Multilevel modeling (MLM) has emerged as a powerful statistical framework for analyzing complex data structures with nested relationships. With its hierarchical modeling approach, MLM enables researchers to account fo...Multilevel modeling (MLM) has emerged as a powerful statistical framework for analyzing complex data structures with nested relationships. With its hierarchical modeling approach, MLM enables researchers to account for dependencies and variations within and between different levels of a hierarchy. By explicitly modeling these relationships, MLM provides a robust and accurate analysis of data. It has become increasingly popular in the field of education. MLM enables the investigation of various research issues, the evaluation of individual and group-level indicators, and the calculation of both fixed and random effects. Overall, MLM revolutionizes data analysis by uncovering patterns, understanding contextual effects, and making more precise statistical inferences in complex datasets. For fitting multilevel models in R, use lmer function provided by lme4 package. Through this examination, the use of a multilevel model is expected to increase and revolutionize data analysis and decision-making. The Constrained Intermediate Model (CIM) and Augmented Intermediate model (AIM) deviation are compared using the Likelihood-ratio (LR) test and the ANOVA function. This study analyzes student results from the University of Agriculture Faisalabad, collected via stratified random sampling. A linear mixed-effect model under multilevel modeling estimates the impact on CGPA, considering department, gender, intermediate marks, and entry test scores. These results indicate that Entry test is a significant predictor of CGPA, but the effect of department identifier CMC on CGPA is not statistically significant.展开更多
Introduction: Among young teens, about one in five smokes worldwide. Adolescents spend a considerable amount of their time in school, and the school environment is therefore important for child health practices and ou...Introduction: Among young teens, about one in five smokes worldwide. Adolescents spend a considerable amount of their time in school, and the school environment is therefore important for child health practices and outcomes. Objectives: We aimed to investigate the impact on smoking behavior of the school environment and the personal characteristics of male teenage students attending schools in Pakistan, taking into account the survey sampling structure. Methods: A two-stage cluster sampling with stratification was employed, and we interviewed 772 male secondary school students. We adopted random effect and generalizing estimating equation models. Results: Peer pressure in particular had a strong influence on adolescents smoking;those whose friends smoked were up to 6 times more likely to smoke. Family smoking was also significantly associated with adolescents smoking, but those students whose mother was educated were 50% less likely to smoke. The fitted random effect model indicated that the between school variability was significant (p-value < 0.01), indicating differences in smoking habits between schools. A random coefficient model showed that variability among schools was not significantly different for public and private schools. Conclusion: Public health campaigns for smoking cessation should target not only the individual but also the families of adolescents attending schools.展开更多
In this study,we used an extensive sampling network established in central Romania to develop tree height and crown length models.Our analysis included more than 18,000 tree measurements from five different species.In...In this study,we used an extensive sampling network established in central Romania to develop tree height and crown length models.Our analysis included more than 18,000 tree measurements from five different species.Instead of building univariate models for each response variable,we employed a multivariate approach using seemingly unrelated mixed-effects models.These models incorporated variables related to species mixture,tree and stand size,competition,and stand structure.With the inclusion of additional variables in the multivariate seemingly unrelated mixed-effects models,the accuracy of the height prediction models improved by over 10% for all species,whereas the improvement in the crown length models was considerably smaller.Our findings indicate that trees in mixed stands tend to have shorter heights but longer crowns than those in pure stands.We also observed that trees in homogeneous stand structures have shorter crown lengths than those in heterogeneous stands.By employing a multivariate mixed-effects modelling framework,we were able to perform cross-model random-effect predictions,leading to a significant increase in accuracy when both responses were used to calibrate the model.In contrast,the improvement in accuracy was marginal when only height was used for calibration.We demonstrate how multivariate mixed-effects models can be effectively used to develop multi-response allometric models that can be easily calibrated with a limited number of observations while simultaneously achieving better-aligned projections.展开更多
Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation ind...Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation index （NDVI） from remotely-sensed imagery, dividing human-induced land degradation from vegetation dynamics due to climate change is not a trivial task. This paper presented a multilevel statistical modeling of the NDVI-rainfall relationship to detect human-induced land degradation at local and landscape scales in the Ordos Plateau of Inner Mongolia, China, and recognized that anthropogenic activities result in either positive （land restoration and re-vegetation） or negative （degradation） trends. Linear regressions were used to assess the accuracy of the multi- level statistical model. The results show that： （1） land restoration was the dominant process in the Ordos Plateau between 1998 and 2012; （2） the effect of the statistical removal of precipitation revealed areas of human-induced land degradation and improvement, the latter reflecting successful restoration projects and changes in land man- agement in many parts of the Ordos; （3） compared to a simple linear regression, multilevel statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. Additional factors should be included when analyzing the NDVI-rainfall relationship and detecting human-induced loss of vegetation cover in drylands to improve the accuracy of the approach and elimi- nate some observed non-significant residual trends.展开更多
Modern battlefield doctrine is based on mobility, flexibility, and rapid response to changing situations. As is well known, mobile ad hoc network systems are among the best utilities for battlefield activity. Although...Modern battlefield doctrine is based on mobility, flexibility, and rapid response to changing situations. As is well known, mobile ad hoc network systems are among the best utilities for battlefield activity. Although much research has been done on secure routing, security issues have largely been ignored in applying mobile ad hoc network theory to computer technology. An ad hoc network is usually assumed to be homogeneous, which is an irrational assumption for armies. It is clear that soldiers, commanders, and commanders-in-chief should have different security levels and computation powers as they have access to asymmetric resources. Imitating basic military rank levels in battlefield situations, how multilevel security can be introduced into ad hoc networks is indicated, thereby controlling restricted classified information flows among nodes that have different security levels.展开更多
To construct a high efficient text clustering algorithm the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed. The model is applied to text clustering. The performance of ...To construct a high efficient text clustering algorithm the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed. The model is applied to text clustering. The performance of clustering algorithm has to be improved with the refinement algorithm application. The experiment result demonstrated that the multilevel graph text clustering algorithm is available. Key words text clustering - multilevel coarsen graph model - refinement algorithm - high-dimensional clustering CLC number TP301 Foundation item: Supported by the National Natural Science Foundation of China (60173051)Biography: CHEN Jian-bin(1970-), male, Associate professor, Ph. D., research direction: data mining.展开更多
By means of vertical normal modes a regional nested multilevel primitive equation model can be reduced to several sets of shallow water equations characterized by various equivalent depths. Therefore, time integration...By means of vertical normal modes a regional nested multilevel primitive equation model can be reduced to several sets of shallow water equations characterized by various equivalent depths. Therefore, time integration of the model in spectral form can be performed in the manner similar to those used in the spectral nested shallow water equation model case.展开更多
The massive scale of new-generation rural-urban migrants in China has attracted extensive scholarly attention in recent years.While previous studies on China’s rural migrant workers focus on migrants’settlement inte...The massive scale of new-generation rural-urban migrants in China has attracted extensive scholarly attention in recent years.While previous studies on China’s rural migrant workers focus on migrants’settlement intentions,migrants’family migration decision-making and the intergenerational differences between the old-generation migrants and new-generation migrants are underexplored.Based on the data of the 2017 China Migrants Dynamic Survey,this paper adopts a multilevel logistic regression approach to explore family and destination factors influencing the family migration decisions of China’s new generation of rural migrant workers.The empirical results reveal that both the migrants’family and destination attributes significantly influence their family migration decision.The demographic and socioeconomic characteristics of the family have been pivotal factors underlying the family migration decision of China’s new generation rural-urban migrants,while 16.9%of the chances are explained by between-destination differences.Self-employed migrants with housing properties in host cities,long migration duration and high-income levels are more likely to migrate with their family members.Yet,the possibility of family migration is found to be significantly and negatively correlated with the age,education level,number of children and inter-provincial mobility of the new generation of migrant workers.In addition,new-generation rural-urban migrants’family migration is more likely to be found in cities with service-oriented industry structures,better environmental quality,and higher hukou barriers which is possibly related to more job opportunities.These research findings not only complement the existing literature on China’s new generation of rural urban migrants,but also have important policy implications for reforming the hukou system and enhancing social integration of the rural-to-urban migrant population.展开更多
The level of surveillance and preparedness against epidemics varies across countries,resulting in different responses to outbreaks.When conducting an in-depth analysis of microinfection dynamics,one must account for t...The level of surveillance and preparedness against epidemics varies across countries,resulting in different responses to outbreaks.When conducting an in-depth analysis of microinfection dynamics,one must account for the substantial heterogeneity across countries.However,many commonly used statistical model specifications lack the flexibility needed for sound and accurate analysis and prediction in such contexts.Nonlinear mixed effects models(NLMMs)constitute a specific statistical tool that can overcome these significant challenges.While compartmental models are well-established in infectious disease modeling and have seen significant advancements,Nonlinear Mixed Models(NLMMs)offer a flexible approach for handling heterogeneous and unbalanced repeated measures data,often with less computational effort than some individual-level compartmental modeling techniques.This study provides an overview of their current use and offers a solid foundation for developing guidelines that may help improve their implementation in real-world situations.Relevant scientific databases in the Research4life Access initiative programs were used to search for papers dealing with key aspects of NLMMs in infectious disease modeling(IDM).From an initial list of 3641 papers,124 were finally included and used for this systematic and critical review spanning the last two decades,following the PRISMA guidelines.NLMMs have evolved rapidly in the last decade,especially in IDM,with most publications dating from 2017 to 2021(83.33%).The routine use of normality assumption appeared inappropriate for IDM,leading to a wealth of literature on NLMMs with non-normal errors and random effects under various estimation methods.We noticed that NLMMs have attracted much attention for the latest known epidemics worldwide(COVID-19,Ebola,Dengue and Lassa)with the robustness and reliability of relaxed propositions of the normality assumption.A case study of the application of COVID-19 data helped to highlight NLMMs’performance in modeling infectious diseases.Out of this study,estimation methods,assumptions,and random terms specification in NLMMs are key aspects requiring particular attention for their application in IDM.展开更多
In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations i...In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.展开更多
In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level...In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level model of this type with ixj=3x2,k=l,and the 1980 monthly mean temperture predichon on a long-t6rm basis were prepared by steadily modifying the weighting coefficient,making for the correlation coefficient of 97% with the measurements.Furthermore,the weighhng parameter was modified for each month of 1980 by means of observations,therefore constrcuhng monthly mean temperature forecasts from January to December of the year,reaching the correlation of 99.9% with the measurements.Likewise,the resulting 1981 monthly predictions on a long-range basis with 1946-1980 corresponding records yielded the correlahon of 98% and the month-tO month forecasts of 99.4%.展开更多
The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,w...The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,we investigate how integration between male and female grooming and aggression interaction networks influences male power trajectories in vervet monkeys Chlorocebus pygerythrus.Our previous analyses of this phenomenon used a monolayer approach,and our aim here is to extend these analyses using a dynamic multilayer approach.To do so,we constructed a temporal series of male and female interaction layers.We then used a multivariate multilevel autoregression model to compare cross-lagged associations between a male's centrality in the female grooming layer and changes in male Elo ratings.Our results confirmed our original findings:changes in male centrality within the female grooming network were weakly but positively tied to changes in their Elo ratings.However,the multilayer network approach offered additional insights into this social process,identifying how changes in a male's centrality cascade through the other network layers.This dynamic view indicates that the changes in Elo ratings are likely to be short-lived,but that male centrality within the female network had a much stronger impact throughout the multilayer network as a whole,especially on reducing intermale aggression(i.e.,aggression directed by males toward other males).We suggest that multilayer social network approaches can take advantage of increased amounts of social data that are more commonly collected these days,using a variety of methods.Such data are inherently multilevel and multilayered,and thus offer the ability to quantify more precisely the dynamics of animal social behaviors.展开更多
Attosecond transient absorption(ATA)has been developed as an all-optical technique for probing electron dynamics in matter.Here we present a scheme that can modify the laserinduced state and the corresponding ATA spec...Attosecond transient absorption(ATA)has been developed as an all-optical technique for probing electron dynamics in matter.Here we present a scheme that can modify the laserinduced state and the corresponding ATA spectrum via excitation by a pair of XUV attosecond pulses and by a time-delayed mid-infrared(MIR)laser probe.Different from the scheme of the electronic excitation by a single XUV attosecond pulse,the application of a pair of XUV pulses provides extra degrees of freedom,such as the time delay and the intensity ratio between two XUV pulses,which make it possible to adjust the pump process,resulting in the modification of the ATA spectrum.We show that by varying the time delay between the two XUV pulses,the population of the dark state and the ATA spectrum of the laser-induced state have periodic modulations.We also demonstrate that the peak of the ATA spectrum of the laser-induced state appears at a fixed time delay between the XUV pair and the MIR laser when the intensity ratio is large,and it changes with the time delay when the intensity ratio is small,which can be related to either one of two peaks in the population of the dark state.展开更多
Based on the multilevel model, numerical calculations of tidal current affected by the M-2 tide in the Tokyo Bay have been carried out. The results of calculation are compared with the data observed in the Tokyo Bay a...Based on the multilevel model, numerical calculations of tidal current affected by the M-2 tide in the Tokyo Bay have been carried out. The results of calculation are compared with the data observed in the Tokyo Bay and the result calculated by an approximate formula as the Tokyo Bay is regarded as a rectangular bay, and good agreement is found. It is proved that the mathematical model and the calculation method are correct and useable.展开更多
Aims:This study aims to explore the association between drinking water salinity and hypertension in three coastal sub-districts of Bangladesh.Methods:The study uses complete data on 6,296 individuals extracted from th...Aims:This study aims to explore the association between drinking water salinity and hypertension in three coastal sub-districts of Bangladesh.Methods:The study uses complete data on 6,296 individuals extracted from the latest Bangladesh Poverty and Groundwater Salinity Survey and a mixed-effects logistic regression model as the analytical tool.Results:Mixed-effects logistic regression analysis shows a significant association of medium or higherlevel salinity with hypertension(adjusted odds ratio[AOR]1.650,95%confidence interval[CI]:1.101—2.473).Other variables significantly associated with hypertension are age,sex,education status,water source,and geographical location.A sizable proportion of the total individual-level variance in the probability of being hypertensive was at household-level(20%)and cluster-level(8%).Conclusion:The findings from this study suggest that greater salinity in potable water common in coastal areas in Bangladesh is associated with increased risk of hypertension.The study refrains from asserting causality but seeks to stimulate public health and policy interventions to address the increased risk.展开更多
This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relatio...This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relation hierarchical data model. Based on the multilevel relation hierarchical data model, the concept of upper lower layer relational integrity is presented after we analyze and eliminate the covert channels caused by the database integrity. Two SQL statements are extended to process polyinstantiation in the multilevel secure environment. The system is based on the multilevel relation hierarchical data model and is capable of integratively storing and manipulating multilevel complicated objects ( e.g., multilevel spatial data) and multilevel conventional data ( e.g., integer, real number and character string).展开更多
Background and aims:The holistic definition of health is not merely the absence of disease or infirmity,but a state of complete physical,mental,and social well-being.However,related research on the influencing factor ...Background and aims:The holistic definition of health is not merely the absence of disease or infirmity,but a state of complete physical,mental,and social well-being.However,related research on the influencing factor of self-rated health and happiness have generally remained separate.Therefore,this study aimed to 1)find individual level determinants of the two facets of health;and 2)investigate the covariance of the two facets of health within individual levels.Methods:Multivariate multilevel analysis of self-rated health and happiness at level 1,were nested within 10,968 people at level 2.Data were obtained from the 2015 Chinese General Social Survey.Results:Lower happiness and self-rated health were found in 1)females;2)the elderly;3)people with a lower educational level;4)people who were presently single;5)people with a lower self-rated economic status;6)people who resided in urban areas;and 7)people with sedentary lifestyles as compared to those in other categories of the same variable.After adjusting the related individual level determinants,the correlation coefficient of two facets of health at the individual level is 0.19,which indicates that no robust covariance was observed.Conclusions:The current study indicates the existence of disparity in the subjective physical and psychological dimensions of health among the elderly in China.Our findings emphasize the importance of paying attention to different aspects of health simultaneously in investigations and the benefits of leisure time activities.展开更多
Background:Uneven economic development has led to substantial health inequalities between Chinese provinces.The extent of,and factors underlying,between-province health inequalities have received little attention.Meth...Background:Uneven economic development has led to substantial health inequalities between Chinese provinces.The extent of,and factors underlying,between-province health inequalities have received little attention.Methods:Data from 15,278 respondents in Wave 2(2013)of the China Health and Retirement Longitudinal Study(CHARLS)were used to investigate inequalities among people aged≥50 years in five health outcomes between 27 Chinese province-level administrative units.After characterizing the betweenprovince differences and the relevance of province effects,proportional change in variance between unadjusted and adjusted models was calculated to determine the percentage of between-province variance in health outcomes explained by province-level variables including measures of economic development and healthcare availability.Results:Although province effects explained<10%of overall variance in health outcomes,they underpinned large between-province inequalities among people aged≥50 years.Gross Regional Product per capita was more important than doctor density in explaining between-province variance in health outcomes,particularly depression symptoms and instrumental activities of daily living impairment.Conclusion:Policy efforts,including more equal distribution of healthcare personnel,may be warranted to reduce between-province health inequalities.展开更多
While much of international marketing research involves two or more levels, limited work in the international marketing literature uses hierarchical linear modeling to examine different level effects. This study condu...While much of international marketing research involves two or more levels, limited work in the international marketing literature uses hierarchical linear modeling to examine different level effects. This study conducts a thorough literature review on hierarchical linear modeling （HLM） in 28 international marketing papers that employed HLM from 2005-2014 and evaluates the use of HLM in these papers on the objects, operating levels, and other issues. We call for more applications of HLM in international marketing research, particularly for research on emerging markets with significant sub-national and institutional variations. The paper provides an illustrative empirical study that employs HLM to test the moderating role of industry-level government subsidies in the relationship between firm innovation and exporter performance in China.展开更多
文摘Multilevel modeling (MLM) has emerged as a powerful statistical framework for analyzing complex data structures with nested relationships. With its hierarchical modeling approach, MLM enables researchers to account for dependencies and variations within and between different levels of a hierarchy. By explicitly modeling these relationships, MLM provides a robust and accurate analysis of data. It has become increasingly popular in the field of education. MLM enables the investigation of various research issues, the evaluation of individual and group-level indicators, and the calculation of both fixed and random effects. Overall, MLM revolutionizes data analysis by uncovering patterns, understanding contextual effects, and making more precise statistical inferences in complex datasets. For fitting multilevel models in R, use lmer function provided by lme4 package. Through this examination, the use of a multilevel model is expected to increase and revolutionize data analysis and decision-making. The Constrained Intermediate Model (CIM) and Augmented Intermediate model (AIM) deviation are compared using the Likelihood-ratio (LR) test and the ANOVA function. This study analyzes student results from the University of Agriculture Faisalabad, collected via stratified random sampling. A linear mixed-effect model under multilevel modeling estimates the impact on CGPA, considering department, gender, intermediate marks, and entry test scores. These results indicate that Entry test is a significant predictor of CGPA, but the effect of department identifier CMC on CGPA is not statistically significant.
文摘Introduction: Among young teens, about one in five smokes worldwide. Adolescents spend a considerable amount of their time in school, and the school environment is therefore important for child health practices and outcomes. Objectives: We aimed to investigate the impact on smoking behavior of the school environment and the personal characteristics of male teenage students attending schools in Pakistan, taking into account the survey sampling structure. Methods: A two-stage cluster sampling with stratification was employed, and we interviewed 772 male secondary school students. We adopted random effect and generalizing estimating equation models. Results: Peer pressure in particular had a strong influence on adolescents smoking;those whose friends smoked were up to 6 times more likely to smoke. Family smoking was also significantly associated with adolescents smoking, but those students whose mother was educated were 50% less likely to smoke. The fitted random effect model indicated that the between school variability was significant (p-value < 0.01), indicating differences in smoking habits between schools. A random coefficient model showed that variability among schools was not significantly different for public and private schools. Conclusion: Public health campaigns for smoking cessation should target not only the individual but also the families of adolescents attending schools.
基金supported by the European Union and the Romanian Government through the Competitiveness Operational Programme 2014–2020, under the project“Increasing the economic competitiveness of the forestry sector and the quality of life through knowledge transfer,technology and CDI skills”(CRESFORLIFE),ID P 40 380/105506, subsidiary contract no. 17/2020partially by the FORCLIMSOC Nucleu Programme (Contract 12N/2023)+2 种基金project PN 23090101CresPerfInst project (Contract 34PFE/December 30, 2021)“Increasing the institutional capacity and performance of INCDS ‘Marin Drǎcea’in RDI activities-CresPer”LM was financially supported by the Research Council of Finland's flagship ecosystem for Forest-Human-Machine Interplay–Building Resilience, Redefining Value Networks and Enabling Meaningful Experiences (UNITE)(decision number 357909)
文摘In this study,we used an extensive sampling network established in central Romania to develop tree height and crown length models.Our analysis included more than 18,000 tree measurements from five different species.Instead of building univariate models for each response variable,we employed a multivariate approach using seemingly unrelated mixed-effects models.These models incorporated variables related to species mixture,tree and stand size,competition,and stand structure.With the inclusion of additional variables in the multivariate seemingly unrelated mixed-effects models,the accuracy of the height prediction models improved by over 10% for all species,whereas the improvement in the crown length models was considerably smaller.Our findings indicate that trees in mixed stands tend to have shorter heights but longer crowns than those in pure stands.We also observed that trees in homogeneous stand structures have shorter crown lengths than those in heterogeneous stands.By employing a multivariate mixed-effects modelling framework,we were able to perform cross-model random-effect predictions,leading to a significant increase in accuracy when both responses were used to calibrate the model.In contrast,the improvement in accuracy was marginal when only height was used for calibration.We demonstrate how multivariate mixed-effects models can be effectively used to develop multi-response allometric models that can be easily calibrated with a limited number of observations while simultaneously achieving better-aligned projections.
基金National Basic Research Program of China (2012CB722201)National Natural Science Foundation of China (30970504, 31060320)National Science and Technology Support Program (2011BAC07B01)
文摘Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation index （NDVI） from remotely-sensed imagery, dividing human-induced land degradation from vegetation dynamics due to climate change is not a trivial task. This paper presented a multilevel statistical modeling of the NDVI-rainfall relationship to detect human-induced land degradation at local and landscape scales in the Ordos Plateau of Inner Mongolia, China, and recognized that anthropogenic activities result in either positive （land restoration and re-vegetation） or negative （degradation） trends. Linear regressions were used to assess the accuracy of the multi- level statistical model. The results show that： （1） land restoration was the dominant process in the Ordos Plateau between 1998 and 2012; （2） the effect of the statistical removal of precipitation revealed areas of human-induced land degradation and improvement, the latter reflecting successful restoration projects and changes in land man- agement in many parts of the Ordos; （3） compared to a simple linear regression, multilevel statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. Additional factors should be included when analyzing the NDVI-rainfall relationship and detecting human-induced loss of vegetation cover in drylands to improve the accuracy of the approach and elimi- nate some observed non-significant residual trends.
基金the National Natural Science Foundation of China (60773049)the Natural Science Foundationof Jiangsu Province (BK2007086)the Fundamental Research Project of Natural Science in Colleges of Jiangsu Province(07KJB520016).
文摘Modern battlefield doctrine is based on mobility, flexibility, and rapid response to changing situations. As is well known, mobile ad hoc network systems are among the best utilities for battlefield activity. Although much research has been done on secure routing, security issues have largely been ignored in applying mobile ad hoc network theory to computer technology. An ad hoc network is usually assumed to be homogeneous, which is an irrational assumption for armies. It is clear that soldiers, commanders, and commanders-in-chief should have different security levels and computation powers as they have access to asymmetric resources. Imitating basic military rank levels in battlefield situations, how multilevel security can be introduced into ad hoc networks is indicated, thereby controlling restricted classified information flows among nodes that have different security levels.
文摘To construct a high efficient text clustering algorithm the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed. The model is applied to text clustering. The performance of clustering algorithm has to be improved with the refinement algorithm application. The experiment result demonstrated that the multilevel graph text clustering algorithm is available. Key words text clustering - multilevel coarsen graph model - refinement algorithm - high-dimensional clustering CLC number TP301 Foundation item: Supported by the National Natural Science Foundation of China (60173051)Biography: CHEN Jian-bin(1970-), male, Associate professor, Ph. D., research direction: data mining.
文摘By means of vertical normal modes a regional nested multilevel primitive equation model can be reduced to several sets of shallow water equations characterized by various equivalent depths. Therefore, time integration of the model in spectral form can be performed in the manner similar to those used in the spectral nested shallow water equation model case.
基金supported by the National Natural Science Foundation of China(Project Number:NSFC 71403193).
文摘The massive scale of new-generation rural-urban migrants in China has attracted extensive scholarly attention in recent years.While previous studies on China’s rural migrant workers focus on migrants’settlement intentions,migrants’family migration decision-making and the intergenerational differences between the old-generation migrants and new-generation migrants are underexplored.Based on the data of the 2017 China Migrants Dynamic Survey,this paper adopts a multilevel logistic regression approach to explore family and destination factors influencing the family migration decisions of China’s new generation of rural migrant workers.The empirical results reveal that both the migrants’family and destination attributes significantly influence their family migration decision.The demographic and socioeconomic characteristics of the family have been pivotal factors underlying the family migration decision of China’s new generation rural-urban migrants,while 16.9%of the chances are explained by between-destination differences.Self-employed migrants with housing properties in host cities,long migration duration and high-income levels are more likely to migrate with their family members.Yet,the possibility of family migration is found to be significantly and negatively correlated with the age,education level,number of children and inter-provincial mobility of the new generation of migrant workers.In addition,new-generation rural-urban migrants’family migration is more likely to be found in cities with service-oriented industry structures,better environmental quality,and higher hukou barriers which is possibly related to more job opportunities.These research findings not only complement the existing literature on China’s new generation of rural urban migrants,but also have important policy implications for reforming the hukou system and enhancing social integration of the rural-to-urban migrant population.
基金support from Deutscher Akademischer Austauschdienst German Academic Exchange Service(DAAD)through the programme In-Country/In-Region ScholarshipRGK acknowledges the support from the German Federal Foreign Office(Grant number:Ref.3.4.-Ben-Hub).
文摘The level of surveillance and preparedness against epidemics varies across countries,resulting in different responses to outbreaks.When conducting an in-depth analysis of microinfection dynamics,one must account for the substantial heterogeneity across countries.However,many commonly used statistical model specifications lack the flexibility needed for sound and accurate analysis and prediction in such contexts.Nonlinear mixed effects models(NLMMs)constitute a specific statistical tool that can overcome these significant challenges.While compartmental models are well-established in infectious disease modeling and have seen significant advancements,Nonlinear Mixed Models(NLMMs)offer a flexible approach for handling heterogeneous and unbalanced repeated measures data,often with less computational effort than some individual-level compartmental modeling techniques.This study provides an overview of their current use and offers a solid foundation for developing guidelines that may help improve their implementation in real-world situations.Relevant scientific databases in the Research4life Access initiative programs were used to search for papers dealing with key aspects of NLMMs in infectious disease modeling(IDM).From an initial list of 3641 papers,124 were finally included and used for this systematic and critical review spanning the last two decades,following the PRISMA guidelines.NLMMs have evolved rapidly in the last decade,especially in IDM,with most publications dating from 2017 to 2021(83.33%).The routine use of normality assumption appeared inappropriate for IDM,leading to a wealth of literature on NLMMs with non-normal errors and random effects under various estimation methods.We noticed that NLMMs have attracted much attention for the latest known epidemics worldwide(COVID-19,Ebola,Dengue and Lassa)with the robustness and reliability of relaxed propositions of the normality assumption.A case study of the application of COVID-19 data helped to highlight NLMMs’performance in modeling infectious diseases.Out of this study,estimation methods,assumptions,and random terms specification in NLMMs are key aspects requiring particular attention for their application in IDM.
基金Under the auspices of the National Natural Science Foundation of China(No.71371160)the Program for Changjiang Youth Scholars(No.Q2016131)the Program for New Century Excellent Talents in University(No.NCET-13-0509)
文摘In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.
文摘In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level model of this type with ixj=3x2,k=l,and the 1980 monthly mean temperture predichon on a long-t6rm basis were prepared by steadily modifying the weighting coefficient,making for the correlation coefficient of 97% with the measurements.Furthermore,the weighhng parameter was modified for each month of 1980 by means of observations,therefore constrcuhng monthly mean temperature forecasts from January to December of the year,reaching the correlation of 99.9% with the measurements.Likewise,the resulting 1981 monthly predictions on a long-range basis with 1946-1980 corresponding records yielded the correlahon of 98% and the month-tO month forecasts of 99.4%.
基金This work was funded by NRH(South Africa)and UNISA awards(S.P.H.),NSERC(Canada)Discovery grants(L.B.,S.P.H.)the NSERC Canada Research Chair program(L.B.)+2 种基金C.Y.is the recipient of a University of Pretoria Senior Postdoctoral FellowshipT.B.has been funded by an FQNRT Post-Doctoral FellowshipT.B.and C.V.are currently funded by NSERC Canada Research Chair and Discovery Grants held by L.B.
文摘The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,we investigate how integration between male and female grooming and aggression interaction networks influences male power trajectories in vervet monkeys Chlorocebus pygerythrus.Our previous analyses of this phenomenon used a monolayer approach,and our aim here is to extend these analyses using a dynamic multilayer approach.To do so,we constructed a temporal series of male and female interaction layers.We then used a multivariate multilevel autoregression model to compare cross-lagged associations between a male's centrality in the female grooming layer and changes in male Elo ratings.Our results confirmed our original findings:changes in male centrality within the female grooming network were weakly but positively tied to changes in their Elo ratings.However,the multilayer network approach offered additional insights into this social process,identifying how changes in a male's centrality cascade through the other network layers.This dynamic view indicates that the changes in Elo ratings are likely to be short-lived,but that male centrality within the female network had a much stronger impact throughout the multilayer network as a whole,especially on reducing intermale aggression(i.e.,aggression directed by males toward other males).We suggest that multilayer social network approaches can take advantage of increased amounts of social data that are more commonly collected these days,using a variety of methods.Such data are inherently multilevel and multilayered,and thus offer the ability to quantify more precisely the dynamics of animal social behaviors.
基金supported by the National Natural Science Foundation of China(Grant Nos.91950102 and 11834004)the Natural Science Foundation of Jiangsu Province(Grant No.BK20220925)the Funding of Nanjing University of Science and Technology(NJUST)(Grant No.TSXK2022D005)
文摘Attosecond transient absorption(ATA)has been developed as an all-optical technique for probing electron dynamics in matter.Here we present a scheme that can modify the laserinduced state and the corresponding ATA spectrum via excitation by a pair of XUV attosecond pulses and by a time-delayed mid-infrared(MIR)laser probe.Different from the scheme of the electronic excitation by a single XUV attosecond pulse,the application of a pair of XUV pulses provides extra degrees of freedom,such as the time delay and the intensity ratio between two XUV pulses,which make it possible to adjust the pump process,resulting in the modification of the ATA spectrum.We show that by varying the time delay between the two XUV pulses,the population of the dark state and the ATA spectrum of the laser-induced state have periodic modulations.We also demonstrate that the peak of the ATA spectrum of the laser-induced state appears at a fixed time delay between the XUV pair and the MIR laser when the intensity ratio is large,and it changes with the time delay when the intensity ratio is small,which can be related to either one of two peaks in the population of the dark state.
文摘Based on the multilevel model, numerical calculations of tidal current affected by the M-2 tide in the Tokyo Bay have been carried out. The results of calculation are compared with the data observed in the Tokyo Bay and the result calculated by an approximate formula as the Tokyo Bay is regarded as a rectangular bay, and good agreement is found. It is proved that the mathematical model and the calculation method are correct and useable.
基金The authors are grateful to open access to data offered by the World Bank and the cooperation of respondents to the survey.
文摘Aims:This study aims to explore the association between drinking water salinity and hypertension in three coastal sub-districts of Bangladesh.Methods:The study uses complete data on 6,296 individuals extracted from the latest Bangladesh Poverty and Groundwater Salinity Survey and a mixed-effects logistic regression model as the analytical tool.Results:Mixed-effects logistic regression analysis shows a significant association of medium or higherlevel salinity with hypertension(adjusted odds ratio[AOR]1.650,95%confidence interval[CI]:1.101—2.473).Other variables significantly associated with hypertension are age,sex,education status,water source,and geographical location.A sizable proportion of the total individual-level variance in the probability of being hypertensive was at household-level(20%)and cluster-level(8%).Conclusion:The findings from this study suggest that greater salinity in potable water common in coastal areas in Bangladesh is associated with increased risk of hypertension.The study refrains from asserting causality but seeks to stimulate public health and policy interventions to address the increased risk.
文摘This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relation hierarchical data model. Based on the multilevel relation hierarchical data model, the concept of upper lower layer relational integrity is presented after we analyze and eliminate the covert channels caused by the database integrity. Two SQL statements are extended to process polyinstantiation in the multilevel secure environment. The system is based on the multilevel relation hierarchical data model and is capable of integratively storing and manipulating multilevel complicated objects ( e.g., multilevel spatial data) and multilevel conventional data ( e.g., integer, real number and character string).
文摘Background and aims:The holistic definition of health is not merely the absence of disease or infirmity,but a state of complete physical,mental,and social well-being.However,related research on the influencing factor of self-rated health and happiness have generally remained separate.Therefore,this study aimed to 1)find individual level determinants of the two facets of health;and 2)investigate the covariance of the two facets of health within individual levels.Methods:Multivariate multilevel analysis of self-rated health and happiness at level 1,were nested within 10,968 people at level 2.Data were obtained from the 2015 Chinese General Social Survey.Results:Lower happiness and self-rated health were found in 1)females;2)the elderly;3)people with a lower educational level;4)people who were presently single;5)people with a lower self-rated economic status;6)people who resided in urban areas;and 7)people with sedentary lifestyles as compared to those in other categories of the same variable.After adjusting the related individual level determinants,the correlation coefficient of two facets of health at the individual level is 0.19,which indicates that no robust covariance was observed.Conclusions:The current study indicates the existence of disparity in the subjective physical and psychological dimensions of health among the elderly in China.Our findings emphasize the importance of paying attention to different aspects of health simultaneously in investigations and the benefits of leisure time activities.
基金supported by the Behavioral and Social Research division of the National Institute on Aging(grant numbers 1-R21-AG031372-01,1-R01-AG037031-01,and 3-R01AG037031-03S1)the Natural Science Foundation of China(grant numbers 70910107022,71130002 and 71273237)+2 种基金the World Bank(contract numbers 7145915 and 7159234)the China Medical BoardPeking University.
文摘Background:Uneven economic development has led to substantial health inequalities between Chinese provinces.The extent of,and factors underlying,between-province health inequalities have received little attention.Methods:Data from 15,278 respondents in Wave 2(2013)of the China Health and Retirement Longitudinal Study(CHARLS)were used to investigate inequalities among people aged≥50 years in five health outcomes between 27 Chinese province-level administrative units.After characterizing the betweenprovince differences and the relevance of province effects,proportional change in variance between unadjusted and adjusted models was calculated to determine the percentage of between-province variance in health outcomes explained by province-level variables including measures of economic development and healthcare availability.Results:Although province effects explained<10%of overall variance in health outcomes,they underpinned large between-province inequalities among people aged≥50 years.Gross Regional Product per capita was more important than doctor density in explaining between-province variance in health outcomes,particularly depression symptoms and instrumental activities of daily living impairment.Conclusion:Policy efforts,including more equal distribution of healthcare personnel,may be warranted to reduce between-province health inequalities.
基金The anthors are grateful for the financial support of the Research Funding for the Doctoral Programs of Higher Education, Ministry of Education, China （20120004120005）, the Beijing Youth Talent Project, and National Natural Science Foundation of China （71202149）.
文摘While much of international marketing research involves two or more levels, limited work in the international marketing literature uses hierarchical linear modeling to examine different level effects. This study conducts a thorough literature review on hierarchical linear modeling （HLM） in 28 international marketing papers that employed HLM from 2005-2014 and evaluates the use of HLM in these papers on the objects, operating levels, and other issues. We call for more applications of HLM in international marketing research, particularly for research on emerging markets with significant sub-national and institutional variations. The paper provides an illustrative empirical study that employs HLM to test the moderating role of industry-level government subsidies in the relationship between firm innovation and exporter performance in China.
