scholarly journals Distribution Characteristics and Influencing Factors of Uranium Isotopes in Saline Lake Waters in the Northeast of Qaidam Basin

Minerals ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 74
Author(s):  
Chen Zhao ◽  
Pu Zhang ◽  
Xiangzhong Li ◽  
Youfeng Ning ◽  
Liangcheng Tan ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Saline Lakes ◽  
Natural Waters ◽  
Qaidam Basin ◽  
Influencing Factor ◽  
Dominant Factor ◽  
Uranium Isotopes ◽  
Distribution Characteristics ◽  
Total Dissolved Solid ◽  
Lake Waters

Four saline lakes in the northeast of Qaidam Basin were selected to explore the distribution characteristics and influencing factors of uranium isotopes in lake waters with high evaporation background. The 238U concentration and the activity ratios of 234U/238U ([234U/238U]AR) showed that there was no significant change in the same lake, but there was a certain degree of difference in the distribution between different lakes. We found that aqueous 238U concentration within a certain range increased with an increase in TDS (total dissolved solid) and salinity, as was also the case with pH. As in natural waters, the pH affects the speciation of 238U, but TDS and salinity affect the adsorption process of aqueous 238U. Further, the replenishment of water will also affect the uranium isotope concentration for lakes, but it is not the main influencing factor for saline lakes. Therefore, we suggest that pH is the dominant factor affecting changes in aqueous 238U concentration of the sampled saline lakes. The [234U/238U]AR in these saline lakes are closely related to the input water and the associated water–rock interactions involving sediments, atmosphere dust, and organic material, etc. during the evolution stage, metamorphous degree, and hydrochemistry of the saline lakes. Lake water samples collected in the maximum and minimum discharge water period, were used to evaluate the seasonal distribution characteristics of aqueous 238U, and we found that 238U concentration did not show an evident change with the seasons in these saline lakes. If the 238U concentration and [234U/238U]AR can remain consistent during a period of time, then the sediment ages and/or sedimentation rates could be determined by lake sediment and/or biogenic carbonate in future, thus allowing for the accurate reconstruction of the paleoclimate and paleoenvironment.

scholarly journals Extracting relationship between air pollution and precipitation using spatio-temporal analysis in Tehran metropolis

2019 ◽  
Vol 2 ◽  
pp. 1-7
Author(s):  
Shokouh Dareshiri ◽  
Mohammadreza Sahelgozin ◽  
Maryam Lotfian ◽  
Jens Ingensand
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Regression Model ◽  
Influencing Factors ◽  
Polynomial Regression ◽  
Human Life ◽  
Pearson Correlation ◽  
Influencing Factor ◽  
Polynomial Equation ◽  
Temporal Analysis

<p><strong>Abstract.</strong> Precipitation is one of the main stages of the water cycle, and it is required for the organisms to survive on the planet. In contrast, air pollution is a phenomenon that has greatly affected the human life nowadays. Population growth, development of factories and increasing number of fossil fuel vehicles are the most influencing factors on air pollution. In addition to understand nature of precipitation and air pollution, finding relationship between these two phenomena is necessary to make appropriate policies for reducing air pollution. Furthermore, studying trends of precipitation and air pollution in the past, is helpful to forecast the times and places with less precipitation and more air pollution for a better urban management. In this study, we tried to extract any probable relationship between these two parameters by investigating their monthly measured amounts in 22 municipal districts of Tehran in three epochs of time (2009, 2013 and 2017). Carbon Monoxide (CO) was considered as the indicator of air pollution. Results of the study show that the parameters have a significant relationship with each other. By using Pearson Correlation Coefficient and One-Way Variance (ANOVA) test, relationship between the data for each month and for each district of Tehran were studied separately. As the time has passed and the air pollution has increased, the correlation between the parameters in districts has decreased. In addition, during the cold months of the year, the correlations decrease since the fact that precipitation is not the only influencing factor on the air pollution due to the rise of air “Inversion”. Finally, the polynomial regression model of carbon monoxide based on precipitation was extracted for each of the three years. The model suggests a degree three polynomial equation. The obtained coefficients from the regression model show that the relationship between parameters was stronger in the years with more rainfalls. This can be due to the more significant impact of other influencing factors on air pollution, such as population density, wind direction, vehicles and factories in the areas or conditions with a less rainfall.</p>

scholarly journals Analysis of Revenue Incentive Dynamic Mechanism of Financial Supply Chain from the Perspective of the Internet of Things

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yue Yin
Keyword(s):  
Supply Chain ◽  
Life Cycle ◽  
Influencing Factors ◽  
Incentive Mechanism ◽  
Influencing Factor ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
The Incentive Mechanism ◽  
Relationship Factors ◽  
The Internet Of Things

With the rapid development of society, all walks of life need the support of the Internet of Things, and the financial industry is no exception. This article integrates blockchain technology with supply chain finance and builds a supply chain financial alliance architecture based on blockchain technology and an underlying model of the Ethereum blockchain system suitable for supply chain finance. We innovated new supply chain finance models and operating mechanisms and proposed business scenarios for supply chain finance from the perspective of blockchain. Taking into account the actual operation of the blockchain supply chain financial platform, the principal-agent model and the incentive theory are applied, and the supply chain financial accounts receivable model is taken as an example in the case of complete information and incomplete information. The incentive mechanism between the service provider of the chain supply chain financial platform and the core enterprise promotes the better implementation of blockchain technology and supply chain finance. Based on the existing theoretical research, this paper identifies the key influencing factors of the supply chain’s cross-enterprise incentive mechanism. These influencing factors system includes two dimensions: transaction factors and relationship factors. Transaction factors include resource dependence, uncertainty, and cooperation experience; relationship factors include corporate reputation, trust level, and relationship commitment. Based on the nature of the incentive mechanism, information sharing and revenue sharing are extracted as the measurement dimensions of the supply chain’s cross-enterprise incentive mechanism. On this basis, this article draws on the existing enterprise life cycle division method and constructs a hypothetical model of the influencing factors of the incentive mechanism in the incubation period, the growth period, and the maturity period. Relevant data was collected through questionnaires, and SPSS and AMOS software were used to perform statistical analysis, reliability analysis, exploratory factor analysis, confirmatory factor analysis, and structural equation hypothesis testing on the data. The performance of each influencing factor in different stages of the enterprise’s life cycle and the importance of each influencing factor in the same life cycle stage are obtained.

A Study on the Effectiveness of College English Blended Learning Under MOOCs Philosophy in China

2020 ◽  
pp. 247-270
Author(s):  
Zhaohui Dai
Keyword(s):  
Collaborative Learning ◽  
Blended Learning ◽  
Influencing Factors ◽  
Influencing Factor ◽  
Negative Attitude ◽  
Great Emphasis ◽  
Autonomous Learning ◽  
College English ◽  
Blended Education ◽  
Attitude And Motivation

This study investigated the effectiveness of college English blended education under MOOCs philosophy in China. The findings suggest that many features of MOOCs philosophy are evident in college English blended education and eight factors influence effectiveness. Relationships of the influencing factors demonstrate that interactions and evaluations are highly influencing factors in autonomous learning and motivations exert high influences on autonomous learning. However, students have low motivation in interaction and evaluation, for they are more extrinsically than intrinsically motivated. And also, collaborative learning is the least influencing factor in the study. To motivate the students, great emphasis should be laid on interactions and evaluation in student's autonomous learning. Moreover, students' negative attitude towards autonomous learning hampers their adaptability to college English blended learning, and, as attitude and motivation are highly related, this deserves equal attention.

scholarly journals Analysis of the Most Severe Flood Events in Turkey (1960–2014): Which Triggering Mechanisms and Aggravating Pathways Can be Identified?

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1562
Author(s):  
Gamze Koç ◽  
Theresia Petrow ◽  
Annegret Thieken
Keyword(s):  
Influencing Factor ◽  
Extreme Rainfall ◽  
Hierarchical Cluster ◽  
Dominant Factor ◽  
Economic Losses ◽  
Soil Conditions ◽  
Flood Events ◽  
Severe Flood ◽  
Catchment Size ◽  
Triggering Mechanisms

The most severe flood events in Turkey were determined for the period 1960–2014 by considering the number of fatalities, the number of affected people, and the total economic losses as indicators. The potential triggering mechanisms (i.e., atmospheric circulations and precipitation amounts) and aggravating pathways (i.e., topographic features, catchment size, land use types, and soil properties) of these 25 events were analyzed. On this basis, a new approach was developed to identify the main influencing factor per event and to provide additional information for determining the dominant flood occurrence pathways for severe floods. The events were then classified through hierarchical cluster analysis. As a result, six different clusters were found and characterized. Cluster 1 comprised flood events that were mainly influenced by drainage characteristics (e.g., catchment size and shape); Cluster 2 comprised events aggravated predominantly by urbanization; steep topography was identified to be the dominant factor for Cluster 3; extreme rainfall was determined as the main triggering factor for Cluster 4; saturated soil conditions were found to be the dominant factor for Cluster 5; and orographic effects of mountain ranges characterized Cluster 6. This study determined pathway patterns of the severe floods in Turkey with regard to their main causal or aggravating mechanisms. Accordingly, geomorphological properties are of major importance in large catchments in eastern and northeastern Anatolia. In addition, in small catchments, the share of urbanized area seems to be an important factor for the extent of flood impacts. This paper presents an outcome that could be used for future urban planning and flood risk prevention studies to understand the flood mechanisms in different regions of Turkey.

scholarly journals Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Hong Chen ◽  
Zuo-xian Gan ◽  
Yu-ting He
Keyword(s):  
Influencing Factors ◽  
Migrant Workers ◽  
Choice Model ◽  
Mode Choice ◽  
Influencing Factor ◽  
Travel Mode ◽  
Factors Affecting ◽  
Travel Choice ◽  
Travel Mode Choice ◽  
Set Up

Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all greater than 80%. Finally, the influence of different factors affecting the choice of travel mode is analyzed in detail, and the inelasticity of each factor is analyzed with the elasticity theory. Influencing factors such as age, education level, and monthly gross income have significant impact on travel choice mode for migrant workers. The elasticity values of education degree are greater than 1, indicating that it on the travel mode choice is of elasticity, while the elasticity values of gender, industry distribution, and travel purpose are less than 1, indicating that these factors on travel mode choice are of inelasticity.

scholarly journals Characterization of the reservoir-caprock of the large basement reservoir in the Dongping field, Qaidam Basin, China

2018 ◽  
Vol 36 (6) ◽  
pp. 1498-1518 ◽  
Author(s):  
Feng Ma ◽  
Wei Yang ◽  
Yongshu Zhang ◽  
Hongzhe Li ◽  
Mei Xie ◽  
...  
Keyword(s):  
Qaidam Basin ◽  
Solution Space ◽  
Source Rocks ◽  
Dominant Factor ◽  
Basement Rock ◽  
Gas Reservoirs ◽  
Large Reservoir ◽  
Heterogeneous Distribution ◽  
Gas Accumulation ◽  
The World

The basement gas reservoir in the Dongping field in the Qaidam Basin is a large reservoir that is different from other basement reservoirs around the world. The basement reservoir does not contain thick mudstone with abundant organic matter that acts as both a source rock and a caprock. The natural gas came from lateral Jurassic source rocks. The basement lithologies in wellblocks Dp3, Dp1, and Dp17 are granite, granitic gneiss, and limestone with slate, respectively, but they all provide effective reservoir space for gas accumulation. The average porosities are 3.3%, 5.2%, and 3.6%, respectively, and the average permeabilities are 0.66 mD, 0.60 mD, and 0.57 mD, respectively. Tectonic fractures are the main factor for improving the physical properties of the reservoir, and secondary solution space is the key factor for the high and stable gas production in the study area. The E1 + 2 Formation, which contains abundant anhydrite, unconformably overlies the basement rock. Some of the anhydrite was deposited as cement and filled the fractures and pores, which led to decreased porosity and to the formation of a tight caprock with a high breaking pressure for hydrocarbon accumulation. The caprock becomes thinner from the lowland to the uplift, and it is missing in wellblock Dp3, which led to the heterogeneous distribution of gas. Anhydrite-bearing caprock is the dominant factor that controls the gas accumulation in the basement rock reservoir in the Dongping field. Studying the spatial distribution of the anhydrite-bearing caprock is important to the exploration and development of basement gas reservoirs in the Qaidam Basin. This unique gas accumulation mechanism in a basement rock reservoir may inspire new ideas for exploring basement oil and gas reservoirs around the world.

scholarly journals Influencing Factors of Void closure in Skew-Rolled Steel Balls Based on the Floating-Pressure Method

Materials ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1391
Author(s):  
Chang Shu ◽  
Jitai Wang ◽  
Xuedao Shu ◽  
Duanyang Tian
Keyword(s):  
Numerical Analysis ◽  
Influencing Factors ◽  
Influencing Factor ◽  
Uniform Design ◽  
Metal Flow ◽  
Rolled Steel ◽  
Void Closure ◽  
Pressure Method ◽  
Steel Balls ◽  
Skew Rolling

Due to the instable conditions caused by the wear of rollers, macro voids inevitably occur in skew rolling steel balls. Macro voids in rolled balls greatly weakens the mechanical properties, resulting in the scrapping of about 23% of all skew rolling balls. This paper adopts the floating-pressure method (FPM) to eliminate macro voids in rolled steel balls, and mainly focuses on the investigation of the influencing factor void closure in skew-rolled balls. The research contents are listed as follows: Firstly, the mechanical model of FPM eliminating void in rolled steel balls is established, and the theoretical relationship between influencing factors of void closure is obtained. Then, the metal flow behaviors, the stress distribution and the effect of process parameters on void closure are revealed by numerical analysis. Subsequently, based on the uniform design method, the prediction equation of the required temperature and air pressure for compacting various inferior rolled balls with different diameter by FPM is deduced. Finally, the FPM experiment is carried out to verify the results of numerical analysis. The research results provide theoretical guidance for eliminating macro voids in skew-rolled steel balls.

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