Considering the challenge of aerodynamic heating,the development of high-performance insulating ce-ramic materials with lightweight and low thermal conductivity is crucially important for aerospace vehi-cles to achiev...Considering the challenge of aerodynamic heating,the development of high-performance insulating ce-ramic materials with lightweight and low thermal conductivity is crucially important for aerospace vehi-cles to achieve flight at high speed for a long time.In this work,macro-porous silicon oxycarbide(SiOC)ceramics with directional pores(DP-SiOC)(mean pore size of 88.1μm)were prepared using polysiloxane precursors via freeze casting and photocrosslinking,followed by pyrolysis.The DP-SiOC samples were lightweight(density∼0.135 g cm^(-3))with a porosity of 90.4%,which showed good shapability through the molding of polysiloxane precursors.The DP-SiOC samples also exhibited an ultra-low thermal con-ductivity of 0.048 W(m K)^(-1)at room temperature,which can also withstand heat treatment at 1200°C for 1 h.In addition,scaffolds with triply periodic minimal surfaces(TPMS)were fabricated using digital light processing(DLP)printing,which was further filled with polysiloxane precursors for increasing the strength of DP-SiOC.The TPMS scaffolds filled with macro-porous SiOC ceramics(TPMS-DP-SiOC)showed good integration between TPMS and macro-pore structures,which had a porosity∼75%and high specific strength of 9.73×10^(3)N m kg^(-1).The thermal conductivity of TPMS-DP-SiOC samples was 0.255 W(m K)^(-1)at room temperature.The biomimetic TPMS-DP-SiOC ceramics developed in this study are likely used for thermal protection systems.展开更多
In this paper,we propose a new method to achieve automatic matching of multi-scale roads under the constraints of smaller scale data.The matching process is:Firstly,meshes are extracted from two different scales road ...In this paper,we propose a new method to achieve automatic matching of multi-scale roads under the constraints of smaller scale data.The matching process is:Firstly,meshes are extracted from two different scales road data.Secondly,several basic meshes in the larger scale road network will be merged into a composite one which is matched with one mesh in the smaller scale road network,to complete the N∶1(N>1)and 1∶1 matching.Thirdly,meshes of the two different scale road data with M∶N(M>1,N>1)matching relationships will be matched.Finally,roads will be classified into two categories under the constraints of meshes:mesh boundary roads and mesh internal roads,and then matchings between the two scales meshes will be carried out within their own categories according to the matching relationships.The results show that roads of different scales will be more precisely matched using the proposed method.展开更多
China’s rapid economic development has initiated the deterioration of its ecological environment,posing a threat to the sustainable development of human society.As a result,an assessment of regional sustainability is...China’s rapid economic development has initiated the deterioration of its ecological environment,posing a threat to the sustainable development of human society.As a result,an assessment of regional sustainability is critical.This paper researches China’s most forested province,Fujian Province,as the study area.We proposed a grid-based approach to assess the regional carbon footprint in accordance with the Intergovernmental Panel on Climate Change’s(IPCC)carbon emission guidelines.Our method of assessment also introduced carbon emission indicators with our improved and published Net Primary Production(NPP)based on process simulation.The carbon footprint in Fujian Province from 2005-2017 was calculated and examined from a spatiotemporal perspective.Ecological indicators were used in the sustainability assessment.The research draws the following conclusions:1)the carbon footprint in the eastern regions of Fujian Province was higher due to rapid economic development;2)that of the western regions was lower;3)an uptrend in the carbon footprint of Fujian Province was observed.All five ecological indicators based on carbon emissions and economic and social data showed an ecologically unsustainable trend over 13 years in the research area due to unsustainable economic development.Therefore,it is urgent to balance the relationship between economic development and environmental protection.Our research provides scientific references for achieving ecological civilization and sustainability in a similar region.展开更多
Remote sensing spatiotemporal fusion models blend multi-source images of different spatial resolutions to create synthetic images with high resolution and frequency,contributing to time series research where high qual...Remote sensing spatiotemporal fusion models blend multi-source images of different spatial resolutions to create synthetic images with high resolution and frequency,contributing to time series research where high quality observations are not available with sufficient frequency.However,existing models are vulnerable to spatial heterogeneity and land cover changes,which are frequent in human-dominated regions.To obtain quality time series of satellite images in a human-dominated region,this study developed the Modified Flexible Spatial-temporal Data Fusion(MFSDAF)approach based on the Flexible Spatial-temporal Data Fusion(FSDAF)model by using the enhanced linear regression(ELR).Multiple experiments of various land cover change scenarios were conducted based on both actual and simulated satellite images,respectively.The proposed MFSDAF model was validated by using the correlation coefficient(r),relative root mean square error(RRMSE),and structural similarity(SSIM),and was then compared with the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM)and FSDAF models.Results show that in the presence of significant land cover change,MFSDAF showed a maximum increase in r,RRMSE,and SSIM of 0.0313,0.0109 and 0.049,respectively,compared to FSDAF,while ESTARFM performed best with less temporal difference of in the input images.In conditions of stable landscape changes,the three performance statistics indicated a small advantage of MFSDAF over FSDAF,but were 0.0286,0.0102,0.0317 higher than for ESTARFM,respectively.MFSDAF showed greater accuracy of capturing subtle changes and created high-precision images from both actual and simulated satellite images.展开更多
Agricultural innovation can be described as a coevolutionary process of technological innovation,symbolic change,and social or institutional innovation,which relies on the interactions and collaboration between multip...Agricultural innovation can be described as a coevolutionary process of technological innovation,symbolic change,and social or institutional innovation,which relies on the interactions and collaboration between multiple stakeholders.This view emphasizes the significance of innovation intermediaries in supporting the coevolution process of innovation.Many studies have provided evidence on how innovation intermediaries play roles in supporting the coevolution innovation process at a broader innovation system level.However,little emphasis has been given to the role of innovation intermediaries in supporting the coevolution process of innovation at the community level in rural China.To address this research gap,this paper offers a case study of a novel type of innovation support intervention designed to promote technical change at the community level,the Science and Technology Backyard(STB).The paper focuses on the efforts of a specific STB in Wangzhuang village to promote innovation in tillage methods in wheat production.The aims was to examine the role of this newly emerging innovation support intervention in supporting the coevolution process of innovation at the community level,and compare the outcome of the coevolution process in the village with an STB to that in villages without an STB.Innovation journey analysis is applied to understand the evolved intermediation roles in the innovation process,and multivariate regression analysis is employed to assess the outcome of the coevolution process in villages with and without an STB.The findings suggest that the roles of STBs have evolved from knowledge brokers to systemic innovation intermediaries that facilitate the coevolution process of innovation inside an STB village.It has led to a higher adoption rate of improved technology,a better enabling environment for learning,and more effective institutional support in STB villages than in non-STB villages.However,the effect of support provided by a single STB on the coevolution process outside the community was limited.This finding points to a need for collaboration mechanisms and for connecting single STBs to support the coevolution process of innovation at a larger scale.展开更多
基金supported by the CAS Interdisciplinary Innova-tion Team Project(No.JCTD-2020-10)of the Chinese Academy of SciencesChina and the Defense Industrial Technology Develop-ment Program(No.JCKY2021130B039).
文摘Considering the challenge of aerodynamic heating,the development of high-performance insulating ce-ramic materials with lightweight and low thermal conductivity is crucially important for aerospace vehi-cles to achieve flight at high speed for a long time.In this work,macro-porous silicon oxycarbide(SiOC)ceramics with directional pores(DP-SiOC)(mean pore size of 88.1μm)were prepared using polysiloxane precursors via freeze casting and photocrosslinking,followed by pyrolysis.The DP-SiOC samples were lightweight(density∼0.135 g cm^(-3))with a porosity of 90.4%,which showed good shapability through the molding of polysiloxane precursors.The DP-SiOC samples also exhibited an ultra-low thermal con-ductivity of 0.048 W(m K)^(-1)at room temperature,which can also withstand heat treatment at 1200°C for 1 h.In addition,scaffolds with triply periodic minimal surfaces(TPMS)were fabricated using digital light processing(DLP)printing,which was further filled with polysiloxane precursors for increasing the strength of DP-SiOC.The TPMS scaffolds filled with macro-porous SiOC ceramics(TPMS-DP-SiOC)showed good integration between TPMS and macro-pore structures,which had a porosity∼75%and high specific strength of 9.73×10^(3)N m kg^(-1).The thermal conductivity of TPMS-DP-SiOC samples was 0.255 W(m K)^(-1)at room temperature.The biomimetic TPMS-DP-SiOC ceramics developed in this study are likely used for thermal protection systems.
基金The National Natural Science Foundation of China(Nos.4110136241471386)。
文摘In this paper,we propose a new method to achieve automatic matching of multi-scale roads under the constraints of smaller scale data.The matching process is:Firstly,meshes are extracted from two different scales road data.Secondly,several basic meshes in the larger scale road network will be merged into a composite one which is matched with one mesh in the smaller scale road network,to complete the N∶1(N>1)and 1∶1 matching.Thirdly,meshes of the two different scale road data with M∶N(M>1,N>1)matching relationships will be matched.Finally,roads will be classified into two categories under the constraints of meshes:mesh boundary roads and mesh internal roads,and then matchings between the two scales meshes will be carried out within their own categories according to the matching relationships.The results show that roads of different scales will be more precisely matched using the proposed method.
基金supported by the National Natural Science Foundation of China(Grant No.41601562)sponsored by China Scholarship Council(No.201806655014)+1 种基金the Research Project for Young Teachers of Fujian Province(No.JAT160085)the Scientific Research Foundation of Fuzhou University(No.XRC-1536).
文摘China’s rapid economic development has initiated the deterioration of its ecological environment,posing a threat to the sustainable development of human society.As a result,an assessment of regional sustainability is critical.This paper researches China’s most forested province,Fujian Province,as the study area.We proposed a grid-based approach to assess the regional carbon footprint in accordance with the Intergovernmental Panel on Climate Change’s(IPCC)carbon emission guidelines.Our method of assessment also introduced carbon emission indicators with our improved and published Net Primary Production(NPP)based on process simulation.The carbon footprint in Fujian Province from 2005-2017 was calculated and examined from a spatiotemporal perspective.Ecological indicators were used in the sustainability assessment.The research draws the following conclusions:1)the carbon footprint in the eastern regions of Fujian Province was higher due to rapid economic development;2)that of the western regions was lower;3)an uptrend in the carbon footprint of Fujian Province was observed.All five ecological indicators based on carbon emissions and economic and social data showed an ecologically unsustainable trend over 13 years in the research area due to unsustainable economic development.Therefore,it is urgent to balance the relationship between economic development and environmental protection.Our research provides scientific references for achieving ecological civilization and sustainability in a similar region.
基金supported by the National Natural Science Foundation of China(51971133,51902200,52071213,32000981 and 52072241)Shanghai Science and Technology Committee(18JC1410500,19ZR1425300 and 19ZR1425100)+2 种基金the National High-Level Talent Program for Young Scholars,Shenzhen Science and Technology Research Funding(JCYJ20190806170011328)China National Postdoctoral Program for Innovative Talents(BX20190352)Guangdong Province Fundamental Research Funds(2019A1515111209).
基金This research received financial support by the National Natural Science Foundation of China(Grant Nos.41601562 and 41761014)the National Key Research and Development Program of China(No.2017YFC1502404)+1 种基金the China Institute of Water Resources and Hydropower Research Team Construction and Talent Development Project(No.JZ0145B752017)the Research Project for Young Teachers of Fujian Province(No.JAT160085).
文摘Remote sensing spatiotemporal fusion models blend multi-source images of different spatial resolutions to create synthetic images with high resolution and frequency,contributing to time series research where high quality observations are not available with sufficient frequency.However,existing models are vulnerable to spatial heterogeneity and land cover changes,which are frequent in human-dominated regions.To obtain quality time series of satellite images in a human-dominated region,this study developed the Modified Flexible Spatial-temporal Data Fusion(MFSDAF)approach based on the Flexible Spatial-temporal Data Fusion(FSDAF)model by using the enhanced linear regression(ELR).Multiple experiments of various land cover change scenarios were conducted based on both actual and simulated satellite images,respectively.The proposed MFSDAF model was validated by using the correlation coefficient(r),relative root mean square error(RRMSE),and structural similarity(SSIM),and was then compared with the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM)and FSDAF models.Results show that in the presence of significant land cover change,MFSDAF showed a maximum increase in r,RRMSE,and SSIM of 0.0313,0.0109 and 0.049,respectively,compared to FSDAF,while ESTARFM performed best with less temporal difference of in the input images.In conditions of stable landscape changes,the three performance statistics indicated a small advantage of MFSDAF over FSDAF,but were 0.0286,0.0102,0.0317 higher than for ESTARFM,respectively.MFSDAF showed greater accuracy of capturing subtle changes and created high-precision images from both actual and simulated satellite images.
基金supported by China Scholarship Council(201913043)Agricultural Carbon Neutral Account Establishment Program in Quzhou(202127).
文摘Agricultural innovation can be described as a coevolutionary process of technological innovation,symbolic change,and social or institutional innovation,which relies on the interactions and collaboration between multiple stakeholders.This view emphasizes the significance of innovation intermediaries in supporting the coevolution process of innovation.Many studies have provided evidence on how innovation intermediaries play roles in supporting the coevolution innovation process at a broader innovation system level.However,little emphasis has been given to the role of innovation intermediaries in supporting the coevolution process of innovation at the community level in rural China.To address this research gap,this paper offers a case study of a novel type of innovation support intervention designed to promote technical change at the community level,the Science and Technology Backyard(STB).The paper focuses on the efforts of a specific STB in Wangzhuang village to promote innovation in tillage methods in wheat production.The aims was to examine the role of this newly emerging innovation support intervention in supporting the coevolution process of innovation at the community level,and compare the outcome of the coevolution process in the village with an STB to that in villages without an STB.Innovation journey analysis is applied to understand the evolved intermediation roles in the innovation process,and multivariate regression analysis is employed to assess the outcome of the coevolution process in villages with and without an STB.The findings suggest that the roles of STBs have evolved from knowledge brokers to systemic innovation intermediaries that facilitate the coevolution process of innovation inside an STB village.It has led to a higher adoption rate of improved technology,a better enabling environment for learning,and more effective institutional support in STB villages than in non-STB villages.However,the effect of support provided by a single STB on the coevolution process outside the community was limited.This finding points to a need for collaboration mechanisms and for connecting single STBs to support the coevolution process of innovation at a larger scale.
