[Heavy Metal Content and Risk Assessment of Sediments and Soils in the Juma River Basin].

The sediment and soil in the Juma River channel pose a risk of pollution to the downstream ecological environment of Beijing and Xiong'an New Area. To address this issue, sediments and soil samples were collected along the river from the source to the Zhangfang outlet. The samples were further divided into three types:main stream sediment (29 samples), riverbank soil (27 samples), and farmland soil (26 samples). Enrichment factor analysis and the potential ecological risk index were employed to investigate the ecological risk. The results showed that the average concentrations of Cd, Hg, Pb, Zn, and Cu in the river sediment and soil in the study area were higher than those in the Baiyangdian Lake sediment and the surface soil of Hebei Province, whereas the concentrations of As, Cr, and Ni were relatively lower. The ranking of heavy metal pollution levels from high to low were Cd > Hg > Pb > Zn > Cu > Cr > Ni > As. The comprehensive ecological risk index showed that farmland soil and riverbank soil were mainly at a slight risk, followed by a moderate risk. The potential ecological risk of the main stream sediment was mainly moderate, severe, and extremely severe, accounting for 35.5%, 24.1%, and 24.1%, respectively, and the main contributing factors of the risk were Cd and Hg. The results of multivariate statistical analysis indicated that the main pollution sources of Cd, Pb, Zn, and Cu were industrial and mining activities. Cr, Ni, and As were mainly controlled by the weathering of the parent rock, and As was also influenced by agricultural activities. Hg was controlled by composite pollution sources such as industrial and mining activities, parent rock weathering, and atmospheric dust fall. Overall, the risk of heavy metal in the soil of the research area was generally at a slight level. However, there was a significant enrichment of Cd and other heavy metal in the sediment of the Taiyu-Sigezhuang-Pengtou River. This river section should be the focus of environmental monitoring, river dredging, and governance.

A data-driven model for power system operating costs based on different types of wind power fluctuations.

The stochastic and intermittent features of wind power as well as the high percentage of wind power grid-connected significantly increase the additional operating costs of the power system. It is difficult to accurately calculate the impact of complex fluctuations in wind power on additional operating costs. To solve the above problems, a power system operating cost model adapted to various wind power fluctuation processes is established. Firstly, based on a two-layer clustering strategy, different types of wind power fluctuations are obtained. Then, a production simulation model of the power system with renewable energy is established. The production simulation model costs include thermal plant operating costs, energy storage system operating costs, positive reserve costs and negative reserve costs. With the optimization objective of minimizing the total operating cost of the power system, realistic and representative system operating parameters and cost samples are obtained for various wind power fluctuations and different wind power grid-connected scenarios. Finally, a data-driven approach based on a deep neural network algorithm is proposed to achieve precise mapping between wind energy fluctuations and the operating costs of power systems and thermal power units, and the operating costs of the power system during the four seasons with different types of wind power fluctuations can be precisely analyzed. The results demonstrate that the method proposed in this paper has high simulation accuracy for the overall simulation operating cost of the power system and the operating cost of thermal power plants. The simulation errors are 4%-18% and 3%-13%, respectively, which verified the effectiveness of the method.

[Assessment of Groundwater Contamination Risk in the Plain Area of Southern Turpan Basin].

Groundwater contamination risk assessment is an effective tool for groundwater pollution prevention and control. The evaluation system mainly includes three parts:groundwater contamination source load assessment, groundwater vulnerability assessment, and groundwater function value evaluation. Taking the plain area of southern Turpan Basin as an example, based on the survey data and land use data, point source pollution and non-point source pollution were divided to evaluate the load of groundwater pollution sources, the classical DRASTIC model was selected to evaluate the vulnerability of groundwater, and the functional value of groundwater was evaluated from the point of view of water quality and quantity. The three factors were weighted and superimposed via GIS platform to generate the risk zoning map of groundwater contamination. The results showed that the overall risk of groundwater contamination in the study area was low. The area of high-risk and relatively high-risk areas accounted for 15.5% of the total study area, which were mainly distributed in L1, L2, and L3 of the study area. L1 was mainly affected by high pollution source load and high groundwater vulnerability. L2 was mainly the result of the joint action of high groundwater function value and domestic non-point source pollution. Non-point source pollution dominated by agricultural activities and high functional value of groundwater were the main reasons for the high risk of groundwater pollution in the L3 area. The results of the groundwater contamination risk assessment serve as an important reference for decision-makers to delineate the prevention and control area of groundwater pollution.

Integrating Unified Medical Language System and Kleinberg's Burst Detection Algorithm into Research Topics of Medications for Post-Traumatic Stress Disorder.

BACKGROUND: The treatment of post-traumatic stress disorder (PTSD) has long been a challenge because the symptoms of PTSD are multifaceted. PTSD is primarily treated with psychotherapy and medication, or a combination of psychotherapy and medication. The present study was designed to analyze the literature on medications for PTSD and explore high-frequency common drugs and low-frequency burst drugs by burst detection algorithm combined with Unified Medical Language System (UMLS) and provide references for developing new drugs for PTSD. METHODS: Publications related to medications for PTSD from 2010 to 2019 were identified through PubMed, Web of Science Core Collection, and BIOSIS Previews. SemRep and SemRep semantic result processing system were performed to extract the set of drug concepts with therapeutic relationship according to the semantic relationship of UMLS. Kleinberg's burst detection algorithm was applied to calculate the burst weight index of drug concepts by a Java-based program. These concepts were sorted according to the frequency and the burst weight index. RESULTS: Four hundred and fifty-nine treatment-related drug concepts were extracted. The drug with the highest burst weight index was "Psilocybine", a hallucinogen, which was more likely to be a hotspot for the pharmacotherapy of PTSD. The highest frequency concept was "prazosin", which was more likely to be the focus of research in the medications for PTSD. CONCLUSION: The present study assessed the medication-related literature on PTSD treatment, providing a framework of burst words detection-based method, a baseline of information for future research and the new attempt for the discovery of textual knowledge. The bibliometric analysis based on the burst detection algorithm combined with UMLS has shown certain feasibility in amplifying the microscopic changes of a specific research direction in a field, it can also be used in other aspects of disease and to explore the trends of various disciplines.

Quantitative Assessment of the Effects of Oxidants on Antigen-Antibody Binding In Vitro.

Objective. We quantitatively assessed the influence of oxidants on antigen-antibody-binding activity. Methods. We used several immunological detection methods, including precipitation reactions, agglutination reactions, and enzyme immunoassays, to determine antibody activity. The oxidation-reduction potential was measured in order to determine total serum antioxidant capacity. Results. Certain concentrations of oxidants resulted in significant inhibition of antibody activity but had little influence on total serum antioxidant capacity. Conclusions. Oxidants had a significant influence on interactions between antigen and antibody, but minimal effect on the peptide of the antibody molecule.