Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric ma...Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric mantle(SCLM)beneath the northern Tan-Lu fault zone(TLFZ)during the Cenozoic.The Qingyuan peridotites are dominated by spinel lherzolites with moderate-Mg^(#)olivines(89.4 to 91.2),suggesting that the regional SCLM is mainly transitional and fertile.Light rare earth element(LREE)-depleted,slightly depleted and enriched clinopyroxenes(Cpx)are identified in different peridotites.Chemical compositions of the LREE-enriched Cpx and the presence of phlogopite suggest that the Qingyuan SCLM has experienced silicate-related metasomatism.The synthesis of available mineral chemical data of the mantle xenoliths across the NCC confirms the SCLM beneath the NCC is highly heterogeneous in time and space.The Mesozoic–Cenozoic SCLM beneath the TLFZ and neighboring regions are more fertile and thinner than that beneath the region away from the fault zone.The fertile and refractory peridotite xenoliths experienced varying degrees of silicate and carbonatite metasomatism,respectively.The spatial-temporal lithospheric mantle heterogeneity in composition,age and thickness suggest that the trans-lithosphere fault zone played an important role in heterogeneous replacement of refractory cratonic lithospheric mantle.展开更多
To conduct a comprehensive analysis of the current status of water environment quality in Yilong Lake,a systematic study was undertaken to characterize the evolution of water quality.This study utilized monthly data o...To conduct a comprehensive analysis of the current status of water environment quality in Yilong Lake,a systematic study was undertaken to characterize the evolution of water quality.This study utilized monthly data on water quality indicators collected from three monitoring sections of Yilong Lake between 2016 and 2023,employing the Mann-Kendall trend test and ArcGIS spatial interpolation technique.The results indicated that the five-day biochemical oxygen demand(BOD5),total nitrogen(TN),and chlorophyll a(Chla)exhibited an overall increasing trend,whereas other indicators demonstrated a decreasing trend.The permanganate index(PI),chemical oxygen demand(COD),TN,and Chla were observed in the following order:east of the lake>middle of the lake>west of the lake.In contrast,the BOD5 and total phosphorus(TP)were ranked as west of the lake>east of the lake>middle of the lake.Additionally,ammonia nitrogen(NH3-N)was found to be in the order of east of the lake>west of the lake>middle of the lake,while transparency was ranked as west of the lake>middle of the lake>east of the lake.Urban domestic sewage,effluent from industrial parks,domestic waste generated by rural residents’production and daily activities,agricultural waste,wastewater from decentralized farming,domestic sewage,and point source discharges from the soybean processing industry are the primary contributors to the exceedance of water quality standards.The enhancement of a precise pollution control system,along with the regulation of pollution sources and the interception of pollutants,can significantly diminish the pollution load entering the lake.This approach is essential for the protection and restoration of river and lake ecosystems,thereby facilitating the gradual recovery of their ecological functions.Additionally,the implementation of ecological water replenishment and the recycling of water resources can improve the capacity of the water environment.Furthermore,bolstering scientific and technological support,as well as comprehensive supervision and assurance measures,is crucial to ensuring that water quality remains stable and adheres to established standards.展开更多
Five sequences of deep fluid injections at the Pohang Enhanced Geothermal System(EGS)triggered an ML 5.4 earthquake on November 15,2017.The foreshock-mainshock-aftershock sequence was monitored using dense seismic net...Five sequences of deep fluid injections at the Pohang Enhanced Geothermal System(EGS)triggered an ML 5.4 earthquake on November 15,2017.The foreshock-mainshock-aftershock sequence was monitored using dense seismic networks.Between November 14,2017,and May 31,2023,this study detected 5,169 earthquakes and determined the relative locations of 4,902 earthquakes,including seven foreshocks.A heterogeneous subsurface fault model is proposed,in which the fault is reactivated by induced and triggered earthquakes.The earthquake frequency decreased after the mainshock,with a temporary increase after the ML 4.6 event on February 10,2018.The magnitude-frequency b-values are significantly lower than those for the background seismicity in the Korean Peninsula and those for the 2016 Gyeongju earthquake sequence.The aftershock decay rate p-values are within the range of typical values,regardless of decreasing over time.The earthquake focal mechanisms exhibit a predominance of strike-slip components,whereas the slip tendency indicates a higher value in reverse faulting geometry,implying stress redistribution after the mainshock.The seismic landscape with ongoing aftershock activity after the 2017 Pohang earthquake underscores the importance of sustained,long-term seismic monitoring to comprehensively grasp the implications of the new seismic environment for seismic hazards in the area.展开更多
Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smo...Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smoother and more precise human motion prediction remains a challenge.To address these issues,a robust human motion prediction method via integration of spatial and temporal cues(RISTC)has been proposed.This method captures sufficient spatio-temporal correlation of the observable sequence of human poses by utilizing the spatio-temporal mixed feature extractor(MFE).In multi-layer MFEs,the channel-graph united attention blocks extract the augmented spatial features of the human poses in the channel and spatial dimension.Additionally,multi-scale temporal blocks have been designed to effectively capture complicated and highly dynamic temporal information.Our experiments on the Human3.6M and Carnegie Mellon University motion capture(CMU Mocap)datasets show that the proposed network yields higher prediction accuracy than the state-of-the-art methods.展开更多
Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analy...Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.展开更多
Tuberculosis(TB)remained the first leading cause of death from a single infectious agent worldwide in 2023,resulting in nearly twice as many deaths as those caused by the human immunodeficiency virus/acquired immune d...Tuberculosis(TB)remained the first leading cause of death from a single infectious agent worldwide in 2023,resulting in nearly twice as many deaths as those caused by the human immunodeficiency virus/acquired immune deficiency syndrome.An estimated 10.8 million TB cases were reported globally in 2023,with approximately 1.25 million associated deaths.In China,which ranks third in the global TB burden,there were approximately 741,000 new cases and 25,000 deaths in 2023^([1]).TB poses a significant threat to human health worldwide.展开更多
Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 1...Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 10 concentration and its relationship with meteorological factors were studied.The results show that from the perspective of temporal variation,the annual average of PM 10 concentration in Yantai City tended to decrease year by year.It was high in winter and spring and low in summer and autumn.In terms of monthly variation,the changing curve is U-shaped,and it was high in December and January but low in July and August.During a day,PM 10 concentration had two peaks.The first peak appeared approximately from 09:00 to 11:00,and the second peak can be found from 21:00 to 23:00.From the perspective of spatial distribution,PM 10 concentration was the highest in the development area and Fushan District.It was the highest in the west,followed by the east,while it was the lowest in the middle.The spatial difference rate was the highest in summer.Average temperature,relative humidity,wind speed and precipitation were the main meteorological factors influencing PM 10 concentration in Yantai area.PM 10 concentration was negatively correlated with average temperature and relative humidity,and the correlation was the most significant from June to October.It was negatively correlated with wind speed and precipitation,and the correlation was different in various months.The negative correlation was significant in summer and winter.展开更多
Predicting human motion based on historical motion sequences is a fundamental problem in computer vision,which is at the core of many applications.Existing approaches primarily focus on encoding spatial dependencies a...Predicting human motion based on historical motion sequences is a fundamental problem in computer vision,which is at the core of many applications.Existing approaches primarily focus on encoding spatial dependencies among human joints while ignoring the temporal cues and the complex relationships across non-consecutive frames.These limitations hinder the model’s ability to generate accurate predictions over longer time horizons and in scenarios with complex motion patterns.To address the above problems,we proposed a novel multi-level spatial and temporal learning model,which consists of a Cross Spatial Dependencies Encoding Module(CSM)and a Dynamic Temporal Connection Encoding Module(DTM).Specifically,the CSM is designed to capture complementary local and global spatial dependent information at both the joint level and the joint pair level.We further present DTM to encode diverse temporal evolution contexts and compress motion features to a deep level,enabling the model to capture both short-term and long-term dependencies efficiently.Extensive experiments conducted on the Human 3.6M and CMU Mocap datasets demonstrate that our model achieves state-of-the-art performance in both short-term and long-term predictions,outperforming existing methods by up to 20.3% in accuracy.Furthermore,ablation studies confirm the significant contributions of the CSM and DTM in enhancing prediction accuracy.展开更多
This study investigated the spatio-temporal variation characteristics of ecosystem service value(ESV)alongside its driving influencing factors,thereby offering valuable theoretical insights for the sustainable develop...This study investigated the spatio-temporal variation characteristics of ecosystem service value(ESV)alongside its driving influencing factors,thereby offering valuable theoretical insights for the sustainable development of Jingzhou City,Hubei Province.Based on the land use data for Jingzhou City from 2000 to 2020,this study quantified the value of the ecological environment using the equivalent factor method.Furthermore,it analyzed and elucidated the spatio-temporal heterogeneity and driving mechanisms of ecosystem services in Jingzhou City.The results indicated that between 2000 and 2020,cultivated land(66.40%)and water area(18.82%)were the predominant land use types in Jingzhou City.The areas of water area and construction land exhibited a growth trend during this period.Construction land had the highest rate of land use change,followed by water area and cultivated land.Land use transitions primarily occurred between cultivated land and water area,as well as between cultivated land and construction land.The total value of ecosystem services in Jingzhou City increased by 165.07%from 2000 to 2020.ESV exhibited an upward trend from 2000 to 2015,followed by a gradual decline from 2015 to 2020.The ranking of individual ecosystem services,in descending order,was as follows:regulation services,supporting services,provisioning services,and cultural services.High-value ESV areas were predominantly situated in the water area of Lake Honghu,while low-value regions were mainly found in the cultivated land in the central and western parts of Jingzhou City.The spatial differentiation of ESV in Jingzhzou City was influenced by both natural and socio-economic factors,with natural factors exerting a more significant impact than socioeconomic factors.Specifically,the Normalized Difference Vegetation Index(NDVI)was the dominant environmental factor,while GDP plays a synergistic role.展开更多
To overcome the deficiencies of single-modal emotion recognition based on facial expression or bodily posture in natural scenes,a spatial guidance and temporal enhancement(SG-TE)network is proposed for facial-bodily e...To overcome the deficiencies of single-modal emotion recognition based on facial expression or bodily posture in natural scenes,a spatial guidance and temporal enhancement(SG-TE)network is proposed for facial-bodily emotion recognition.First,ResNet50,DNN and spatial ransformer models are used to capture facial texture vectors,bodily skeleton vectors and wholebody geometric vectors,and an intraframe correlation attention guidance(S-CAG)mechanism,which guides the facial texture vector and the bodily skeleton vector by the whole-body geometric vector,is designed to exploit the spatial potential emotional correlation between face and posture.Second,an interframe significant segment enhancement(T-SSE)structure is embedded into a temporal transformer to enhance high emotional intensity frame information and avoid emotional asynchrony.Finally,an adaptive weight assignment(M-AWA)strategy is constructed to realise facial-bodily fusion.The experimental results on the BabyRobot Emotion Dataset(BRED)and Context-Aware Emotion Recognition(CAER)dataset indicate that the proposed network reaches accuracies of 81.61%and 89.39%,which are 9.61%and 9.46%higher than those of the baseline network,respectively.Compared with the state-of-the-art methods,the proposed method achieves 7.73%and 20.57%higher accuracy than single-modal methods based on facial expression or bodily posture,respectively,and 2.16%higher accuracy than the dual-modal methods based on facial-bodily fusion.Therefore,the proposed method,which adaptively fuses the complementary information of face and posture,improves the quality of emotion recognition in real-world scenarios.展开更多
Based on the data of meteorological elements and concentration of negative ions in the county town station,Luguhe station and Yunjishan station during 2020-2024,the temporal and spatial variations in the concentration...Based on the data of meteorological elements and concentration of negative ions in the county town station,Luguhe station and Yunjishan station during 2020-2024,the temporal and spatial variations in the concentration of negative ions and their influencing factors in Xinfeng County were analyzed.The results show that the concentration of negative ions was the highest in summer,followed by spring;it was lower in autumn and the lowest in winter.In terms of diurnal variations,it was higher in the early morning and night,and lower in the noon and afternoon,which was closely related to the diurnal variations of human activities and meteorological conditions.The factors that affect the concentration of negative ions in the air are more complex.Besides meteorological factors,vegetation,altitude,human activities and other factors should be considered.展开更多
Recently,information acquired at the canopy top,such as spectral and textural data,has been widely used to estimate plant nitrogen(N)accumulation(PNA).The response of crops to N uptake involves not only changes in hor...Recently,information acquired at the canopy top,such as spectral and textural data,has been widely used to estimate plant nitrogen(N)accumulation(PNA).The response of crops to N uptake involves not only changes in horizontal canopy top information but also an increase in vertical plant height(PH).It remains unclear whether the fusion of spectral indices with PH can improve the estimation performance of PNA models based on spectral remote sensing across different growth stages.展开更多
High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume sion disper-in complex terrain.However,their high computational cost makes them impractical for applications requiri...High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume sion disper-in complex terrain.However,their high computational cost makes them impractical for applications requiring rapid responses or iterative processes,such as optimization,uncertainty quantification,or inverse modeling.To address this challenge,this work introduces the Dual-Stage Temporal Three-dimensional UNet Super-resolution(DST3D-UNet-SR)model,a highly efficient deep learning model for plume dispersion predictions.DST3D-UNet-SR is composed of two sequential modules:the temporal module(TM),which predicts the transient evolution of a plume in complex terrain from low-resolution temporal data,and the spatial refinement module(SRM),which subsequently enhances the spatial resolution of the TM predictions.We train DST3D-UNet-SR using a comprehensive dataset derived from high-resolution large eddy simulations(LES)of plume transport.We propose the DST3D-UNet-SR model to significantly accelerate LES of three-dimensional(3D)plume dispersion by three orders of magnitude.Additionally,the model demonstrates the ability to dynamically adapt to evolving conditions through the incorporation of new observational data,substantially improving prediction accuracy in high-concentration regions near the source.展开更多
Smart grid substation operations often take place in hazardous environments and pose significant threats to the safety of power personnel.Relying solely on manual supervision can lead to inadequate oversight.In respon...Smart grid substation operations often take place in hazardous environments and pose significant threats to the safety of power personnel.Relying solely on manual supervision can lead to inadequate oversight.In response to the demand for technology to identify improper operations in substation work scenarios,this paper proposes a substation safety action recognition technology to avoid the misoperation and enhance the safety management.In general,this paper utilizes a dual-branch transformer network to extract spatial and temporal information from the video dataset of operational behaviors in complex substation environments.Firstly,in order to capture the spatial-temporal correlation of people's behaviors in smart grid substation,we devise a sparse attention module and a segmented linear attention module that are embedded into spatial branch transformer and temporal branch transformer respectively.To avoid the redundancy of spatial and temporal information,we fuse the temporal and spatial features using a tensor decomposition fusion module by a decoupled manner.Experimental results indicate that our proposed method accurately detects improper operational behaviors in substation work scenarios,outperforming other existing methods in terms of detection and recognition accuracy.展开更多
The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also h...The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.展开更多
[Objective] The paper aimed to reflect the spatial pattern and temporal and spatial evolution characteristics, the differences between inter-regional tourism economy was measured from the quality aspect, which provide...[Objective] The paper aimed to reflect the spatial pattern and temporal and spatial evolution characteristics, the differences between inter-regional tourism economy was measured from the quality aspect, which provided a reference for the local governments in the future tourism development. [Method] Using the location entropy methods, three time periods side of tourism-related date of 2000, 2005, 2007 were selected, from the angle of the spatial pattern and the evolution of the differences within the different scales, the spatial and temporal evolution characteristics of the economic development level of Jiangsu were analysed. [Result] The results showed that from the aspect of spatial evolution pattern, as time goes on, the economic development of Jiangsu tourism has experienced morphological evolution of concentration- dispersion decrease-stability; when it comes to the development of the tourism economy, in recent years, the overall gap between the tourism economy in Jiangsu did not widen, the gap mainly led by the region one after another. According to their volatility, it will be divided into four categories: A Stable type (Wuxi, Xuzhou, Lianyungang and Taizhou), B Increasing type (Huai’an), C Fluctuations type (Nanjing, Changzhou, Suzhou and Yangzhou) and D Depression type (Nantong, Yancheng, Zhenjiang and Suqian). [Conclusion] Location entropy was quoted into tourism economic analysis, the method was simple and easy to understand, the result was accurate and convincing, which provided a reference for travel economic development and investment decision-making of Jiangsu.展开更多
This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employ...This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse,the research mapped out the progression and distribution of aging demographics.Furthermore,the study delved into the influencing factors of aging using an optimal parameters-based geographical detector.Results indicate a deepening degree of population aging in Henan Province,transitioning from an adult type to an old type structure.There is a marked positive spatial correlation among counties,with high-value aging areas initially decreasing,then increasing,and notably spreading from the central to the central and southern regions of the province.The center of gravity for population aging,specifically around Changge City and Xuchang City,exhibits a trajectory moving southeast before shifting northwest.Factor detection reveals that in 2000,2010,and 2020,the elderly dependency ratio predominantly influences the aging trend,with explanatory powers of 88.4%,87.9%,and 90.9%,respectively.Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province,reaching 97.3%,97.0%,and 97.4%,respectively.展开更多
The study of sulfur hexafluoride(SF6) discharge is vital for its application in gas-insulated equipment. Direct current partial discharge(PD) may cause SF6 decomposition, and the decomposed products of SF6, such as F ...The study of sulfur hexafluoride(SF6) discharge is vital for its application in gas-insulated equipment. Direct current partial discharge(PD) may cause SF6 decomposition, and the decomposed products of SF6, such as F atoms, play a dominant role in the breakdown of insulation systems. In this study, the PD caused by metal protrusion defects is simulated by a needle-plate electrode using pulsed high voltage in SF6/Ar mixtures. The spatial and temporal characteristics of SF6/Ar plasma are analyzed by measuring the emission spectra of F and Ar atoms, which are important for understanding the characteristics of PD. The spatial resolved results show that both F and Ar atom spectral intensities increase first from the plate anode to the needle and then decrease under the conditions of a background pressure of400 Pa, peak voltage of-1000 V, frequency of 2 kHz, pulse width of 60 μs, and electrode gap of 5-9 mm. However, the distribution characteristics of F and Ar are significantly different. The temporal distribution results show that the spectral intensity of Ar decreasesfirst and then increases slowly, while the spectral intensity of F increases slowly for the duration of the pulsed discharge at the electrode gap of 5 mm and the pulse width of40-80 μs.展开更多
Evapotranspiration （ET） is the sum of soil or water body evaporation and plant transpiration from the earth surface and ocean to the atmosphere, and thus plays a significant role in regulating carbon and water resou...Evapotranspiration （ET） is the sum of soil or water body evaporation and plant transpiration from the earth surface and ocean to the atmosphere, and thus plays a significant role in regulating carbon and water resource cycles. The time-series data set from the remote sensing MOLDS product （MOD16） was used to study the spatial-temporal evolution of vegetation evapotranspiration in salinized areas during 2000-2014 by analyzing the variability, spatial patterns and Mann-Kendall （MK） nonparametric trends for the time series. The results indicate that inter-annual and intra-annual variations of ET across various vegetated areas show seasonal changes, with the abnormal months identified. The Cultivated land displays a greater degree of spatial heterogeneity and the spatial pattern of ET in the area covered by broadleaved deciduous forests corresponds to a higher ET rate and increased water consumption. Awidespread decline of ET is observed only in cultivated areas. However, agricultural cultivation doesn＇t worsen water shortage and soil salinization problems in the region, and water shortage problems are worsening for other vegetated areas. This research provides a basis of reference for the reasonable allocation of water resources and restructuring of vegetation patterns in salinized areas.展开更多
This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic devel...This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province＇s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows：（1） Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low.（2） Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others.（3） Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.展开更多
基金supported by funds from the Ministry of Science and Technology of the People's Republic of China(No.2019YFA0708603)NSFC(Nos.41973050,42288201,41930215)the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(No.GML2019ZD0202)。
文摘Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric mantle(SCLM)beneath the northern Tan-Lu fault zone(TLFZ)during the Cenozoic.The Qingyuan peridotites are dominated by spinel lherzolites with moderate-Mg^(#)olivines(89.4 to 91.2),suggesting that the regional SCLM is mainly transitional and fertile.Light rare earth element(LREE)-depleted,slightly depleted and enriched clinopyroxenes(Cpx)are identified in different peridotites.Chemical compositions of the LREE-enriched Cpx and the presence of phlogopite suggest that the Qingyuan SCLM has experienced silicate-related metasomatism.The synthesis of available mineral chemical data of the mantle xenoliths across the NCC confirms the SCLM beneath the NCC is highly heterogeneous in time and space.The Mesozoic–Cenozoic SCLM beneath the TLFZ and neighboring regions are more fertile and thinner than that beneath the region away from the fault zone.The fertile and refractory peridotite xenoliths experienced varying degrees of silicate and carbonatite metasomatism,respectively.The spatial-temporal lithospheric mantle heterogeneity in composition,age and thickness suggest that the trans-lithosphere fault zone played an important role in heterogeneous replacement of refractory cratonic lithospheric mantle.
文摘To conduct a comprehensive analysis of the current status of water environment quality in Yilong Lake,a systematic study was undertaken to characterize the evolution of water quality.This study utilized monthly data on water quality indicators collected from three monitoring sections of Yilong Lake between 2016 and 2023,employing the Mann-Kendall trend test and ArcGIS spatial interpolation technique.The results indicated that the five-day biochemical oxygen demand(BOD5),total nitrogen(TN),and chlorophyll a(Chla)exhibited an overall increasing trend,whereas other indicators demonstrated a decreasing trend.The permanganate index(PI),chemical oxygen demand(COD),TN,and Chla were observed in the following order:east of the lake>middle of the lake>west of the lake.In contrast,the BOD5 and total phosphorus(TP)were ranked as west of the lake>east of the lake>middle of the lake.Additionally,ammonia nitrogen(NH3-N)was found to be in the order of east of the lake>west of the lake>middle of the lake,while transparency was ranked as west of the lake>middle of the lake>east of the lake.Urban domestic sewage,effluent from industrial parks,domestic waste generated by rural residents’production and daily activities,agricultural waste,wastewater from decentralized farming,domestic sewage,and point source discharges from the soybean processing industry are the primary contributors to the exceedance of water quality standards.The enhancement of a precise pollution control system,along with the regulation of pollution sources and the interception of pollutants,can significantly diminish the pollution load entering the lake.This approach is essential for the protection and restoration of river and lake ecosystems,thereby facilitating the gradual recovery of their ecological functions.Additionally,the implementation of ecological water replenishment and the recycling of water resources can improve the capacity of the water environment.Furthermore,bolstering scientific and technological support,as well as comprehensive supervision and assurance measures,is crucial to ensuring that water quality remains stable and adheres to established standards.
基金funded by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant from the Ministry of Trade,Industry and Energy(MOTIE)(No.20198210100030,20208310100020)the Nuclear Safety Research Program through the Korea Foundation of Nuclear Safety(KoFONS)grant from the Nuclear Safety and Security Commission(NSSC)(No.071610)of the Republic of Korea.
文摘Five sequences of deep fluid injections at the Pohang Enhanced Geothermal System(EGS)triggered an ML 5.4 earthquake on November 15,2017.The foreshock-mainshock-aftershock sequence was monitored using dense seismic networks.Between November 14,2017,and May 31,2023,this study detected 5,169 earthquakes and determined the relative locations of 4,902 earthquakes,including seven foreshocks.A heterogeneous subsurface fault model is proposed,in which the fault is reactivated by induced and triggered earthquakes.The earthquake frequency decreased after the mainshock,with a temporary increase after the ML 4.6 event on February 10,2018.The magnitude-frequency b-values are significantly lower than those for the background seismicity in the Korean Peninsula and those for the 2016 Gyeongju earthquake sequence.The aftershock decay rate p-values are within the range of typical values,regardless of decreasing over time.The earthquake focal mechanisms exhibit a predominance of strike-slip components,whereas the slip tendency indicates a higher value in reverse faulting geometry,implying stress redistribution after the mainshock.The seismic landscape with ongoing aftershock activity after the 2017 Pohang earthquake underscores the importance of sustained,long-term seismic monitoring to comprehensively grasp the implications of the new seismic environment for seismic hazards in the area.
基金supported by the National Key R&D Program of China(No.2018YFB1305200)the Natural Science Foundation of Zhejiang Province(No.LGG21F030011)。
文摘Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smoother and more precise human motion prediction remains a challenge.To address these issues,a robust human motion prediction method via integration of spatial and temporal cues(RISTC)has been proposed.This method captures sufficient spatio-temporal correlation of the observable sequence of human poses by utilizing the spatio-temporal mixed feature extractor(MFE).In multi-layer MFEs,the channel-graph united attention blocks extract the augmented spatial features of the human poses in the channel and spatial dimension.Additionally,multi-scale temporal blocks have been designed to effectively capture complicated and highly dynamic temporal information.Our experiments on the Human3.6M and Carnegie Mellon University motion capture(CMU Mocap)datasets show that the proposed network yields higher prediction accuracy than the state-of-the-art methods.
基金Under the auspices of National Natural Science Foundation of China(No.42371192)Natural Science Foundation of Hunan Province(No.2023JJ30100)Social Science Foundation of Hunan Province(No.23ZDAJ023,23YBA133)。
文摘Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.
文摘Tuberculosis(TB)remained the first leading cause of death from a single infectious agent worldwide in 2023,resulting in nearly twice as many deaths as those caused by the human immunodeficiency virus/acquired immune deficiency syndrome.An estimated 10.8 million TB cases were reported globally in 2023,with approximately 1.25 million associated deaths.In China,which ranks third in the global TB burden,there were approximately 741,000 new cases and 25,000 deaths in 2023^([1]).TB poses a significant threat to human health worldwide.
基金the Science and Technology Research Project of Shandong Meteorological Bureau(2022SDQN11)Science and Technology Research Project of Yantai Meteorological Bureau(2024ytcx07).
文摘Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 10 concentration and its relationship with meteorological factors were studied.The results show that from the perspective of temporal variation,the annual average of PM 10 concentration in Yantai City tended to decrease year by year.It was high in winter and spring and low in summer and autumn.In terms of monthly variation,the changing curve is U-shaped,and it was high in December and January but low in July and August.During a day,PM 10 concentration had two peaks.The first peak appeared approximately from 09:00 to 11:00,and the second peak can be found from 21:00 to 23:00.From the perspective of spatial distribution,PM 10 concentration was the highest in the development area and Fushan District.It was the highest in the west,followed by the east,while it was the lowest in the middle.The spatial difference rate was the highest in summer.Average temperature,relative humidity,wind speed and precipitation were the main meteorological factors influencing PM 10 concentration in Yantai area.PM 10 concentration was negatively correlated with average temperature and relative humidity,and the correlation was the most significant from June to October.It was negatively correlated with wind speed and precipitation,and the correlation was different in various months.The negative correlation was significant in summer and winter.
基金supported by the Urgent Need for Overseas Talent Project of Jiangxi Province(Grant No.20223BCJ25040)the Thousand Talents Plan of Jiangxi Province(Grant No.jxsg2023101085)+3 种基金the National Natural Science Foundation of China(Grant No.62106093)the Natural Science Foundation of Jiangxi(Grant Nos.20224BAB212011,20232BAB212008,20242BAB25078,and 20232BAB202051)The Youth Talent Cultivation Innovation Fund Project of Nanchang University(Grant No.XX202506030015)funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R759),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Predicting human motion based on historical motion sequences is a fundamental problem in computer vision,which is at the core of many applications.Existing approaches primarily focus on encoding spatial dependencies among human joints while ignoring the temporal cues and the complex relationships across non-consecutive frames.These limitations hinder the model’s ability to generate accurate predictions over longer time horizons and in scenarios with complex motion patterns.To address the above problems,we proposed a novel multi-level spatial and temporal learning model,which consists of a Cross Spatial Dependencies Encoding Module(CSM)and a Dynamic Temporal Connection Encoding Module(DTM).Specifically,the CSM is designed to capture complementary local and global spatial dependent information at both the joint level and the joint pair level.We further present DTM to encode diverse temporal evolution contexts and compress motion features to a deep level,enabling the model to capture both short-term and long-term dependencies efficiently.Extensive experiments conducted on the Human 3.6M and CMU Mocap datasets demonstrate that our model achieves state-of-the-art performance in both short-term and long-term predictions,outperforming existing methods by up to 20.3% in accuracy.Furthermore,ablation studies confirm the significant contributions of the CSM and DTM in enhancing prediction accuracy.
文摘This study investigated the spatio-temporal variation characteristics of ecosystem service value(ESV)alongside its driving influencing factors,thereby offering valuable theoretical insights for the sustainable development of Jingzhou City,Hubei Province.Based on the land use data for Jingzhou City from 2000 to 2020,this study quantified the value of the ecological environment using the equivalent factor method.Furthermore,it analyzed and elucidated the spatio-temporal heterogeneity and driving mechanisms of ecosystem services in Jingzhou City.The results indicated that between 2000 and 2020,cultivated land(66.40%)and water area(18.82%)were the predominant land use types in Jingzhou City.The areas of water area and construction land exhibited a growth trend during this period.Construction land had the highest rate of land use change,followed by water area and cultivated land.Land use transitions primarily occurred between cultivated land and water area,as well as between cultivated land and construction land.The total value of ecosystem services in Jingzhou City increased by 165.07%from 2000 to 2020.ESV exhibited an upward trend from 2000 to 2015,followed by a gradual decline from 2015 to 2020.The ranking of individual ecosystem services,in descending order,was as follows:regulation services,supporting services,provisioning services,and cultural services.High-value ESV areas were predominantly situated in the water area of Lake Honghu,while low-value regions were mainly found in the cultivated land in the central and western parts of Jingzhou City.The spatial differentiation of ESV in Jingzhzou City was influenced by both natural and socio-economic factors,with natural factors exerting a more significant impact than socioeconomic factors.Specifically,the Normalized Difference Vegetation Index(NDVI)was the dominant environmental factor,while GDP plays a synergistic role.
基金National Natural Science Foundation of China,Grant/Award Number:62176084,Natural Science Foundation of Anhui Province of China,Grant/Award Number:1908085MF195,Natural Science Research Project of the Education Department of Anhui Province of China Grant/Award Numbers:2022AH051038,2023AH050474 and 2023AH050490.
文摘To overcome the deficiencies of single-modal emotion recognition based on facial expression or bodily posture in natural scenes,a spatial guidance and temporal enhancement(SG-TE)network is proposed for facial-bodily emotion recognition.First,ResNet50,DNN and spatial ransformer models are used to capture facial texture vectors,bodily skeleton vectors and wholebody geometric vectors,and an intraframe correlation attention guidance(S-CAG)mechanism,which guides the facial texture vector and the bodily skeleton vector by the whole-body geometric vector,is designed to exploit the spatial potential emotional correlation between face and posture.Second,an interframe significant segment enhancement(T-SSE)structure is embedded into a temporal transformer to enhance high emotional intensity frame information and avoid emotional asynchrony.Finally,an adaptive weight assignment(M-AWA)strategy is constructed to realise facial-bodily fusion.The experimental results on the BabyRobot Emotion Dataset(BRED)and Context-Aware Emotion Recognition(CAER)dataset indicate that the proposed network reaches accuracies of 81.61%and 89.39%,which are 9.61%and 9.46%higher than those of the baseline network,respectively.Compared with the state-of-the-art methods,the proposed method achieves 7.73%and 20.57%higher accuracy than single-modal methods based on facial expression or bodily posture,respectively,and 2.16%higher accuracy than the dual-modal methods based on facial-bodily fusion.Therefore,the proposed method,which adaptively fuses the complementary information of face and posture,improves the quality of emotion recognition in real-world scenarios.
文摘Based on the data of meteorological elements and concentration of negative ions in the county town station,Luguhe station and Yunjishan station during 2020-2024,the temporal and spatial variations in the concentration of negative ions and their influencing factors in Xinfeng County were analyzed.The results show that the concentration of negative ions was the highest in summer,followed by spring;it was lower in autumn and the lowest in winter.In terms of diurnal variations,it was higher in the early morning and night,and lower in the noon and afternoon,which was closely related to the diurnal variations of human activities and meteorological conditions.The factors that affect the concentration of negative ions in the air are more complex.Besides meteorological factors,vegetation,altitude,human activities and other factors should be considered.
基金supported by the National Key Research and Development Plan Project Sub-Topic of China(Grant Nos.2022YFD1901500 and 2022YFD1901505-07)the National Natural Science Foundation of China(Grant No.32260531)+1 种基金the Key Laboratory of Molecular Breeding for Grain and Oil Crops in Guizhou Province,China(Grant No.Qiankehezhongyindi[2023]8)the Key Laboratory of Functional Agriculture of Guizhou Provincial Higher Education Institutions,China(Grant No.Qianjiaoji[2023]007).
文摘Recently,information acquired at the canopy top,such as spectral and textural data,has been widely used to estimate plant nitrogen(N)accumulation(PNA).The response of crops to N uptake involves not only changes in horizontal canopy top information but also an increase in vertical plant height(PH).It remains unclear whether the fusion of spectral indices with PH can improve the estimation performance of PNA models based on spectral remote sensing across different growth stages.
文摘High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume sion disper-in complex terrain.However,their high computational cost makes them impractical for applications requiring rapid responses or iterative processes,such as optimization,uncertainty quantification,or inverse modeling.To address this challenge,this work introduces the Dual-Stage Temporal Three-dimensional UNet Super-resolution(DST3D-UNet-SR)model,a highly efficient deep learning model for plume dispersion predictions.DST3D-UNet-SR is composed of two sequential modules:the temporal module(TM),which predicts the transient evolution of a plume in complex terrain from low-resolution temporal data,and the spatial refinement module(SRM),which subsequently enhances the spatial resolution of the TM predictions.We train DST3D-UNet-SR using a comprehensive dataset derived from high-resolution large eddy simulations(LES)of plume transport.We propose the DST3D-UNet-SR model to significantly accelerate LES of three-dimensional(3D)plume dispersion by three orders of magnitude.Additionally,the model demonstrates the ability to dynamically adapt to evolving conditions through the incorporation of new observational data,substantially improving prediction accuracy in high-concentration regions near the source.
文摘Smart grid substation operations often take place in hazardous environments and pose significant threats to the safety of power personnel.Relying solely on manual supervision can lead to inadequate oversight.In response to the demand for technology to identify improper operations in substation work scenarios,this paper proposes a substation safety action recognition technology to avoid the misoperation and enhance the safety management.In general,this paper utilizes a dual-branch transformer network to extract spatial and temporal information from the video dataset of operational behaviors in complex substation environments.Firstly,in order to capture the spatial-temporal correlation of people's behaviors in smart grid substation,we devise a sparse attention module and a segmented linear attention module that are embedded into spatial branch transformer and temporal branch transformer respectively.To avoid the redundancy of spatial and temporal information,we fuse the temporal and spatial features using a tensor decomposition fusion module by a decoupled manner.Experimental results indicate that our proposed method accurately detects improper operational behaviors in substation work scenarios,outperforming other existing methods in terms of detection and recognition accuracy.
基金supported by the Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences.
文摘The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.
文摘[Objective] The paper aimed to reflect the spatial pattern and temporal and spatial evolution characteristics, the differences between inter-regional tourism economy was measured from the quality aspect, which provided a reference for the local governments in the future tourism development. [Method] Using the location entropy methods, three time periods side of tourism-related date of 2000, 2005, 2007 were selected, from the angle of the spatial pattern and the evolution of the differences within the different scales, the spatial and temporal evolution characteristics of the economic development level of Jiangsu were analysed. [Result] The results showed that from the aspect of spatial evolution pattern, as time goes on, the economic development of Jiangsu tourism has experienced morphological evolution of concentration- dispersion decrease-stability; when it comes to the development of the tourism economy, in recent years, the overall gap between the tourism economy in Jiangsu did not widen, the gap mainly led by the region one after another. According to their volatility, it will be divided into four categories: A Stable type (Wuxi, Xuzhou, Lianyungang and Taizhou), B Increasing type (Huai’an), C Fluctuations type (Nanjing, Changzhou, Suzhou and Yangzhou) and D Depression type (Nantong, Yancheng, Zhenjiang and Suqian). [Conclusion] Location entropy was quoted into tourism economic analysis, the method was simple and easy to understand, the result was accurate and convincing, which provided a reference for travel economic development and investment decision-making of Jiangsu.
基金Humanities and Social Science Project of the Ministry of Education(NO.17YJCZH041)。
文摘This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse,the research mapped out the progression and distribution of aging demographics.Furthermore,the study delved into the influencing factors of aging using an optimal parameters-based geographical detector.Results indicate a deepening degree of population aging in Henan Province,transitioning from an adult type to an old type structure.There is a marked positive spatial correlation among counties,with high-value aging areas initially decreasing,then increasing,and notably spreading from the central to the central and southern regions of the province.The center of gravity for population aging,specifically around Changge City and Xuchang City,exhibits a trajectory moving southeast before shifting northwest.Factor detection reveals that in 2000,2010,and 2020,the elderly dependency ratio predominantly influences the aging trend,with explanatory powers of 88.4%,87.9%,and 90.9%,respectively.Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province,reaching 97.3%,97.0%,and 97.4%,respectively.
基金supported by National Natural Science Foundation of China (Nos. 11605023, 11805028, and 11705020)the National Key R&D Program of China (No. 2017YFE0301300)+1 种基金the China Postdoctoral Science Foundation (Nos. 2017T100172 and 2016M591423)the Fundamental Research Funds for the Central Universities (Nos. DUT17RC(4)53 and DUT18LK38)
文摘The study of sulfur hexafluoride(SF6) discharge is vital for its application in gas-insulated equipment. Direct current partial discharge(PD) may cause SF6 decomposition, and the decomposed products of SF6, such as F atoms, play a dominant role in the breakdown of insulation systems. In this study, the PD caused by metal protrusion defects is simulated by a needle-plate electrode using pulsed high voltage in SF6/Ar mixtures. The spatial and temporal characteristics of SF6/Ar plasma are analyzed by measuring the emission spectra of F and Ar atoms, which are important for understanding the characteristics of PD. The spatial resolved results show that both F and Ar atom spectral intensities increase first from the plate anode to the needle and then decrease under the conditions of a background pressure of400 Pa, peak voltage of-1000 V, frequency of 2 kHz, pulse width of 60 μs, and electrode gap of 5-9 mm. However, the distribution characteristics of F and Ar are significantly different. The temporal distribution results show that the spectral intensity of Ar decreasesfirst and then increases slowly, while the spectral intensity of F increases slowly for the duration of the pulsed discharge at the electrode gap of 5 mm and the pulse width of40-80 μs.
基金financial support from the National Key Research and Development Program of China(2017YFC1502404)the National Natural Science Foundation of China(41601562 and 41761014)+1 种基金the China Institute of Water Resources and Hydropower Research Team Construction and Talent Development Project(JZ0145B752017)the Research Project for Young Teachers of Fujian Province,China(JAT160085)
文摘Evapotranspiration （ET） is the sum of soil or water body evaporation and plant transpiration from the earth surface and ocean to the atmosphere, and thus plays a significant role in regulating carbon and water resource cycles. The time-series data set from the remote sensing MOLDS product （MOD16） was used to study the spatial-temporal evolution of vegetation evapotranspiration in salinized areas during 2000-2014 by analyzing the variability, spatial patterns and Mann-Kendall （MK） nonparametric trends for the time series. The results indicate that inter-annual and intra-annual variations of ET across various vegetated areas show seasonal changes, with the abnormal months identified. The Cultivated land displays a greater degree of spatial heterogeneity and the spatial pattern of ET in the area covered by broadleaved deciduous forests corresponds to a higher ET rate and increased water consumption. Awidespread decline of ET is observed only in cultivated areas. However, agricultural cultivation doesn＇t worsen water shortage and soil salinization problems in the region, and water shortage problems are worsening for other vegetated areas. This research provides a basis of reference for the reasonable allocation of water resources and restructuring of vegetation patterns in salinized areas.
基金National Natural Science Foundation of China,No.41171433Philosophy and Social Science Foundation of China,No.16BJY039
文摘This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province＇s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows：（1） Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low.（2） Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others.（3） Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.
