ALBERT

Description: A validated hydrodynamic-biogeochemical model was applied to investigate the effects of physical forcing (i.e., river discharge, winds, and tides) on the summertime dissolved oxygen (DO) dynamics and hypoxia (DO 〈 3 mg L−1) in the Pearl River estuary (PRE), based on a suite of model sensitivity experiments. Compared with the base model run in 2006 (a wet year), the simulated hypoxic area in the moderate year (with 75% of river discharge of the base run) and the dry year scenario (with 50% of river discharge of the base run) was reduced by ~30% and ~60%, respectively. This is because under the lower river discharge levels, less particulate organic matter was delivered to the estuary that subsequently alleviated the oxygen demand at the water–sediment interface, and in the meantime, the water stratification strength was decreased, which facilitated the vertical diffusion of DO. Regarding the effect of winds, the highly varying and intermittent strong winds had a significant impact on the replenishment of bottom DO by disrupting water stratification and thus inhibiting the development of hypoxia. Sensitivity experiments showed that the hypoxic area and volume were both remarkably increased in the low wind scenario (with a bottom hypoxic zone extending from the Modaomen sub-estuary to the western shoal in Lingdingyang Bay), whereas hypoxia was almost absent in the strong wind scenario. The DO budget indicated that winds altered the bottom DO mostly by affecting the DO flux due to vertical diffusion and horizontal advection, and had a limited influence on the DO consumption processes. Moreover, the DO concentration exhibited remarkable fluctuations over the spring-neap tidal cycles due to the significant differences in vertical diffusion. The results of a tide-sensitivity experiment indicated that without tide forcing, most of the shallow areas (average water depth 〈 5 m) in the PRE experienced severe and persistent hypoxia. The tides mainly enhanced mixing in the shallow areas, which led to higher vertical diffusion and enhanced replenishment of bottom DO.

Description: Due to the uncertainties of radar target prior information in the actual scene, the waveform designed based on radar target prior information cannot meet the needs of detection and parameter estimation performance. In this paper, the optimal waveform design techniques under energy constraints for different tasks are considered. To improve the detection performance of radar systems, a novel waveform design method which can maximize the signal-to-interference-plus-noise ratio (SINR) for known and random extended targets is proposed. To improve the performance of parameter estimation, another waveform design method which can maximize the mutual information (MI) between the radar echo and the random-target spectrum response is also considered. Most of the previous waveform design researches assumed that the prior information of the target spectrum is completely known. However, in the actual scene, the real target spectrum cannot be accurately captured. To simulate this scenario, the real target spectrum was assumed to be within an uncertainty range where the upper and lower bounds are known. Then, the SINR- and MI-based maximin robust waveforms were designed, which could optimize the performance under the most unfavorable conditions. The simulation results show that the designed optimal waveforms based on these two criteria are different, which provides useful guidance for waveform energy allocation in different transmission tasks. However, under the constraint of limited energy, we also found that the performance improvement of SINR or MI in the worst case for single targets is less significant than that of multiple targets.

Description: The contradiction between increasing demand and current supply has affected the healthy development of industry. Investigating the key influence factors of industrial water use change has important practical significance for water resource management. In this study, the authors propose the vector autoregression model to analyze the dynamic influences of industrial development, technological progress, and environmental protection on industrial water use change, and take Jiangsu Province, China as a case study. Results show that each of the factors had different effects during 2001–2015, in which industrial development was the greatest contributor to the change of industrial water use and showed a positive effect in the forecast period; technological progress played a major role in reducing industrial water use, but the negative effect weakened periodically over time; environmental protection also had a positive influence in the early forecast period, and then showed a marginal effect with time. Results of this study could assist the relevant authorities to formulate appropriate industrial development planning and water saving policies, and to reasonably control the industrial water demand.

Description: Biomass reflects the state of forest management and is critical for assessing forest benefits and carbon storage. The effective crown is the region above the lower limit of the forest crown that includes the maximum vertical distribution density of branches and leaves; this component plays an important role in tree growth. Adding the effective crown to biomass equations can enhance the accuracy of the derived biomass. Six sample plots in a larch plantation (ranging in area from 0.06 ha to 0.12 ha and in number of trees from 63 to 96) at the Mengjiagang forest farm in Huanan County, Jiamusi City, Heilongjiang Province, China, were analyzed in this study. Terrestrial laser scanning (TLS) was used to obtain three-dimensional point cloud data on the trees, from which crown parameters at different heights were extracted. These parameters were used to determine the position of the effective crown. Moreover, effective crown parameters were added to biomass equations with tree height as the sole variable to improve the accuracy of the derived individual-tree biomass estimates. The results showed that the minimum crown contact height was very similar to the effective crown height, and an increase in model accuracy was apparent (with R a 2 increasing from 0.846 to 0.910 and root-mean-square error (RMSE) decreasing from 0.372 kg to 0.286 kg). The optimal model for deriving biomass included tree height, crown length from minimum contact height, crown height from minimum contact height, and crown surface area from minimum contact height. The novelty of the article is that it improves the fit of individual-tree biomass models by adding crown-related variables and investigates how the accuracy of biomass estimation can be enhanced by using remote sensing methods without obtaining diameter at breast height.

Description: With the continuous development of smart distribution networks, their observable problems have become more serious. Research on the optimal placement of the distribution phasor measurement unit (D-PMU) is an important way to improve the measurability, observability and controllability of a smart distribution network. In this paper, the optimal D-PMU placement methods and implementation technology were studied to determine the optimal D-PMU placement scheme. Considering the bus vulnerability index and the different operating states of the system, the more practical one-time optimal placement methods to ensure complete system observability was proposed. On this basis, the system's measurement redundancy and unobservable depth were considered to realize the multistage optimal D-PMU placement. The corresponding mathematical model and solution flow were given. Then the implementation technology of the methods was studied and the optimal D-PMU placement assistant decision-making software for smart distribution network was developed. Thereby, the structure and requirements of different distribution networks can be satisfied. The application analysis, functional architecture and the overall design process were given. Finally, the methods and software were analyzed by using the IEEE 33 bus system and an actual project, the Guangzhou Nansha Yuan'an Substation. The verification results showed that the method and software mentioned in this paper can provide convenient and quick operation for optimal D-PMU placement, improve the efficiency of smart distribution network planning work, and promote the theoretical application level of smart distribution network planning results.

Description: Rapid and accurate detection of driver fatigue is of great significance to improve traffic safety. In the present work, we propose the man-machine response mode (MRM) to relieve driver fatigue caused by long-term driving. In this paper, the characteristics of the complex brain network, which can effectively reflect brain activity information, were used to detect the change of driving fatigue over time. Combined with the traditional eye movement characteristics and a subjective questionnaire (SQ), the changes in driving fatigue characteristics were comprehensively analyzed. The results show that driving fatigue can be effectively delayed using the MRM. Additionally, the response equipment is low in cost and practical, so it will be practical to use in actual driving situations in the future.