Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need t...Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county's most likely to start using opioids were Pike and Bale.In Ohio,the county's most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids.展开更多
In recent years, the speed of urban development becomes faster and faster with expanding of land construction scale, and a lot of idle lands lead to serious land waste. This paper builds game model by carrying out a m...In recent years, the speed of urban development becomes faster and faster with expanding of land construction scale, and a lot of idle lands lead to serious land waste. This paper builds game model by carrying out a market allocation analysis and applying economic game theory to the analysis of current idle land problem; it gets six kinds of results through analyzing the game model of idle land market, and the final Nash equilibrium is(system innovation, publicly traded) through contrastive to help balance the game relationship between government and the user of idle land and raise some new scientific and rational institutions to serve as future references for effective usage of idle land.展开更多
The paradigm of global geopolitical competition has irreversibly shifted from the territorial accumulation of physical resources to the jurisdictional monopolization of algorithmic logic.In the era of Artificial Gener...The paradigm of global geopolitical competition has irreversibly shifted from the territorial accumulation of physical resources to the jurisdictional monopolization of algorithmic logic.In the era of Artificial General Intelligence(AGI),human capital is no longer merely a factor of economic production;it has metamorphosed into Sovereign Cognitive Capital.Consequently,the capacity of a nation or a strategic metropolis to attract,ingest,and retain top-tier artificial intelligence talent has become the absolute determinant of national technological sovereignty and strategic security.This study reconstructs the analytical geometry of global talent attraction by introducing the Institutional Gravity Model of Talent,mathematically establishing that elite AI researcher mobility is dictated by the precise interaction between regional Compute Density,Data Sovereignty Access,and Institutional Friction.By systematically applying this formal theoretical matrix to the immigration architectures of Silicon Valley,Toronto,London,Singapore,and Tel Aviv,the analysis demonstrates that traditional,subsidy-driven labor procurement mechanisms are catastrophically obsolete.Leveraging this paradigm,this paper explores how Guangzhou—functioning as the central transmission node of the Guangdong–Hong Kong–Macao Greater Bay Area(GBA)—can transcend conventional competitive disadvantages.The research establishes a hyper-strategic blueprint for Guangzhou,proposing the institutional creation of Algorithmic Special Economic Zones(ASEZs).These zones are designed to theoretically bypass domestic institutional friction through“Digital Extraterritoriality,”allowing elite global researchers unprecedented access to the world’s most massive industrial data-lake originating from GBA manufacturing,supercharged by unified cross-border compute capacity.Furthermore,the paper explicitly bridges talent immigration policy with National Security imperatives,illustrating how the aggressive mobilization of overseas Chinese diaspora networks and strategic visa deregulation constitute frontline defense mechanisms in the preservation of China’s autonomous knowledge systems.Ultimately,this monograph elevates municipal talent attraction from an administrative human resources function into a core organ of national geopolitical statecraft.展开更多
文摘Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county's most likely to start using opioids were Pike and Bale.In Ohio,the county's most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids.
基金Supported by Chinese Tobacco Science and Technology Project(YATAS-KJ-040)
文摘In recent years, the speed of urban development becomes faster and faster with expanding of land construction scale, and a lot of idle lands lead to serious land waste. This paper builds game model by carrying out a market allocation analysis and applying economic game theory to the analysis of current idle land problem; it gets six kinds of results through analyzing the game model of idle land market, and the final Nash equilibrium is(system innovation, publicly traded) through contrastive to help balance the game relationship between government and the user of idle land and raise some new scientific and rational institutions to serve as future references for effective usage of idle land.
基金Hebei Province Higher Education Reform Research and Practice Project:“Research on the Construction Path of Smart Curriculum for Immigration Management Science Based on Knowledge Graphs”(Grant No.2026GJJG457)Guangdong Province Higher Education Society“14th Five-Year Plan”Youth Project:“Research on the Functions and Realization Paths of Immigration Management Professional Education Serving the National Security Strategy from the Perspective of‘Safe China’”(Grant No.25GQN044).
文摘The paradigm of global geopolitical competition has irreversibly shifted from the territorial accumulation of physical resources to the jurisdictional monopolization of algorithmic logic.In the era of Artificial General Intelligence(AGI),human capital is no longer merely a factor of economic production;it has metamorphosed into Sovereign Cognitive Capital.Consequently,the capacity of a nation or a strategic metropolis to attract,ingest,and retain top-tier artificial intelligence talent has become the absolute determinant of national technological sovereignty and strategic security.This study reconstructs the analytical geometry of global talent attraction by introducing the Institutional Gravity Model of Talent,mathematically establishing that elite AI researcher mobility is dictated by the precise interaction between regional Compute Density,Data Sovereignty Access,and Institutional Friction.By systematically applying this formal theoretical matrix to the immigration architectures of Silicon Valley,Toronto,London,Singapore,and Tel Aviv,the analysis demonstrates that traditional,subsidy-driven labor procurement mechanisms are catastrophically obsolete.Leveraging this paradigm,this paper explores how Guangzhou—functioning as the central transmission node of the Guangdong–Hong Kong–Macao Greater Bay Area(GBA)—can transcend conventional competitive disadvantages.The research establishes a hyper-strategic blueprint for Guangzhou,proposing the institutional creation of Algorithmic Special Economic Zones(ASEZs).These zones are designed to theoretically bypass domestic institutional friction through“Digital Extraterritoriality,”allowing elite global researchers unprecedented access to the world’s most massive industrial data-lake originating from GBA manufacturing,supercharged by unified cross-border compute capacity.Furthermore,the paper explicitly bridges talent immigration policy with National Security imperatives,illustrating how the aggressive mobilization of overseas Chinese diaspora networks and strategic visa deregulation constitute frontline defense mechanisms in the preservation of China’s autonomous knowledge systems.Ultimately,this monograph elevates municipal talent attraction from an administrative human resources function into a core organ of national geopolitical statecraft.
