Root-cause identification plays a vital role in business decision making by providing effective future directions for the organizations.Aspect extraction and sentiment extraction plays a vital role in identifying the ...Root-cause identification plays a vital role in business decision making by providing effective future directions for the organizations.Aspect extraction and sentiment extraction plays a vital role in identifying the rootcauses.This paper proposes the Ensemble based temporal weighting and pareto ranking(ETP)model for Root-cause identification.Aspect extraction is performed based on rules and is followed by opinion identification using the proposed boosted ensemble model.The obtained aspects are validated and ranked using the proposed aspect weighing scheme.Pareto-rule based aspect selection is performed as the final selection mechanism and the results are presented for business decision making.Experiments were performed with the standard five product benchmark dataset.Performances on all five product reviews indicate the effective performance of the proposed model.Comparisons are performed using three standard state-of-the-art models and effectiveness is measured in terms of F-Measure and Detection rates.The results indicate improved performances exhibited by the proposed model with an increase in F-Measure levels at 1%–15%and detection rates at 4%–24%compared to the state-of-the-art models.展开更多
Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-tempor...Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever’s temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever’s spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors’influence exhibiting notable spatial and temporal variation.展开更多
The Yellow River Basin in Sichuan Province(YRS)is undergoing severe soil erosion and exacerbated ecological vulnerability,which collectively pose formidable challenges for regional water conservation(WC)and sustainabl...The Yellow River Basin in Sichuan Province(YRS)is undergoing severe soil erosion and exacerbated ecological vulnerability,which collectively pose formidable challenges for regional water conservation(WC)and sustainable development.While effectively enhancing WC necessitates a comprehensive understanding of its driving factors and corresponding intervention strategies,existing studies have largely neglected the spatiotemporal heterogeneity of both natural and socio-economic drivers.Therefore,this study explored the spatiotemporal heterogeneity of WC drivers in YRS using multi-scale geographically weighted regression(MGWR)and geographically and temporally weighted regression(GTWR)models from an eco-hydrological perspective.We discovered that downstream regions,which are more developed,achieved significantly better WC than upstream regions.The results also demonstrated that the influence of temperature and wind speed is consistently dominant and temporally stable due to climate stability,while the influence of vegetation shifted from negative to positive around 2010,likely indicating greater benefits from understory vegetation.Economic growth positively impacted WC in upstream regions but had a negative effect in the more developed downstream regions.These findings highlight the importance of targeted water conservation strategies,including locally appropriate revegetation,optimization of agricultural and economic structures,and the establishment of eco-compensation mechanisms for ecological conservation and sustainable development.展开更多
This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station...This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station planning and development.Data from 159 metro stations in Nanjing,collected over a 14-d period,were analyzed to identify changes in weekday and weekend ridership patterns.The analysis included explanatory variables grouped into three categories:urban spatial variables,socioeconomic vari-ables,and transit service variables.A geographically and temporally weighted regression(GTWR)model was developed,and its performance was compared with that of ordinary least squares(OLS)and geographically weighted regression(GWR)models.The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment.In addition,the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions,revealing distinct patterns.Notably,the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays.These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.展开更多
In this paper, we propose a new algorithm for temporally consistent depth map estimation to generate three-dimensional video. The proposed algorithm adaptively computes the matching cost using a temporal weighting fun...In this paper, we propose a new algorithm for temporally consistent depth map estimation to generate three-dimensional video. The proposed algorithm adaptively computes the matching cost using a temporal weighting function, which is obtained by block-based moving object detection and motion estimation with variable block sizes. Experimental results show that the proposed algorithm improves the temporal consistency of the depth video and reduces by about 38% both the flickering artefact in the synthesized view and the number of coding bits for depth video coding.展开更多
This study applies multi-source datasets(i.e.,Baidu Heat Map data,points of interest(POIs)data,and floor area and land use data)and geographically and temporally weighted regression(GTWR)models to elaborate the spatio...This study applies multi-source datasets(i.e.,Baidu Heat Map data,points of interest(POIs)data,and floor area and land use data)and geographically and temporally weighted regression(GTWR)models to elaborate the spatiotemporal relationships between the built environment and urban vibrancy on both weekdays and weekends,using Guangzhou City as a case.First,we verified the spatially and temporally nonstationary nature of the built environment correlates,which have been largely ignored in previous studies based on local regression techniques.The spatially and temporally heterogeneous effects of the built environment on urban vibrancy are then presented and visualized,based on the GTWR results.We found that the elasticity of location(i.e.,distance),land use mix(i.e.,diversity),building intensity and numbers of POIs with various functions(i.e.,density)are different across time(2-h intervals within a day)and space(grids),due to people’s everyday lifestyle,time-space constraints,and geographical context(e.g.,spatial structure).The findings highlight the importance of a better understanding of the local geography on the spatiotemporal relationships for urban planners and local governments so as to put forward decision-making support for fostering and maintaining urban vibrancy.展开更多
To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and ge...To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and geographically and temporally weighted regression(GTWR)model to analyze the spatial-temporal patterns and the corresponding driving mechanisms of its urban-rural coordination since 1990.The results are as follows.First,the urban-rural coupling coordination degree in Northeast China was very low and improved slowly,but its stages of evolution is a good interpretation of the strategic arrangements of China's urbanization.Second,the urban-rural coupling coordination degree in Northeast China had spatial differences and was characterized by central polarization,converging on urban agglomeration,which was high in the south and low in the north.Moreover,the gap between the north and south weakened.Third,the spatial-temporal evolution of the urban-rural coordination relationship in Northeast China was influenced by pulling from the central cities,pushing from rural transformation,and government regulations.The influence intensity of the three mechanisms was weak,but the pulling from the central cities was stronger than that of the other two mechanisms.Furthermore,the spatial difference between the three mechanisms determines the spatial pattern and its evolution of the urban-rural coordination relationship in Northeast China.Fourth,to promote the development of urban-rural coordination in Northeast China,it is essential to advance urban-rural economic correlation,enhance the government^role in regulating and guiding,and adopt different policies for each region in Northeast China.展开更多
Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological...Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological environment of the QTP.However,there are few studies that explored the effects of climate extremes on ecological environment quality of the QTP,and few researchers have made quantitative analysis.Hereby,this paper proposed the Ecological Environmental Quality Index(EEQI)for analyzing the spatial and temporal variation of ecological environment quality on the QTP from 2000 to 2020,and explored the effects of climate extremes on EEQI based on Geographically and Temporally Weighted Regression(GTWR)model.The results showed that the ecological environment quality in QTP was poor in the west,but good in the east.Between 2000 and 2020,the area of EEQI variation was large(34.61%of the total area),but the intensity of EEQI variation was relatively low and occurred mainly by a slightly increasing level(EEQI change range of 0.05-0.1).The overall ecological environment quality of the QTP exhibited spatial and temporal fluctuations,which may be attributed to climate extremes.Significant spatial heterogeneity was observed in the effects of the climate extremes on ecological environment quality.Specifically,the effects of daily temperature range(DTR),number of frost days(FD0),maximum 5-day precipitation(RX5day),and moderate precipitation days(R10)on ecological environment quality were positive in most regions.Furthermore,there were significant temporal differences in the effects of consecutive dry days(CDD),consecutive wet days(CWD),R10,and FD0 on ecological environment quality.These differences may be attributed to variances in ecological environment quality,climate extremes,and vegetation types across different regions.In conclusion,the impact of climate extremes on ecological environment quality exhibits complex patterns.These findings will assist managers in identifying changes in the ecological environment quality of the QTP and addressing the effects of climate extremes.展开更多
Climate change brings new challenges to the sustainable development of agriculture in the new era.Accurately grasping the patterns of climate change impacts on agricultural systems is crucial for ensuring agricultural...Climate change brings new challenges to the sustainable development of agriculture in the new era.Accurately grasping the patterns of climate change impacts on agricultural systems is crucial for ensuring agricultural sustainability and food security.Taking the Loess Plateau(LP),China as an example,this study used a coupling coordination degree model and spatial autocorrelation analysis to portray the spatial and temporal features of crop-cropland coupling relationship from 2000 to 2020 and explored the impact law of climate change through geographically and temporally weighted regression(GTWR).The results were as follows:1)the crop-cropland coupling coordination degree of the LP showed a gradual upward trend from 2000 to 2020,forming a spatial pattern with lower values in the central region and higher values in the surrounding areas.2)There was a positive correlation in the spatial distribution of cropcropland coupling coordination degree in the LP from 2000 to 2020,and the high value-low value(H-L)and low value-low value(L-L)agglomerations continued to expand eastward,while the spatial and temporal evolution of the high value-high value(H-H)and low value-high value(L-H)agglomerations was not obvious.3)The impacts of climatic elements on crop-cropland coupling coordination degree in the LP showed strong heterogeneity in time scales.The inhibitory impacts of summer days(SU)and frost days(FD)accounted for a higher proportion,while the annual average temperature(TEM)had both promoting and inhibiting impacts.The impacts proportion and intensity of extreme heavy precipitation day(R25),continuous drought days(CDD),and annual precipitation(PRE)all experienced significant changes.4)In space,the impacts of SU and FD on the crop-cropland coupling coordination degree varied with latitude and altitude.The adaptability of the LP to R25 gradually strengthened,and the extensions of CDD and increase of PRE led to the increasing inhibition beyond the eastern region of LP,and TEM showed a promoting impact in the Fenwei Plain.As an important grainproducing area in China,the LP should actively deal with the impacts of climate change on the crop-cropland coupling relationship,vigorously safeguard food security,and promote sustainable agricultural development.展开更多
With ongoing global climate change,drought has become the primary threat constraining food security in China.Traditional assessment frameworks based on administrative boundaries or macro-climatic zoning overlook varia...With ongoing global climate change,drought has become the primary threat constraining food security in China.Traditional assessment frameworks based on administrative boundaries or macro-climatic zoning overlook variation in vulnerability affected by key agronomic practices,such as crop phenology and cropping systems,thereby limiting their accuracy.To address this research gap,this study developed and validated a novel drought risk assessment framework based on agricultural cropping zones(single-,double-,and triple-cropping zones).The framework coupled a Geographical and Temporal Neural Network Weighted Regression(GTNNWR)model for forecasting future crop vegetation dynamics with the Standardized Precipitation Evapotranspiration Index(SPEI)to assess drought risk under historical(2001-2020)and projected future(2021-2100)scenarios.The GTNNWR model achieved R^(2) values ranging from 0.72 to 0.82 and RMSE values between 0.11 and 0.14 for NDVI prediction,significantly outperforming conventional models.Historical drought risk assessment revealed that drought events were most frequent during summer and concentrated in single-cropping and double-cropping zones.Future projections indicate a substantial intensification of drought risk.Under the Shared Socioeconomic Pathway(SSP)126 scenario,drought risk is projected to increase in the triple-cropping zones of the middle and lower reaches of the Yangtze River Plain.Under the SSP245 scenario,the frequency of spring and winter droughts is anticipated to rise markedly.Under the SSP585 scenario,drought intensity is projected to intensify in central–eastern single-cropping zones and southwestern double-cropping zones.This assessment framework based on agricultural cropping zones can precisely identify drought risks and facilitate adaptation in agricultural management,such as optimizing irrigation systems and adjusting crop structures.展开更多
Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics o...Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics of urban expansion patterns,based on the intensity index of the urban expansion,the differentiation index of the urban expansion,the fractal dimension index,the land urbanization rate,and the center of gravity model,by taking the Beijing-Tianjin-Hebei(Jing-Jin-Ji)urban agglomeration as an example.We then build the center of gravity-geographically and temporally weighted regression(GTWR)model by coupling the center of gravity model with the GTWR model.Through the analysis of the temporal and spatial patterns and by using the center of gravity-GTWR model,we analyze the driving forces of the urban land expansion and summarize the dominant development modes and core driving forces of the Jing-Jin-Ji urban agglomeration.The results show that:1)Between 1990 and 2015,the expansion intensity of the Jing-Jin-Ji urban agglomeration showed a down-up-down trend,and the peak period was in 2005-2010.Before 2005,high-speed development took place in Beijing,Tianjin,Baoding,and Langfang;after 2005,rapid development was seen in Xingtai and Handan.2)Although the barycenter of cities in the Jing-Jin-Ji urban agglomeration has shown a divergent trend,the local interaction between cities has been enhanced,and the driving forces of urban land expansion have shown a characteristic of spatial spillover.3)The spatial development mode of the Jing-Jin-Ji urban agglomeration has changed from a dual-core development mode to a multi-core development mode,which is made up of three functional cores:the transportation core in the northern part,the economic development core in the central part,and the investment core in the southern part.The synergistic development between each functional core has led to the multi-core development mode.4)The center of gravity-GTWR model combines the analysis of spatial and temporal nonstationarity with urban spatial interaction,and analyzes the urban land expansion as a space-time dynamic system.The results of this study show that the model is a feasible approach in the analysis of the driving forces of urban land expansion.展开更多
The occurrence of the Wenchuan earthquake caused the degradation of regional ecosystems,including vegetation destruction.However,the post-seismic vegetation recovery and its driving forces on the spatial-temporal scal...The occurrence of the Wenchuan earthquake caused the degradation of regional ecosystems,including vegetation destruction.However,the post-seismic vegetation recovery and its driving forces on the spatial-temporal scale are still vague,especially in the severely damaged areas(including Wenchuan,Beichuan,Mianzhu,Shifang,Qingchuan,Maoxian,Anzhou,Dujiangyan,Pingwu and Pengzhou).Here,we detected vegetation recovery in the severely damaged areas by using Ensemble Empirical Mode Decomposition(EEMD)to analyze the time series characteristics of the Enhanced Vegetation Index(EVI),and explored the driving effects of climate,land use types,nighttime light,water system,slope,and clay content on vegetation recovery based on Geographically and Temporally Weighted Regression(GTWR)model.The results indicated that the post-seismic vegetation recovery rate increased rapidly(acceleration>0)but slowed down after 2013.And the areas of best vegetation recovery(EVI increments>0.1)were distributed in the north of the study area,the Minjiang River Basin,and front fault and central fault of the Longmenshan Fault Zone.While the areas with the worst vegetation recovery(EVI increments<-0.1)were concentrated in the southern high-altitude areas and the Chengdu Plain.Additionally,a process attribution of the driving forces of vegetation recovery indicated that accumulated precipitation and maximum temperature promoted vegetation recovery(regression coefficients>0),but the impacts weakened after the earthquake,possibly due to the increase of secondary disasters induced by precipitation and the rise in maximum temperature.The impact of cultivated land on vegetation recovery was mostly positive(regression coefficients>0),which may be related to the implementation of the Grain for Green Project.The nighttime light inhibited vegetation recovery(regression coefficients<0),which could be closely associated with urbanization.The results indicated that more attention should be paid to the nonlinear variations of post-earthquake vegetation recovery trends,and the effects of climatic and anthropogenic factors on vegetation recovery also should not be underestimated.展开更多
The rapid expansion of cities seriously threatens the sustainable development of agriculture in China.Exploring the evolution law and influencing mechanism of agricultural regional system in the process of urbanizatio...The rapid expansion of cities seriously threatens the sustainable development of agriculture in China.Exploring the evolution law and influencing mechanism of agricultural regional system in the process of urbanization is of great significance for promoting sustainable development of agriculture in China.This paper takes the Loess Plateau(LP)as an example,and constructs a research framework to study the effect of urbanization on agricultural regional system through the lens of human-earth interaction,aiming at elucidating the evolutionary characteristics of agricultural regional system and revealing the impact law of urbanization.The results show that:(1)The growth trend of the evolution index of the agricultural regional system in the LP was significant,gradually evolving into a spatial pattern of"high in the north and south,low in the east and west".(2)The hot spot and sub-hot spot zones of the agricultural regional system evolution index in the LP were mainly distributed in the south and north,while the cold spot and sub-cold spot zones were primarily located in the center,east and west.(3)The levels of agricultural mechanization,agricultural land productivity,cropland area,and agricultural labor productivity were the main internal influencing factors of the agricultural regional system in the LP.The obstacle degree of agricultural mechanization level,cropland area,and the proportion of agricultural employees increased over time,while the obstacle degree of agricultural land productivity and grain yield capacity decreased.(4)The impact of population urbanization in the LP showed a spatial pattern of"inhibition in the southeast and promotion in the northwest",the impact of economic urbanization was dominated by inhibition,and the impact of land urbanization showed a spatial pattern of"promotion in the whole and inhibition in the local".This study provides ideas for the comprehensive research on the evolution and influencing factors of agricultural regional system,and offers practical references for achieving sustainable agricultural development in LP.展开更多
The Gravity Recovery and Climate Experiment（GRACE） mission can significantly improve our knowledge of the temporal variability of the Earth＇s gravity field.We obtained monthly gravity field solutions based on varia...The Gravity Recovery and Climate Experiment（GRACE） mission can significantly improve our knowledge of the temporal variability of the Earth＇s gravity field.We obtained monthly gravity field solutions based on variational equations approach from GPS-derived positions of GRACE satellites and K-band range-rate measurements.The impact of different fixed data weighting ratios in temporal gravity field recovery while combining the two types of data was investigated for the purpose of deriving the best combined solution.The monthly gravity field solution obtained through above procedures was named as the Institute of Geodesy and Geophysics（IGG） temporal gravity field models.IGG temporal gravity field models were compared with GRACE Release05（RL05） products in following aspects：（i） the trend of the mass anomaly in China and its nearby regions within 2005-2010; （ii） the root mean squares of the global mass anomaly during 2005-2010; （iii） time-series changes in the mean water storage in the region of the Amazon Basin and the Sahara Desert between 2005 and 2010.The results showed that IGG solutions were almost consistent with GRACE RL05 products in above aspects（i）-（iii）.Changes in the annual amplitude of mean water storage in the Amazon Basin were 14.7 ± 1.2 cm for IGG,17.1 ± 1.3 cm for the Centre for Space Research（CSR）,16.4 ± 0.9 cm for the GeoForschungsZentrum（GFZ） and 16.9 ± 1.2 cm for the Jet Propulsion Laboratory（JPL） in terms of equivalent water height（EWH）,respectively.The root mean squares of the mean mass anomaly in Sahara were 1.2 cm,0.9 cm,0.9 cm and 1.2 cm for temporal gravity field models of IGG,CSR,GFZ and JPL,respectively.Comparison suggested that IGG temporal gravity field solutions were at the same accuracy level with the latest temporal gravity field solutions published by CSR,GFZ and JPL.展开更多
Background Urbanization greatly afects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases.Schistosomiasis,a common parasitic disease transmitted by the snai...Background Urbanization greatly afects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases.Schistosomiasis,a common parasitic disease transmitted by the snail Oncomelania hupensis,is mainly found in areas with population aggregations along rivers and lakes where snails live.Previous studies have suggested that factors related to urbanization may infuence the infection risk of schistosomiasis,but this association remains unclear.This study aimed to analyse the efect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China.Methods County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected.The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)and the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite(NPP-VIIRS).The geographically and temporally weighted regression model(GTWR)was used to quantify the infuence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled.The regression coefcient of urbanization was tested for signifcance(α=0.05),and the infuence of urbanization on schistosomiasis infection risk was analysed over time and across space based on signifcant regression coefcients.Variables studied included climate,soil,vegetation,hydrology and topography.Results The mean regression coefcient for urbanization(0.167)is second only to the leached soil area(0.300),which shows that the urbanization is the most important infuence factors for schistosomiasis infection risk besides leached soil area.The other important variables are distance to the nearest water source(0.165),mean minimum temperature(0.130),broadleaf forest area(0.105),amount of precipitation(0.073),surface temperature(0.066),soil bulk density(0.037)and grassland area(0.031).The infuence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year.During the study period,the signifcant coefcient of urbanization level increased from−0.205 to−0.131.Conclusions The infuence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous.The urbanization does reduce the risk of schistosomiasis infection to some extend,but the strength of this infuence decreases with increasing urbanization.Additionally,the efect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors.This study provides scientifc basis for understanding the infuence of urbanization on schistosomiasis,and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk.展开更多
Carbon dioxide(CO_(2))from road traffic is a non-negligible part of global greenhouse gas(GHG)emissions,and it is a challenge for the world today to accurately estimate road traffic CO_(2)emissions and formulate effec...Carbon dioxide(CO_(2))from road traffic is a non-negligible part of global greenhouse gas(GHG)emissions,and it is a challenge for the world today to accurately estimate road traffic CO_(2)emissions and formulate effective emission reduction policies.Current emission inventories for vehicles have either low-resolution,or limited coverage,and they have not adequately focused on the CO_(2)emission produced by new energy vehicles(NEV)considering fuel life cycle.To fill the research gap,this paper proposed a framework of a high-resolution well-to-wheel(WTW)CO_(2)emission estimation for a full sample of vehicles and revealed the unique CO_(2)emission characteristics of different categories of vehicles combined with vehicle behavior.Based on this,the spatiotemporal characteristics and influencing factors of CO_(2)emissions were analyzed with the geographical and temporal weighted regression(GTWR)model.Finally,the CO_(2)emissions of vehicles under different scenarios are simulated to support the formulation of emission reduction policies.The results show that the distribution of vehicle CO_(2)emissions shows obvious heterogeneity in time,space,and vehicle category.By simply adjusting the existing NEV promotion policy,the emission reduction effect can be improved by 6.5%-13.5%under the same NEV penetration.If combined with changes in power generation structure,it can further release the emission reduction potential of NEVs,which can reduce the current CO_(2)emissions by 78.1%in the optimal scenario.展开更多
Background The disease burden of tuberculosis(TB)was heavy in Hainan Province,China,and the information on transmission patterns was limited with few studies.This atudy aims to further explore the epidemiological char...Background The disease burden of tuberculosis(TB)was heavy in Hainan Province,China,and the information on transmission patterns was limited with few studies.This atudy aims to further explore the epidemiological charac-teristics and influencing factors of TB in Hainan Province,and thereby contribute valuable scientific evidences for TB elimination in Hainan Province.Methods The TB notification data in Hainan Province from 2013 to 2022 were collected from the Chinese National Disease Control Information System Tuberculosis Surveillance System,along with socio-economic data.The spatial-temporal and population distributions were analyzed,and spatial autocorrelation analysis was conducted to explore TB notification rate clustering.In addition,the epidemiological characteristics of the cases among in-country migrants were described,and the delay pattern in seeking medical care was investigated.Finally,a geographically and tem-porally weighted regression(GTWR)model was adopted to analyze the relationship between TB notification rate and socio-economic indicators.The tailored control suggestions in different regions for TB elimination was provided by understanding epidemiological characteristics and risk factors obtained by GTWR.Results From 2013 to 2022,64,042 cases of TB were notified in Hainan Province.The estimated annual percent-age change of TB notification rate in Hainan Province from 2013 to 2020 was-6.88%[95%confidence interval(CI):-5.30%,-3.69%],with higher rates in central and southern regions.The majority of patients were males(76.33%)and farmers(67.80%).Cases among in-country migrants primarily originated from Sichuan(369 cases),Heilongjiang(267 cases),Hunan(236 cases),Guangdong(174 cases),and Guangxi(139 cases),accounting for 53%.The majority(98.83%)of TB cases were notified through passive case finding approaches,with delay in seeking care.The GTWR analysis showed that gross domestic product per capita,the number of medical institutions and health personnel per 10,oo0 people were main factors affecting the high TB notification rates in some regions in Hainan Province.Dif-ferent regional tailored measures such as more TB specialized hospitals were proposed based on the characteristics of each region.Conclusions The notification rate of TB in Hainan Province has been declining overall but still remained high in central and southern regions.Particular attention should be paid to the prevalence of TB among males,farmers,and outof-province migrant populations.The notification rate was also influenced by economic development and medical conditions,indicating the need of more TB specialized hospitals,active surveillance and other tailored prevention and control measures to promote the progress of TB elimination in Hainan Province.展开更多
文摘Root-cause identification plays a vital role in business decision making by providing effective future directions for the organizations.Aspect extraction and sentiment extraction plays a vital role in identifying the rootcauses.This paper proposes the Ensemble based temporal weighting and pareto ranking(ETP)model for Root-cause identification.Aspect extraction is performed based on rules and is followed by opinion identification using the proposed boosted ensemble model.The obtained aspects are validated and ranked using the proposed aspect weighing scheme.Pareto-rule based aspect selection is performed as the final selection mechanism and the results are presented for business decision making.Experiments were performed with the standard five product benchmark dataset.Performances on all five product reviews indicate the effective performance of the proposed model.Comparisons are performed using three standard state-of-the-art models and effectiveness is measured in terms of F-Measure and Detection rates.The results indicate improved performances exhibited by the proposed model with an increase in F-Measure levels at 1%–15%and detection rates at 4%–24%compared to the state-of-the-art models.
基金supported by National Science and Technology Infrastructure Platform National Population and Health Science Data Sharing Service Platform Public Health Science Data Center[NCMI-ZB01N-201905]。
文摘Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever’s temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever’s spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors’influence exhibiting notable spatial and temporal variation.
基金supported by the funding provided by the State Key Laboratory of Hydraulics and Mountain River Engineering(SKHL2210)National Natural Science Foundation of China(42171304)+1 种基金the Sichuan Science and Technology Program(2023YFS0380)Natural Science Foundation of Jiangsu Province of China(BK20242018)。
文摘The Yellow River Basin in Sichuan Province(YRS)is undergoing severe soil erosion and exacerbated ecological vulnerability,which collectively pose formidable challenges for regional water conservation(WC)and sustainable development.While effectively enhancing WC necessitates a comprehensive understanding of its driving factors and corresponding intervention strategies,existing studies have largely neglected the spatiotemporal heterogeneity of both natural and socio-economic drivers.Therefore,this study explored the spatiotemporal heterogeneity of WC drivers in YRS using multi-scale geographically weighted regression(MGWR)and geographically and temporally weighted regression(GTWR)models from an eco-hydrological perspective.We discovered that downstream regions,which are more developed,achieved significantly better WC than upstream regions.The results also demonstrated that the influence of temperature and wind speed is consistently dominant and temporally stable due to climate stability,while the influence of vegetation shifted from negative to positive around 2010,likely indicating greater benefits from understory vegetation.Economic growth positively impacted WC in upstream regions but had a negative effect in the more developed downstream regions.These findings highlight the importance of targeted water conservation strategies,including locally appropriate revegetation,optimization of agricultural and economic structures,and the establishment of eco-compensation mechanisms for ecological conservation and sustainable development.
基金The National Key Research and Development Program of China(No.2022YFC3800201).
文摘This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station planning and development.Data from 159 metro stations in Nanjing,collected over a 14-d period,were analyzed to identify changes in weekday and weekend ridership patterns.The analysis included explanatory variables grouped into three categories:urban spatial variables,socioeconomic vari-ables,and transit service variables.A geographically and temporally weighted regression(GTWR)model was developed,and its performance was compared with that of ordinary least squares(OLS)and geographically weighted regression(GWR)models.The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment.In addition,the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions,revealing distinct patterns.Notably,the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays.These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.
基金supported by the National Research Foundation of Korea Grant funded by the Korea Ministry of Science and Technology under Grant No. 2012-0009228
文摘In this paper, we propose a new algorithm for temporally consistent depth map estimation to generate three-dimensional video. The proposed algorithm adaptively computes the matching cost using a temporal weighting function, which is obtained by block-based moving object detection and motion estimation with variable block sizes. Experimental results show that the proposed algorithm improves the temporal consistency of the depth video and reduces by about 38% both the flickering artefact in the synthesized view and the number of coding bits for depth video coding.
基金Under the auspices of National Natural Science Foundation of China(No.41901191,41930646)Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.311020017)。
文摘This study applies multi-source datasets(i.e.,Baidu Heat Map data,points of interest(POIs)data,and floor area and land use data)and geographically and temporally weighted regression(GTWR)models to elaborate the spatiotemporal relationships between the built environment and urban vibrancy on both weekdays and weekends,using Guangzhou City as a case.First,we verified the spatially and temporally nonstationary nature of the built environment correlates,which have been largely ignored in previous studies based on local regression techniques.The spatially and temporally heterogeneous effects of the built environment on urban vibrancy are then presented and visualized,based on the GTWR results.We found that the elasticity of location(i.e.,distance),land use mix(i.e.,diversity),building intensity and numbers of POIs with various functions(i.e.,density)are different across time(2-h intervals within a day)and space(grids),due to people’s everyday lifestyle,time-space constraints,and geographical context(e.g.,spatial structure).The findings highlight the importance of a better understanding of the local geography on the spatiotemporal relationships for urban planners and local governments so as to put forward decision-making support for fostering and maintaining urban vibrancy.
基金Under the auspices of National Natural Science Foundation of China(No.41401182,41501173)Youth Fund for Humanities and Social Sciences of the Ministry of Education of China(No.19YJC630177)+2 种基金Natural Science Foundation of Heilongjiang Province(No.LH2019D008)University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(No.UNPYSCT-2018194)Talent Introduction Project of Southwest University(No.SWU019020)。
文摘To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and geographically and temporally weighted regression(GTWR)model to analyze the spatial-temporal patterns and the corresponding driving mechanisms of its urban-rural coordination since 1990.The results are as follows.First,the urban-rural coupling coordination degree in Northeast China was very low and improved slowly,but its stages of evolution is a good interpretation of the strategic arrangements of China's urbanization.Second,the urban-rural coupling coordination degree in Northeast China had spatial differences and was characterized by central polarization,converging on urban agglomeration,which was high in the south and low in the north.Moreover,the gap between the north and south weakened.Third,the spatial-temporal evolution of the urban-rural coordination relationship in Northeast China was influenced by pulling from the central cities,pushing from rural transformation,and government regulations.The influence intensity of the three mechanisms was weak,but the pulling from the central cities was stronger than that of the other two mechanisms.Furthermore,the spatial difference between the three mechanisms determines the spatial pattern and its evolution of the urban-rural coordination relationship in Northeast China.Fourth,to promote the development of urban-rural coordination in Northeast China,it is essential to advance urban-rural economic correlation,enhance the government^role in regulating and guiding,and adopt different policies for each region in Northeast China.
基金funded by the key R&D project of the Sichuan Provincial Department of Science and Technology,“Research and Application of Key Technologies for Agricultural Drought Monitoring in Tibet Based on Multi-source Remote Sensing Data”(2021YFQ0042)Tibet Autonomous Region Science and Technology Support Plan Project“Construction and Demonstration Application of Ecological Environment Monitoring Technology System in Tibet Based on Three-Dimensional Remote Sensing Observation Network”(XZ201901-GA-07)。
文摘Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological environment of the QTP.However,there are few studies that explored the effects of climate extremes on ecological environment quality of the QTP,and few researchers have made quantitative analysis.Hereby,this paper proposed the Ecological Environmental Quality Index(EEQI)for analyzing the spatial and temporal variation of ecological environment quality on the QTP from 2000 to 2020,and explored the effects of climate extremes on EEQI based on Geographically and Temporally Weighted Regression(GTWR)model.The results showed that the ecological environment quality in QTP was poor in the west,but good in the east.Between 2000 and 2020,the area of EEQI variation was large(34.61%of the total area),but the intensity of EEQI variation was relatively low and occurred mainly by a slightly increasing level(EEQI change range of 0.05-0.1).The overall ecological environment quality of the QTP exhibited spatial and temporal fluctuations,which may be attributed to climate extremes.Significant spatial heterogeneity was observed in the effects of the climate extremes on ecological environment quality.Specifically,the effects of daily temperature range(DTR),number of frost days(FD0),maximum 5-day precipitation(RX5day),and moderate precipitation days(R10)on ecological environment quality were positive in most regions.Furthermore,there were significant temporal differences in the effects of consecutive dry days(CDD),consecutive wet days(CWD),R10,and FD0 on ecological environment quality.These differences may be attributed to variances in ecological environment quality,climate extremes,and vegetation types across different regions.In conclusion,the impact of climate extremes on ecological environment quality exhibits complex patterns.These findings will assist managers in identifying changes in the ecological environment quality of the QTP and addressing the effects of climate extremes.
基金Under the auspices of Major Program of National Natural Science Foundation of China(No.42293271)Alliance of International Science Organizations(No.ANSO-PA-2023-16)。
文摘Climate change brings new challenges to the sustainable development of agriculture in the new era.Accurately grasping the patterns of climate change impacts on agricultural systems is crucial for ensuring agricultural sustainability and food security.Taking the Loess Plateau(LP),China as an example,this study used a coupling coordination degree model and spatial autocorrelation analysis to portray the spatial and temporal features of crop-cropland coupling relationship from 2000 to 2020 and explored the impact law of climate change through geographically and temporally weighted regression(GTWR).The results were as follows:1)the crop-cropland coupling coordination degree of the LP showed a gradual upward trend from 2000 to 2020,forming a spatial pattern with lower values in the central region and higher values in the surrounding areas.2)There was a positive correlation in the spatial distribution of cropcropland coupling coordination degree in the LP from 2000 to 2020,and the high value-low value(H-L)and low value-low value(L-L)agglomerations continued to expand eastward,while the spatial and temporal evolution of the high value-high value(H-H)and low value-high value(L-H)agglomerations was not obvious.3)The impacts of climatic elements on crop-cropland coupling coordination degree in the LP showed strong heterogeneity in time scales.The inhibitory impacts of summer days(SU)and frost days(FD)accounted for a higher proportion,while the annual average temperature(TEM)had both promoting and inhibiting impacts.The impacts proportion and intensity of extreme heavy precipitation day(R25),continuous drought days(CDD),and annual precipitation(PRE)all experienced significant changes.4)In space,the impacts of SU and FD on the crop-cropland coupling coordination degree varied with latitude and altitude.The adaptability of the LP to R25 gradually strengthened,and the extensions of CDD and increase of PRE led to the increasing inhibition beyond the eastern region of LP,and TEM showed a promoting impact in the Fenwei Plain.As an important grainproducing area in China,the LP should actively deal with the impacts of climate change on the crop-cropland coupling relationship,vigorously safeguard food security,and promote sustainable agricultural development.
文摘With ongoing global climate change,drought has become the primary threat constraining food security in China.Traditional assessment frameworks based on administrative boundaries or macro-climatic zoning overlook variation in vulnerability affected by key agronomic practices,such as crop phenology and cropping systems,thereby limiting their accuracy.To address this research gap,this study developed and validated a novel drought risk assessment framework based on agricultural cropping zones(single-,double-,and triple-cropping zones).The framework coupled a Geographical and Temporal Neural Network Weighted Regression(GTNNWR)model for forecasting future crop vegetation dynamics with the Standardized Precipitation Evapotranspiration Index(SPEI)to assess drought risk under historical(2001-2020)and projected future(2021-2100)scenarios.The GTNNWR model achieved R^(2) values ranging from 0.72 to 0.82 and RMSE values between 0.11 and 0.14 for NDVI prediction,significantly outperforming conventional models.Historical drought risk assessment revealed that drought events were most frequent during summer and concentrated in single-cropping and double-cropping zones.Future projections indicate a substantial intensification of drought risk.Under the Shared Socioeconomic Pathway(SSP)126 scenario,drought risk is projected to increase in the triple-cropping zones of the middle and lower reaches of the Yangtze River Plain.Under the SSP245 scenario,the frequency of spring and winter droughts is anticipated to rise markedly.Under the SSP585 scenario,drought intensity is projected to intensify in central–eastern single-cropping zones and southwestern double-cropping zones.This assessment framework based on agricultural cropping zones can precisely identify drought risks and facilitate adaptation in agricultural management,such as optimizing irrigation systems and adjusting crop structures.
基金National Natural Science Foundation of China,No.41571384Land Resources Survey and Evaluation Project of Ministry of Land and Resources of China,No.DCPJ161207-01+2 种基金Fund for Fostering Talents in Basic Science of National Natural Science Foundation of China,No.J1103409Key Program of National Natural Science Foundation of China,No.71433008Programme of Excellent Young Scientists of the Institute of Geographic Sciences and Natural Resources Research,CAS。
文摘Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics of urban expansion patterns,based on the intensity index of the urban expansion,the differentiation index of the urban expansion,the fractal dimension index,the land urbanization rate,and the center of gravity model,by taking the Beijing-Tianjin-Hebei(Jing-Jin-Ji)urban agglomeration as an example.We then build the center of gravity-geographically and temporally weighted regression(GTWR)model by coupling the center of gravity model with the GTWR model.Through the analysis of the temporal and spatial patterns and by using the center of gravity-GTWR model,we analyze the driving forces of the urban land expansion and summarize the dominant development modes and core driving forces of the Jing-Jin-Ji urban agglomeration.The results show that:1)Between 1990 and 2015,the expansion intensity of the Jing-Jin-Ji urban agglomeration showed a down-up-down trend,and the peak period was in 2005-2010.Before 2005,high-speed development took place in Beijing,Tianjin,Baoding,and Langfang;after 2005,rapid development was seen in Xingtai and Handan.2)Although the barycenter of cities in the Jing-Jin-Ji urban agglomeration has shown a divergent trend,the local interaction between cities has been enhanced,and the driving forces of urban land expansion have shown a characteristic of spatial spillover.3)The spatial development mode of the Jing-Jin-Ji urban agglomeration has changed from a dual-core development mode to a multi-core development mode,which is made up of three functional cores:the transportation core in the northern part,the economic development core in the central part,and the investment core in the southern part.The synergistic development between each functional core has led to the multi-core development mode.4)The center of gravity-GTWR model combines the analysis of spatial and temporal nonstationarity with urban spatial interaction,and analyzes the urban land expansion as a space-time dynamic system.The results of this study show that the model is a feasible approach in the analysis of the driving forces of urban land expansion.
基金funded by the key R&D project of Sichuan Provincial Department of Science and Technology,"Research and Application of Key Technologies for Agricultural Drought Monitoring in Tibet Based on Multi-source Remote Sensing Data"(2021YFQ0042)Tibet Autonomous Region Science and Technology Support Plan Project"Construction and Demonstration Application of Ecological Environment Monitoring Technology System in Tibet Based on Three-dimensional Remote Sensing Observation Network”(XZ201901-GA-07)。
文摘The occurrence of the Wenchuan earthquake caused the degradation of regional ecosystems,including vegetation destruction.However,the post-seismic vegetation recovery and its driving forces on the spatial-temporal scale are still vague,especially in the severely damaged areas(including Wenchuan,Beichuan,Mianzhu,Shifang,Qingchuan,Maoxian,Anzhou,Dujiangyan,Pingwu and Pengzhou).Here,we detected vegetation recovery in the severely damaged areas by using Ensemble Empirical Mode Decomposition(EEMD)to analyze the time series characteristics of the Enhanced Vegetation Index(EVI),and explored the driving effects of climate,land use types,nighttime light,water system,slope,and clay content on vegetation recovery based on Geographically and Temporally Weighted Regression(GTWR)model.The results indicated that the post-seismic vegetation recovery rate increased rapidly(acceleration>0)but slowed down after 2013.And the areas of best vegetation recovery(EVI increments>0.1)were distributed in the north of the study area,the Minjiang River Basin,and front fault and central fault of the Longmenshan Fault Zone.While the areas with the worst vegetation recovery(EVI increments<-0.1)were concentrated in the southern high-altitude areas and the Chengdu Plain.Additionally,a process attribution of the driving forces of vegetation recovery indicated that accumulated precipitation and maximum temperature promoted vegetation recovery(regression coefficients>0),but the impacts weakened after the earthquake,possibly due to the increase of secondary disasters induced by precipitation and the rise in maximum temperature.The impact of cultivated land on vegetation recovery was mostly positive(regression coefficients>0),which may be related to the implementation of the Grain for Green Project.The nighttime light inhibited vegetation recovery(regression coefficients<0),which could be closely associated with urbanization.The results indicated that more attention should be paid to the nonlinear variations of post-earthquake vegetation recovery trends,and the effects of climatic and anthropogenic factors on vegetation recovery also should not be underestimated.
基金funded by the Major Program of National Natural Science Foundation of China(Grant No.42293271)the National Natural Science Foundation of China(Grant No.42171208).
文摘The rapid expansion of cities seriously threatens the sustainable development of agriculture in China.Exploring the evolution law and influencing mechanism of agricultural regional system in the process of urbanization is of great significance for promoting sustainable development of agriculture in China.This paper takes the Loess Plateau(LP)as an example,and constructs a research framework to study the effect of urbanization on agricultural regional system through the lens of human-earth interaction,aiming at elucidating the evolutionary characteristics of agricultural regional system and revealing the impact law of urbanization.The results show that:(1)The growth trend of the evolution index of the agricultural regional system in the LP was significant,gradually evolving into a spatial pattern of"high in the north and south,low in the east and west".(2)The hot spot and sub-hot spot zones of the agricultural regional system evolution index in the LP were mainly distributed in the south and north,while the cold spot and sub-cold spot zones were primarily located in the center,east and west.(3)The levels of agricultural mechanization,agricultural land productivity,cropland area,and agricultural labor productivity were the main internal influencing factors of the agricultural regional system in the LP.The obstacle degree of agricultural mechanization level,cropland area,and the proportion of agricultural employees increased over time,while the obstacle degree of agricultural land productivity and grain yield capacity decreased.(4)The impact of population urbanization in the LP showed a spatial pattern of"inhibition in the southeast and promotion in the northwest",the impact of economic urbanization was dominated by inhibition,and the impact of land urbanization showed a spatial pattern of"promotion in the whole and inhibition in the local".This study provides ideas for the comprehensive research on the evolution and influencing factors of agricultural regional system,and offers practical references for achieving sustainable agricultural development in LP.
基金funded by the Major National Scientific Research Plan(2013CB733305,2012CB957703)the National Natural Science Foundation of China(41174066,41131067,41374087,41431070)
文摘The Gravity Recovery and Climate Experiment（GRACE） mission can significantly improve our knowledge of the temporal variability of the Earth＇s gravity field.We obtained monthly gravity field solutions based on variational equations approach from GPS-derived positions of GRACE satellites and K-band range-rate measurements.The impact of different fixed data weighting ratios in temporal gravity field recovery while combining the two types of data was investigated for the purpose of deriving the best combined solution.The monthly gravity field solution obtained through above procedures was named as the Institute of Geodesy and Geophysics（IGG） temporal gravity field models.IGG temporal gravity field models were compared with GRACE Release05（RL05） products in following aspects：（i） the trend of the mass anomaly in China and its nearby regions within 2005-2010; （ii） the root mean squares of the global mass anomaly during 2005-2010; （iii） time-series changes in the mean water storage in the region of the Amazon Basin and the Sahara Desert between 2005 and 2010.The results showed that IGG solutions were almost consistent with GRACE RL05 products in above aspects（i）-（iii）.Changes in the annual amplitude of mean water storage in the Amazon Basin were 14.7 ± 1.2 cm for IGG,17.1 ± 1.3 cm for the Centre for Space Research（CSR）,16.4 ± 0.9 cm for the GeoForschungsZentrum（GFZ） and 16.9 ± 1.2 cm for the Jet Propulsion Laboratory（JPL） in terms of equivalent water height（EWH）,respectively.The root mean squares of the mean mass anomaly in Sahara were 1.2 cm,0.9 cm,0.9 cm and 1.2 cm for temporal gravity field models of IGG,CSR,GFZ and JPL,respectively.Comparison suggested that IGG temporal gravity field solutions were at the same accuracy level with the latest temporal gravity field solutions published by CSR,GFZ and JPL.
基金supported by the National Natural Science Foundation of China(81973102)Autonomous and Controllable Special Project for Surveying and Mapping of China(Grant No.816-517).
文摘Background Urbanization greatly afects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases.Schistosomiasis,a common parasitic disease transmitted by the snail Oncomelania hupensis,is mainly found in areas with population aggregations along rivers and lakes where snails live.Previous studies have suggested that factors related to urbanization may infuence the infection risk of schistosomiasis,but this association remains unclear.This study aimed to analyse the efect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China.Methods County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected.The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)and the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite(NPP-VIIRS).The geographically and temporally weighted regression model(GTWR)was used to quantify the infuence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled.The regression coefcient of urbanization was tested for signifcance(α=0.05),and the infuence of urbanization on schistosomiasis infection risk was analysed over time and across space based on signifcant regression coefcients.Variables studied included climate,soil,vegetation,hydrology and topography.Results The mean regression coefcient for urbanization(0.167)is second only to the leached soil area(0.300),which shows that the urbanization is the most important infuence factors for schistosomiasis infection risk besides leached soil area.The other important variables are distance to the nearest water source(0.165),mean minimum temperature(0.130),broadleaf forest area(0.105),amount of precipitation(0.073),surface temperature(0.066),soil bulk density(0.037)and grassland area(0.031).The infuence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year.During the study period,the signifcant coefcient of urbanization level increased from−0.205 to−0.131.Conclusions The infuence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous.The urbanization does reduce the risk of schistosomiasis infection to some extend,but the strength of this infuence decreases with increasing urbanization.Additionally,the efect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors.This study provides scientifc basis for understanding the infuence of urbanization on schistosomiasis,and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk.
基金supported by"Pioneer"and"Leading Goose"R&D Program of Zhejiang(2023C03155)the National Natural Science Foundation of China(72361137006,52131202,and 92046011)+1 种基金the Natural Science Foundation of Zhejiang Province(LR23E080002)Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies.
文摘Carbon dioxide(CO_(2))from road traffic is a non-negligible part of global greenhouse gas(GHG)emissions,and it is a challenge for the world today to accurately estimate road traffic CO_(2)emissions and formulate effective emission reduction policies.Current emission inventories for vehicles have either low-resolution,or limited coverage,and they have not adequately focused on the CO_(2)emission produced by new energy vehicles(NEV)considering fuel life cycle.To fill the research gap,this paper proposed a framework of a high-resolution well-to-wheel(WTW)CO_(2)emission estimation for a full sample of vehicles and revealed the unique CO_(2)emission characteristics of different categories of vehicles combined with vehicle behavior.Based on this,the spatiotemporal characteristics and influencing factors of CO_(2)emissions were analyzed with the geographical and temporal weighted regression(GTWR)model.Finally,the CO_(2)emissions of vehicles under different scenarios are simulated to support the formulation of emission reduction policies.The results show that the distribution of vehicle CO_(2)emissions shows obvious heterogeneity in time,space,and vehicle category.By simply adjusting the existing NEV promotion policy,the emission reduction effect can be improved by 6.5%-13.5%under the same NEV penetration.If combined with changes in power generation structure,it can further release the emission reduction potential of NEVs,which can reduce the current CO_(2)emissions by 78.1%in the optimal scenario.
文摘Background The disease burden of tuberculosis(TB)was heavy in Hainan Province,China,and the information on transmission patterns was limited with few studies.This atudy aims to further explore the epidemiological charac-teristics and influencing factors of TB in Hainan Province,and thereby contribute valuable scientific evidences for TB elimination in Hainan Province.Methods The TB notification data in Hainan Province from 2013 to 2022 were collected from the Chinese National Disease Control Information System Tuberculosis Surveillance System,along with socio-economic data.The spatial-temporal and population distributions were analyzed,and spatial autocorrelation analysis was conducted to explore TB notification rate clustering.In addition,the epidemiological characteristics of the cases among in-country migrants were described,and the delay pattern in seeking medical care was investigated.Finally,a geographically and tem-porally weighted regression(GTWR)model was adopted to analyze the relationship between TB notification rate and socio-economic indicators.The tailored control suggestions in different regions for TB elimination was provided by understanding epidemiological characteristics and risk factors obtained by GTWR.Results From 2013 to 2022,64,042 cases of TB were notified in Hainan Province.The estimated annual percent-age change of TB notification rate in Hainan Province from 2013 to 2020 was-6.88%[95%confidence interval(CI):-5.30%,-3.69%],with higher rates in central and southern regions.The majority of patients were males(76.33%)and farmers(67.80%).Cases among in-country migrants primarily originated from Sichuan(369 cases),Heilongjiang(267 cases),Hunan(236 cases),Guangdong(174 cases),and Guangxi(139 cases),accounting for 53%.The majority(98.83%)of TB cases were notified through passive case finding approaches,with delay in seeking care.The GTWR analysis showed that gross domestic product per capita,the number of medical institutions and health personnel per 10,oo0 people were main factors affecting the high TB notification rates in some regions in Hainan Province.Dif-ferent regional tailored measures such as more TB specialized hospitals were proposed based on the characteristics of each region.Conclusions The notification rate of TB in Hainan Province has been declining overall but still remained high in central and southern regions.Particular attention should be paid to the prevalence of TB among males,farmers,and outof-province migrant populations.The notification rate was also influenced by economic development and medical conditions,indicating the need of more TB specialized hospitals,active surveillance and other tailored prevention and control measures to promote the progress of TB elimination in Hainan Province.
