Autler-Townes effect in a strongly driven electromagnetically induced transparency resonance

In this paper we study the nonlinear behavior of an electromagnetically induced transparency EIT resonance subject to a coherent driving field. The EIT is associated with a three-level system where two hyperfine levels within an electronic ground state are coupled to a common excited state level by a coupling field and a probe field. In addition there is an radio-frequency rf field driving a hyperfine transition within the ground state. The paper contrasts two different situations. In one case the rf-driven transition shares a common level with the probed transition and in the second case it shares a common level with the coupled transition. In both cases the EIT resonance is split into a doublet and the characteristics of the EIT doublet are determined by the strength and frequency of the rf-driving field. The doublet splitting originates from the rf-field induced dynamic Stark effect and has close analogy with the Autler-Townes effect observed in three-level pump-probe spectroscopy study. The situation changes when the rf field is strong and the two cases are very different. One is analogous to two three-level systems with EIT resonance associated with each. The other corresponds to a doubly driven three-level system with rf-field-induced electromagnetically induced absorption resonance. The two situations are modeled using numerical solutions of the relevant equation of motion of density matrix. In addition a physical account of their behaviors is given in terms of a dressed state picture

Complex PM2.5 Pollution and Hospital Admission for Respiratory Diseases over Big Data in Cloud Environment

With the establishment of China’s national air quality monitoring network, large amounts of monitoring data are available for different kinds of users. How to process and use this big data is a tough problem for users: most users have limited computing power, and new data are collected at every moment. Cloud computing may be an efficient and low-cost way to solve this problem. This paper investigates a problem of a complex system: the impact of PM2.5 on hospitalization for respiratory diseases. A change-point detection method based on grey relation analysis was used to solve this problem. Daily air pollution monitoring data and patient data were used in this study. Our results showed that (1) PM2.5 pollution showed a positive correlation on hospital admission for respiratory disease; (2) most patients went to hospital 2 days after PM2.5 pollution events; and (3) male, children, and old people were significantly affected by PM2.5 pollution. Our study is of great significance to help the government formulate suitable policies to reduce the damage caused by PM2.5 pollution and help hospitals allocate medical resources efficiently

Research on the Effect of Urbanization on China’s Carbon Emission Efficiency

Improvements in carbon emission efficiency are crucial to China’s economic growth; carbon emission reduction and urbanization are two of the focuses of research on carbon emission efficiency. This paper selects 2000–2015 panel data from 30 provinces in China, evaluates the carbon emission efficiency of each province using the DEA method and, based on the STIRPAT expansion form, empirically looks at the effect of urbanization on carbon emission efficiency. The results show that, during the chosen time frame, not only did the carbon emission efficiency of China’s provinces show an upward trend but the carbon emission efficiency of the Eastern, Central and Western regions differed markedly, with the highest efficiency in the Eastern region, the second highest in the Central region and the lowest in the Western region. After controlling for population density, economic development level, energy intensity and industrial structure, urbanization we determine that urbanization can indeed improve carbon emission efficiency, although there are regional differences. Urbanization is conducive to improvements in carbon emission efficiency in both the Central and Western regions but the promotion effect of the Western region is stronger. The effect in the Eastern region is not significant. Based on the conclusions above, this paper puts forward policy recommendations that promote both China’s lower carbon efficiency and future environmental protection

How Does Foreign Equity Right Impact Manufacturing Enterprise Innovation Behaviors? Mediation Test Based on Technology Introduction

The impacts of FDI (foreign direct investment) on the innovation of Chinese local enterprises have always been the focus of attention, but few studies have explored the impacts of foreign shareholding on enterprise innovation behaviors through the micro level. Based on the survey data regarding the manufacturing sector of China enterprises conducted by the World Bank in 2012, this paper conducts an empirical study on the relationship between foreign shareholding and enterprise innovation behaviors. The research findings include two aspects; that is, (1) foreign shareholding has significantly positive impacts on enterprise innovation behaviors; (2) technology introduction plays a complete mediating effect in foreign shareholding and enterprise innovation behaviors. On the basis of considering sample selective bias and endogenous problems, the propensity score matching (PSM) method is further applied to evaluate the impacts of foreign shareholding on enterprise innovation behaviors. After putting the endogenous problems and sample selective bias under control, the above conclusions are still robust. Thus, under the current complicated international situation, enterprises should be encouraged to attract foreign investment under moderate control, with a view to accelerating the promotion of enterprise innovation activities through the technology introduction brought about by foreign shareholding

Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China

Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM10) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO2, NO2, PM10, annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures

Research on the Agglomeration and Spatiotemporal Development of China's Green High-Tech Industries

Accurate understanding of the spatial and temporal development of the agglomeration of green high-tech industries holds significant importance for the scientific formulation of policies promoting industrial innovation and development. This has attracted increasing attention from scholars. Utilizing nearly a decade's worth of statistical data on China's green high-tech industries, this paper employs methods from spatial geography and other disciplines to analyze the temporal and spatial variations, as well as the agglomeration characteristics of these industries in China. A comprehensive analysis of the development levels of China's high-tech industries and their sub-sectors is conducted through calculations of spatial Gini coefficients, industrial concentration ratios, location quotients, and coefficients of variation.Results indicate that the four key indicators of the development of China's major high-tech industries, namely the number of enterprises, employment figures, operating income, and profits, exhibit linear growth trends. Overall, the agglomeration level of the industry shows a fluctuating downward trend. The regional agglomeration level follows a gradient distribution trend of "eastern region - central region - western region - northeastern region," with a decreasing concentration trend. Regional disparities in the agglomeration level of industries evolve over time, with an increasing concentration in the western and central regions, and a decreasing concentration in the eastern and northeastern regions. From a provincial perspective, Guangdong and Jiangsu provinces stand out with significantly higher levels of development in high-tech industries.Furthermore, distinct differences are observed in the development processes of four typical industries. The agglomeration levels, ranked from high to low, are as follows: computer and office equipment manufacturing, electronic information and communication equipment manufacturing, medical device manufacturing, and pharmaceutical manufacturing，the development of the four types of industries has undergone certain transfers and optimizations.   Received: 22 December 2023 | Revised: 20 February 2024 | Accepted:26 February 2024   Conflicts of Interest The authors declare that they have no conflicts of interest to this work.   Data Availability Statement Data available on request from the authors

ON ADDITIVE CONSISTENT PROPERTIES OF THE INTUITIONISTIC FUZZY PREFERENCE RELATION

We investigate the properties of additive consistent intuitionistic fuzzy preference relations (IFPR). Usually, consistency in fuzzy preference relations (FPR) is associated with transitivity such as general transitivity, weak transitivity, and restricted max–max transitivity. This paper extends the consistency properties of the FPR to those of the IFPR. Since weak transitivity is the minimal logical requirement and a fundamental principle of human judgment, this paper develops three determination theorems and the corresponding algorithms to judge the weak transitivity of an IFPR from different angles. Two numerical examples show that the three methods proposed are feasible and effective.Intuitionistic fuzzy sets, preference relation, additive transitivity, weak transitivity

Haze Influencing Factors: A Data Envelopment Analysis Approach

This paper investigates the meteorological factors and human activities that influence PM2.5 pollution by employing the data envelopment analysis (DEA) approach to a chance constrained stochastic optimization problem. This approach has the two advantages of admitting random input and output, and allowing the evaluation unit to exceed the front edge under the given probability constraint. Furthermore, by utilizing the meteorological observation data incorporated with the economic and social data for Jiangsu Province, the chance constrained stochastic DEA model was solved to explore the relationship between the meteorological elements and human activities and PM2.5 pollution. The results are summarized by the following: (1) Among all five primary indexes, social progress, energy use and transportation are the most significant for PM2.5 pollution. (2) Among our selected 14 secondary indexes, coal consumption, population density and civil car ownership account for a major portion of PM2.5 pollution. (3) Human activities are the main factor producing PM2.5 pollution. While some meteorological elements generate PM2.5 pollution, some act as influencing factors on the migration of PM2.5 pollution. These findings can provide a reference for the government to formulate appropriate policies to reduce PM2.5 emissions and for the communities to develop effective strategies to eliminate PM2.5 pollution