[Variation Characteristics and Source Analysis of Carbonaceous Aerosols in Winter in Jiashan].

Organic carbon (OC), elemental carbon (EC), and PM2.5 concentration data obtained from Shanxi Super Station in Jiashan County of Jiaxing City, in the winter of 2018 and 2019, were analyzed to determine the variation and potential source areas of carbonaceous aerosols. The results show that OC concentrations in the winter of 2018 and 2019 were 6.90 µg·m-3 and 5.63 µg·m-3, respectively, while EC concentrations were 2.47 µg·m-3 and 1.57 µg·m-3, respectively. The concentrations of OC and EC in the winter of 2019 were lower than those in the winter of 2018, by approximately 18.4% and 36.4%, respectively. In 2018 and 2019, the concentrations of secondary organic carbon (SOC), calculated using the minimum R-squared (MRS) method, were 1.49 µg·m-3 and 1.97 µg·m-3, respectively, and the concentrations of primary organic carbon (POC) were 5.41 µg·m-3 and 3.66 µg·m-3, respectively. The proportion of POC in OC showed a downward trend, from 96.0% in December 2018 to 64.9% in February 2020, indicating a decrease of 31.1 percentage points. SOC showed an upward trend, increasing by 31.1 percentage points from 4.0% in December 2018 to 35.1% in February 2020. It is worth noting that with the increase in PM2.5 concentration, the concentration of OC and EC increased by 474.7% and 408.2%, respectively, although the proportion of OC in PM2.5 decreased from 18.8% to 12.3%. and the percentage of OC decreased from 5.8% to 3.3%. The contribution of POC to PM2.5 did not fluctuate, and only decreased significantly above 150 µg·m-3, while the contribution of SOC to PM2.5 first decreased and then increased. In Jiaxing, the potential sources of OC and EC were mainly southern Jiangsu, southeastern Anhui, local Jiaxing, and northern Zhejiang. In the winter of the contribution concentrations of OC and EC in the main potential source regions were approximately 2 µg·m-3 and 6 µg·m-3 lower, respectively, than in winter 2018. The range of high values in the potential source regions also decreased in 2019. Before the COVID-19 epidemic, it was affected by both motor vehicle exhaust emissions and coal burning. During the Spring Festival and home isolation, due to traffic control and other reasons, motor vehicle emissions were reduced, which leaving coal burning as the main contributor.

Current Situation, Global Potential Distribution and Evolution of Six Almond Species in China.

Almond resources are widely distributed in Central Asia; its distribution has not been studied in detail. Based on the first-hand data of field investigation, climate variables and chloroplast genome data, climatic characteristics of six almond species in China were analyzed, and the global distribution and evolutionary relationship were predicted. The six almond species are concentrated between 27.99°N and 60.47°N. Different almond species have different climatic characteristics. The climate of the almond species distribution has its characteristics, and the distribution of almond species was consistent with the fatty acid cluster analysis. All the test AUC (area under curve) values of MaxEnt model were larger than 0.92. The seven continents except for Antarctica contain suitable areas for the six almond species, and such areas account for approximately 8.08% of the total area of these six continents. Based on the analysis of chloroplast DNA and the distribution characteristics, the evolutionary relationship of the six almond species was proposed, which indicated that China was not the origin of almond. In this study, the construction of a phylogenetic tree based on the chloroplast genome and the characteristics of geographical distribution were constructed. The six almond species in China may have evolved from "Unknown almond species" through two routes. The MaxEnt model for each almond species provided satisfactory results. The prediction results can provide the important reference for Prunus dulcis cultivation, wild almond species development and protection.

Triple Archives Particle Swarm Optimization.

There are two common challenges in particle swarm optimization (PSO) research, that is, selecting proper exemplars and designing an efficient learning model for a particle. In this article, we propose a triple archives PSO (TAPSO), in which particles in three archives are used to deal with the above two challenges. First, particles who have better fitness (i.e., elites) are recorded in one archive while other particles who offer faster progress, called profiteers in this article, are saved in another archive. Second, when breeding each dimension of a potential exemplar for a particle, we choose a pair of elite and profiteer from corresponding archives as two parents to generate the dimension value by ordinary genetic operators. Third, each particle carries out a specific learning model according to the fitness of its potential exemplars. Furthermore, there is no acceleration coefficient in TAPSO aiming to simplify the learning models. Finally, if an exemplar has excellent performance, it will be regarded as an outstanding exemplar and saved in the third archive, which can be reused by inferior particles aiming to enhance the exploitation and to save computing resources. The experimental results and comparisons between TAPSO and other eight PSOs on 30 benchmark functions and four real applications suggest that TAPSO attains very promising performance in different types of functions, contributing to both higher solution accuracy and faster convergence speed. Furthermore, the effectiveness and efficiency of these new proposed strategies are discussed based on extensive experiments.

Ginsenoside Rh2 enhances the antitumor immunological response of a melanoma mice model.

The treatment of malignant tumors following surgery is important in preventing relapse. Among all the post-surgery treatments, immunomodulators have demonstrated satisfactory effects on preventing recurrence according to recent studies. Ginsenoside is a compound isolated from panax ginseng, which is a famous traditional Chinese medicine. Ginsenoside aids in killing tumor cells through numerous processes, including the antitumor processes of ginsenoside Rh2 and Rg1, and also affects the inflammatory processes of the immune system. However, the role that ginsenoside serves in antitumor immunological activity remains to be elucidated. Therefore, the present study aimed to analyze the effect of ginsenoside Rh2 on the antitumor immunological response. With a melanoma mice model, ginsenoside Rh2 was demonstrated to inhibit tumor growth and improved the survival time of the mice. Ginsenoside Rh2 enhanced T-lymphocyte infiltration in the tumor and triggered cytotoxicity in spleen lymphocytes. In addition, the immunological response triggered by ginsenoside Rh2 could be transferred to other mice. In conclusion, the present study provides evidence that ginsenoside Rh2 treatment enhanced the antitumor immunological response, which may be a potential therapy for melanoma.

[Ecological cost of grain production in gully area of Loess Plateau].

Economic and ecological methods were applied to investigate the ecological cost of grain production in the gully area of Loess Plateau. In the study area in 2008, the ecological loss due to grain production was 7.2% of the total crop output, and the ecological cost reached 2.42 yuan x kg(-1) for wheat and 2.12 yuan x kg(-1) for corn. However, the per unit sales were 1.70 yuan x kg(-1) for wheat and 1.28 yuan x kg(-1) for corn. The combination of high production cost and low income affected the sustainable development of local ecological economy. The analysis of grey relationships among various factors affecting the ecological cost of grain production indicated that yield, sown area, and agricultural mechanical cost were the important factors affecting the ecological cost of grain production, while chemical fertilizer cost and organic fertilizer cost had less impact on the ecological cost of grain production. Under current production conditions, the ecological cost of grain production in the area could be reduced by raising the level of scientific and technological inputs, expanding the scale of family agricultural production, and improving the grain yield.