020 obtained from high frequency radar (HFR), the surface currents data from 907 densely distributed points were selected to analyze the characteristics of spatial-temporal variation. Harmonic analysis and some other methods were used to explore the characteristics of tidal currents. The results show that the irregular semidiurnal tide M2 is dominant in the sea area, and the shallow-water effect is significant. The dip angles of the main diurnal and semidiurnal tides are between 120° to 160°. The direction of maximum flow rate is WN-ES, which shows the trend of shore offshore flow. As the distance to the shoreline increases, the tidal current pattern coefficient and the effect of shallow water constituents coefficient gradually increase, and the offshore area in the south of the research area shows the characteristics of irregular diurnal tide. The ranges of probable maximum current velocity and measured maximum current velocity were 0.33 cm/s to 71.01 cm/s and 58.63 cm/s to 149.99 cm/s, respectively, with the upper-end values distributed in the northwest and south of the study area.

Aiming at the problem that the current power text classification methods ignore the latent semantic association between category labels and therefore lead to low classification performance, a hierarchical multi-label power text classification method is proposed. Firstly, a power multi-label text dataset is built using automatic information extraction based on power unstructured texts, and the hierarchical structural relationships between categories are constructed by leveraging relevant domain knowledge. Secondly, a text classification method HONLSTM-BERT is proposed based on hybrid embeddings of category structure and label semantics for hierarchically classifying power texts in a top-down manner. At last, experiments were made in comparison with some popular text classification methods, and the experimental results show that proposed HONLSTM-BERT method achieves superior classification accuracy, and can efficiently improve the performance of automatic text classification.

This study estimated the shadow price of two air pollutants (sulfur dioxide and nitrogen oxides) and carbon dioxide in 867 chemical firms from 2007 to 2012 using a parameterized directional distance function to measure the marginal abatement cost of pollutants. The result is as follows. 1) The average shadow prices of SO₂, NO_x and CO₂ in the sample chemical firms were 59.8 yuan/kg equivalent, 388.13 yuan/kg equivalent and 164 yuan/ton equivalent, respectively. 2) The shadow prices of the three pollutants showed an upward and fragmented trend, implying that traditional target-bound emission reductions policies during the 11th Five-Year-Plan had not been economically effective. 3) By plotting the marginal abatement cost curve (MACC) of chemical industry, we find that in order to achieve the pollution reduction targets set by the 13th Five-Year Plan, the effective environmental tax rate should be much higher than the current environmental tax rate or the average carbon price in the carbon market, which means that the current environmental tax may require some adjustment. The shadow price of nitrogen oxides is much higher than that of sulfur dioxide, therefore the tax rate of nitrogen oxides may need a certain degree of adjustment. The results can provide some reference for the future establishment of a more complete system of environmental tax.

 In order to explore spatial pattern of soil microbial biomass carbon (MBC) and its environmental driving forces in grassland surface layer (0?10 cm) and subsurface layer (10?20 cm) in the agro-pastoral transition zone in northern China, 456 soil samples (57 sample sites, two soil layers and four replicates) were selected for investigation from Inner Mongolia-Liaoning plain, Bashang on the north of Beijing, the northern foot of Yinshan Mountain and Ningxia-Shaanxi Loess Plateau. The results showed that the spatial pattern of MBC was consistent between the surface and subsurface layer, which increased with latitude and had no significant change with longitude and elevation. With the increase of degradation degree, the reduction of soil microbial biomass in the subsurface layer was smaller than that in the surface layer. The difference of soil pH between the two layers decreased with the degree of degradation. The difference in soil MBC between surface and subsurface soils was regulated by the change of soil pH. The smaller the difference in pH between the two soil layers, the smaller the difference in MBC. Climate, vegetation and soil factors could affect the spatial variation of MBC, and soil factors were the main driving forces for MBC at the regional scale. The main influencing factor of MBC was soil total carbon at surface layer, and soil total nitrogen at subsurface layer. In the context of climate change and the intensification of human activities, the results were useful for predicting the response of soil microorganisms at the regional scale and maintaining and restoring ecological functions of degraded grasslands.

Challenges in calibration of hydrological model parameters in ungauged basins were discussed, and the latest advances in regionalization method and remote sensing based method were summarized. First, the common problems in the hydrological model calibration (derivation of hydrographic parameters, construction of objective function and selection of optimization method) and their influences on the results of parameter optimization) were analyzed and leading-edge solutions were then provided. Next, fundamental principles and study progress of regionalization method were introduced, and the importance of stream gauge network density of donor catchments for the streamflow prediction was emphasized. The advance of remote sensing based hydrological model calibration method was discussed in terms of model spatial domain, model structure, satellite data source, and

calibration target. Finally, the advantages and disadvantages and the future development prospect between regionalization method and remote sensing based method were compared and analyzed, and potential practical strategies for continuous streamflow prediction in ungauged basins in China are suggested.

In order to reveal temporal variations of autumn phenology of herbaceous plants and their climatic attributions, we analyzed changing trend of the common brown-down date of Taraxacum mongolicum and simulated interannual variation of the common brown-down date using plant phenological and meteorological data at 47 phenological stations in eastern China’s temperate zone from 1992 to 2012 and statistical methods. Results show that 1) the common brown-down date of Taraxacum mongolicum was delayed at 34 stations from 1992 to 2012, of which significant delaying trends were observed at 22 stations. By contrast, the common brown-down date of Taraxacum mongolicum advanced at 13 stations, of which significant advancing trends were detected at five stations. 2) The common brown-down date of Taraxacum mongolicum at individual stations correlates mainly negative with average temperature during the growing season (the period from leaf unfolding to common browndown) but positive with relative soil moisture and daily minimum temperature in autumn. 3) Among the 30 effective optimal models at individual stations (p<0.05), the common brown-down date of Taraxacum mongolicum was influenced by relative soil moisture at 22 stations, by daily minimum temperature at 19 stations and by average temperature during the growing season at 21 stations. Moreover, simulation accuracy of the model was significantly affected by interannual variation of the common brown-down date of Taraxacum mongolicum, namely, the smaller the interannual variation of the common brown-down date at a station, the higher the simulation accuracy of the model.

The COMCOT model was used to analyze the potential hazards of the tsunami source in Manila Trench. By changing the information of the two tsunami initial fields — magnitude and source depth, the quantitative relationship between the first wave amplitude and the two is revealed when the tsunami landed in China’s coastal areas. The results show that the influence amplitude of different focal depths on the amplitude of the first wave can reach 50%. With the different magnitude of earthquake, the influence of the focal depth on the amplitude of the first wave is also different. The amplitude of the first wave of the tsunami landing basically increases with the magnitude. However, during the process of the tsunami spreading to the near shore, the tsunami wave will overlap with the reflection wave near the shore, which may cause the first wave landing amplitude to decrease abnormally. When the magnitude reach Mw 8.6, the tsunami level is 1 and some coastal areas will be threatened by tsunami.

The authors calulate chiral corrections to the decuplet-octet baryon transition axial charges through O(p³) using heavy baryon chiral perturbation theory (HBCPT). Theoretical predictions are presented. Chiral symmetry breaking, vertex correctiongs, wavefunction renormalization are included. The contributions from both the intermediate decuplet and octet baryon states are taken into account in the loops. The results show reasonably good convergence of the chiral expansion and agreement with the known experimental data.