The increase in the frequency and intensity of drought events expected in the coming decades in Western Europe may disturb forest biogeochemical cycles and create nutrient deficiencies in trees.One possible origin of ...The increase in the frequency and intensity of drought events expected in the coming decades in Western Europe may disturb forest biogeochemical cycles and create nutrient deficiencies in trees.One possible origin of nutrient deficiency is the disturbance of the partitioning of the green leaf pool during the leaf senescence period between resorption,foliar leaching and senesced leaves.However,the effects of drought events on this partitioning and the consequences for the maintenance of tree nutrition are poorly documented.An experiment in a beech forest in Meuse(France)was conducted to assess the effect of drought events on nutrient canopy exchanges and on the partitioning of the green leaf pool during the leaf senescence period.The aim was to identify potential nutritional consequences of droughts for trees.Monitoring nutrient dynamics,including resorption,chemistry of green and senesced leaves,foliar absorption and leaching in mature beech stands from 2012 to 2019 allowed us to compare the nutrient exchanges for three nondry and three dry years(i.e.,with an intense drought event during the growing season).During dry years,we observed a decrease by almost a third of the potassium(K)partitioning to resorption(i.e.resorption efficiency),thus reducing the K reserve in trees for the next growing season.This result suggests that with the increased drought frequency and intensity expected for the coming decades,there will be a risk of potassium deficiency in trees,as already observed in a rainfall exclusion experiment on the same study site.Reduced foliar leaching and higher parititioning to the senesced leaves for K and phosphorus(P)were also observed.In addition,a slight increase in nitrogen(N)resorption efficiency occurred during dry years which is more likely to improve tree nutrition.The calcium(Ca)negative resorption decreased,with no apparent consequence in our study site.Our results show that nutrient exchanges in the canopy and the partitioning of the green leaf pool can be modified by drought events,and may have consequences on tree nutrition.展开更多
Elastomer blends,among which natural rubber(NR)and butadiene rubber(BR),are involved in many components of the automotive/tire industry.A comprehensive understanding of their mechanical behavior requires,among other f...Elastomer blends,among which natural rubber(NR)and butadiene rubber(BR),are involved in many components of the automotive/tire industry.A comprehensive understanding of their mechanical behavior requires,among other features,a detailed description of the crosslink density in these mixtures.In the case of vulcanized immiscible blends,the distribution of the cross-link density within each of the NR-and BR-rich domains is key information,but difficult to determine using the conventional approaches used for one-component crosslinked elastomers.In this study,the vulcanization within NR/BR blends is investigated using a robust^(1)H double-quantum(DQ)MAS recoupling experiment,BaBa-xy16.Two kinds of cross-linked NR/BR blends were considered with two different microstructures for the BR component.The bulk organization of the resulting blends was first probed by analyzing the^(1)H spin-lattice relaxation behavior.In a second step,BaBa-xy16 was used to investigate,in a selective way,the cross-link heterogeneities within NR/BR blends.In particular,for immiscible NR/BR mixtures,the distribution of the cross-link density between both phases was compared and the observed differences were discussed.展开更多
Modern additive manufacturing processes enable fabricating architected cellular materials of complex shape,which can be used for different purposes.Among them,lattice structures are increasingly used in applications r...Modern additive manufacturing processes enable fabricating architected cellular materials of complex shape,which can be used for different purposes.Among them,lattice structures are increasingly used in applications requiring a compromise among lightness and suited mechanical properties,like improved energy absorption capacity and specific stiffness-to-weight and strength-to-weight ratios.A dedicated modeling strategy to assess the energy absorption capacity of lattice structures under uni-axial compression loading is presented in this work.The numerical model is developed in a non-linear framework accounting for the strain rate effect on the mechanical responses of the lattice structure.Four geometries,i.e.,cubic body centered cell,octet cell,rhombic-dodecahedron and truncated cuboctahedron 2+,are investigated.Specifically,the influence of the relative density of the representative volume element of each geometry,the strain-rate dependency of the bulk material and of the presence of the manufacturing process-induced geometrical imperfections on the energy absorption capacity of the lattice structure is investigated.The main outcome of this study points out the importance of correctly integrating geometrical imperfections into the modeling strategy when shock absorption applications are aimed for.展开更多
Background:Pine wilt disease(PWD)is a major ecological concern in China that has caused severe damage to millions of Chinese pines(Pinus tabulaeformis).To control the spread of PWD,it is necessary to develop an effect...Background:Pine wilt disease(PWD)is a major ecological concern in China that has caused severe damage to millions of Chinese pines(Pinus tabulaeformis).To control the spread of PWD,it is necessary to develop an effective approach to detect its presence in the early stage of infection.One potential solution is the use of Unmanned Airborne Vehicle(UAV)based hyperspectral images(HIs).UAV-based HIs have high spatial and spectral resolution and can gather data rapidly,potentially enabling the effective monitoring of large forests.Despite this,few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine.Method:To fill this gap,we used a Random Forest(RF)algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data(data directly collected from trees in the field).We compared relative accuracy of each of these data collection methods.We built our RF model using vegetation indices(VIs),red edge parameters(REPs),moisture indices(MIs),and their combination.Results:We report several key results.For ground data,the model that combined all parameters(OA:80.17%,Kappa:0.73)performed better than VIs(OA:75.21%,Kappa:0.66),REPs(OA:79.34%,Kappa:0.67),and MIs(OA:74.38%,Kappa:0.65)in predicting the PWD stage of individual pine tree infection.REPs had the highest accuracy(OA:80.33%,Kappa:0.58)in distinguishing trees at the early stage of PWD from healthy trees.UAV-based HI data yielded similar results:the model combined VIs,REPs and MIs(OA:74.38%,Kappa:0.66)exhibited the highest accuracy in estimating the PWD stage of sampled trees,and REPs performed best in distinguishing healthy trees from trees at early stage of PWD(OA:71.67%,Kappa:0.40).Conclusion:Overall,our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage,although its accuracy must be improved before widespread use is practical.We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data.We believe that these results can be used to improve preventative measures in the control of PWD.展开更多
Background:Anoplophora glabripennis(Motschulsky),commonly known as Asian longhorned beetle(ALB),is a wood-boring insect that can cause lethal infestation to multiple borer leaf trees.In Gansu Province,northwest China,...Background:Anoplophora glabripennis(Motschulsky),commonly known as Asian longhorned beetle(ALB),is a wood-boring insect that can cause lethal infestation to multiple borer leaf trees.In Gansu Province,northwest China,ALB has caused a large number of deaths of a local tree species Populus gansuensis.The damaged area belongs to Gobi desert where every single tree is artificially planted and is extremely difficult to cultivate.Therefore,the monitoring of the ALB infestation at the individual tree level in the landscape is necessary.Moreover,the determination of an abnormal phenotype that can be obtained directly from remote-sensing images to predict the damage degree can greatly reduce the cost of field investigation and management.Methods:Multispectral WorldView-2(WV-2)images and 5 tree physiological factors were collected as experimental materials.One-way ANOVA of the tree’s physiological factors helped in determining the phenotype to predict damage degrees.The original bands of WV-2 and derived vegetation indices were used as reference data to construct the dataset of a prediction model.Variance inflation factor and stepwise regression analyses were used to eliminate collinearity and redundancy.Finally,three machine learning algorithms,i.e.,Random Forest(RF),Support Vector Machine(SVM),Classification And Regression Tree(CART),were applied and compared to find the best classifier for predicting the damage stage of individual P.gansuensis.Results:The confusion matrix of RF achieved the highest overall classification accuracy(86.2%)and the highest Kappa index value(0.804),indicating the potential of using WV-2 imaging to accurately detect damage stages of individual trees.In addition,the canopy color was found to be positively correlated with P.gansuensis’damage stages.Conclusions:A novel method was developed by combining WV-2 and tree physiological index for semi-automatic classification of three damage stages of P.gansuensis infested with ALB.The canopy color was determined as an abnormal phenotype that could be directly assessed using remote-sensing images at the tree level to predict the damage degree.These tools are highly applicable for driving quick and effective measures to reduce damage to pure poplar forests in Gansu Province,China.展开更多
Background: Heavy backpacks are often used by soldiers and firefighters. Weight carrying could reduce the speed and efficiency in task completion by altering the foot sole sensitivity and postural control.Methods: In ...Background: Heavy backpacks are often used by soldiers and firefighters. Weight carrying could reduce the speed and efficiency in task completion by altering the foot sole sensitivity and postural control.Methods: In fifteen healthy subjects, we measured the changes in sensitivity to vibrations applied to the foot sole when standing upright or walking after load carrying(30% body weight). The participants were asked to judge different vibration amplitudes applied on the 2 nd or 5 th metatarsal head and the heel at two frequencies(25 and 150 Hz) to determine the vibration threshold and the global perceptual representation(Ψ)of the vibration amplitude(Φ)given by the Stevens power function(Ψ=k×Φ~n). Any increase in negative k value indicated a reduction in sensitivity to the lowest loads. Pedobarographic measurements, with computation of the center of pressure(COP) and its deviations, were performed during weight carrying.Results: The 25-Hz vibration threshold significantly increased after weight carrying when standing upright or walking.After standing with the added loads, the absolute negative k value increased for the 25 Hz frequency. After walking with the added loads, the k coefficient increased for the two vibration frequencies. Weight carrying significantly increased both the CoP surface and CoP lateral deviation.Conclusions: Our data show that weight carrying reduces the sensory pathways from the foot sole and accentuates the center of pressure deviations.展开更多
A fully dense carbon nanotubes (CNTs) reinforced AlSi matrix composite with the multiscale nacre-like architecture was designed and successfully realized by flake powder metallurgy followed by cold spraying (CS). The ...A fully dense carbon nanotubes (CNTs) reinforced AlSi matrix composite with the multiscale nacre-like architecture was designed and successfully realized by flake powder metallurgy followed by cold spraying (CS). The nanolaminated and ultrafine-grained structure initially created in the CNT/AlSi flaky powder was perfectly conserved, due to the typical ‘cold’ feature of CS. As discussed based on finite element analysis and single splat observation, self-alignment behavior of the flaky powders during impact also allowed the formation of the microlaminated structure. Hence, the scalable CS technique opens a new avenue for bioinspired material design and fabrication with complex shape.展开更多
Seed size and the growth environment are important variables that influence seed germination, growth and biomass of seedlings and future tree harvest and should thus be taken into account in agroforestry and reforesta...Seed size and the growth environment are important variables that influence seed germination, growth and biomass of seedlings and future tree harvest and should thus be taken into account in agroforestry and reforestation programmes for endangered species like Pterocarpus erinaceus. In the present study, to assess seedling germination and vigour in P. erinaceus as a function of seed size in two environments, 1080 seeds and 360 seedlings were evaluated at two separate sites in Côte d'Ivoire. The results show that large seeds had very high germination rates (up to 100%) and produced more vigorous plants better able to adapt to climate change. The maternal environment and seed size had a significant influence on seed germination (P < 0.05) and seedling development (P < 0.05) and biomass (P < 0.05). Seedlings were most successful at the site with a humid tropical climate (Daloa). Seedling leaves had the same resistance regardless of seed size and study site, but leaf moisture content was more stable in seedlings grown from medium and small seeds. These results will help guide conservation strategies for the species and are key factors for rural populations, loggers, and forest management structures for the silviculture of this species.展开更多
基金supported by the Lorraine University of Excellence via the DEEPSURF project(ANR 70315-IDEX-04-LUE)。
文摘The increase in the frequency and intensity of drought events expected in the coming decades in Western Europe may disturb forest biogeochemical cycles and create nutrient deficiencies in trees.One possible origin of nutrient deficiency is the disturbance of the partitioning of the green leaf pool during the leaf senescence period between resorption,foliar leaching and senesced leaves.However,the effects of drought events on this partitioning and the consequences for the maintenance of tree nutrition are poorly documented.An experiment in a beech forest in Meuse(France)was conducted to assess the effect of drought events on nutrient canopy exchanges and on the partitioning of the green leaf pool during the leaf senescence period.The aim was to identify potential nutritional consequences of droughts for trees.Monitoring nutrient dynamics,including resorption,chemistry of green and senesced leaves,foliar absorption and leaching in mature beech stands from 2012 to 2019 allowed us to compare the nutrient exchanges for three nondry and three dry years(i.e.,with an intense drought event during the growing season).During dry years,we observed a decrease by almost a third of the potassium(K)partitioning to resorption(i.e.resorption efficiency),thus reducing the K reserve in trees for the next growing season.This result suggests that with the increased drought frequency and intensity expected for the coming decades,there will be a risk of potassium deficiency in trees,as already observed in a rainfall exclusion experiment on the same study site.Reduced foliar leaching and higher parititioning to the senesced leaves for K and phosphorus(P)were also observed.In addition,a slight increase in nitrogen(N)resorption efficiency occurred during dry years which is more likely to improve tree nutrition.The calcium(Ca)negative resorption decreased,with no apparent consequence in our study site.Our results show that nutrient exchanges in the canopy and the partitioning of the green leaf pool can be modified by drought events,and may have consequences on tree nutrition.
基金financial support from the French National Research Agency(ANR)[grant number ANR-22-CE06-0031]。
文摘Elastomer blends,among which natural rubber(NR)and butadiene rubber(BR),are involved in many components of the automotive/tire industry.A comprehensive understanding of their mechanical behavior requires,among other features,a detailed description of the crosslink density in these mixtures.In the case of vulcanized immiscible blends,the distribution of the cross-link density within each of the NR-and BR-rich domains is key information,but difficult to determine using the conventional approaches used for one-component crosslinked elastomers.In this study,the vulcanization within NR/BR blends is investigated using a robust^(1)H double-quantum(DQ)MAS recoupling experiment,BaBa-xy16.Two kinds of cross-linked NR/BR blends were considered with two different microstructures for the BR component.The bulk organization of the resulting blends was first probed by analyzing the^(1)H spin-lattice relaxation behavior.In a second step,BaBa-xy16 was used to investigate,in a selective way,the cross-link heterogeneities within NR/BR blends.In particular,for immiscible NR/BR mixtures,the distribution of the cross-link density between both phases was compared and the observed differences were discussed.
文摘Modern additive manufacturing processes enable fabricating architected cellular materials of complex shape,which can be used for different purposes.Among them,lattice structures are increasingly used in applications requiring a compromise among lightness and suited mechanical properties,like improved energy absorption capacity and specific stiffness-to-weight and strength-to-weight ratios.A dedicated modeling strategy to assess the energy absorption capacity of lattice structures under uni-axial compression loading is presented in this work.The numerical model is developed in a non-linear framework accounting for the strain rate effect on the mechanical responses of the lattice structure.Four geometries,i.e.,cubic body centered cell,octet cell,rhombic-dodecahedron and truncated cuboctahedron 2+,are investigated.Specifically,the influence of the relative density of the representative volume element of each geometry,the strain-rate dependency of the bulk material and of the presence of the manufacturing process-induced geometrical imperfections on the energy absorption capacity of the lattice structure is investigated.The main outcome of this study points out the importance of correctly integrating geometrical imperfections into the modeling strategy when shock absorption applications are aimed for.
基金funded by the National Key Research&Development Program of China(2018YFD0600200)Beijing’s Science and Technology Planning Project(Z191100008519004)Major emergency science and technology projects of National Forestry and Grassland Administration(ZD202001–05).
文摘Background:Pine wilt disease(PWD)is a major ecological concern in China that has caused severe damage to millions of Chinese pines(Pinus tabulaeformis).To control the spread of PWD,it is necessary to develop an effective approach to detect its presence in the early stage of infection.One potential solution is the use of Unmanned Airborne Vehicle(UAV)based hyperspectral images(HIs).UAV-based HIs have high spatial and spectral resolution and can gather data rapidly,potentially enabling the effective monitoring of large forests.Despite this,few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine.Method:To fill this gap,we used a Random Forest(RF)algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data(data directly collected from trees in the field).We compared relative accuracy of each of these data collection methods.We built our RF model using vegetation indices(VIs),red edge parameters(REPs),moisture indices(MIs),and their combination.Results:We report several key results.For ground data,the model that combined all parameters(OA:80.17%,Kappa:0.73)performed better than VIs(OA:75.21%,Kappa:0.66),REPs(OA:79.34%,Kappa:0.67),and MIs(OA:74.38%,Kappa:0.65)in predicting the PWD stage of individual pine tree infection.REPs had the highest accuracy(OA:80.33%,Kappa:0.58)in distinguishing trees at the early stage of PWD from healthy trees.UAV-based HI data yielded similar results:the model combined VIs,REPs and MIs(OA:74.38%,Kappa:0.66)exhibited the highest accuracy in estimating the PWD stage of sampled trees,and REPs performed best in distinguishing healthy trees from trees at early stage of PWD(OA:71.67%,Kappa:0.40).Conclusion:Overall,our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage,although its accuracy must be improved before widespread use is practical.We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data.We believe that these results can be used to improve preventative measures in the control of PWD.
基金supported by National Key Research&Development Program of China“Research on key technologies for prevention and control of major disasters in plantation”(Grant No.2018YFD0600200)Beijing’s Science and Technology Planning Project“Key technologies for prevention and control of major pests in Beijing ecological public welfare forests”(Grant Nos.Z191100008519004 and Z201100008020001).
文摘Background:Anoplophora glabripennis(Motschulsky),commonly known as Asian longhorned beetle(ALB),is a wood-boring insect that can cause lethal infestation to multiple borer leaf trees.In Gansu Province,northwest China,ALB has caused a large number of deaths of a local tree species Populus gansuensis.The damaged area belongs to Gobi desert where every single tree is artificially planted and is extremely difficult to cultivate.Therefore,the monitoring of the ALB infestation at the individual tree level in the landscape is necessary.Moreover,the determination of an abnormal phenotype that can be obtained directly from remote-sensing images to predict the damage degree can greatly reduce the cost of field investigation and management.Methods:Multispectral WorldView-2(WV-2)images and 5 tree physiological factors were collected as experimental materials.One-way ANOVA of the tree’s physiological factors helped in determining the phenotype to predict damage degrees.The original bands of WV-2 and derived vegetation indices were used as reference data to construct the dataset of a prediction model.Variance inflation factor and stepwise regression analyses were used to eliminate collinearity and redundancy.Finally,three machine learning algorithms,i.e.,Random Forest(RF),Support Vector Machine(SVM),Classification And Regression Tree(CART),were applied and compared to find the best classifier for predicting the damage stage of individual P.gansuensis.Results:The confusion matrix of RF achieved the highest overall classification accuracy(86.2%)and the highest Kappa index value(0.804),indicating the potential of using WV-2 imaging to accurately detect damage stages of individual trees.In addition,the canopy color was found to be positively correlated with P.gansuensis’damage stages.Conclusions:A novel method was developed by combining WV-2 and tree physiological index for semi-automatic classification of three damage stages of P.gansuensis infested with ALB.The canopy color was determined as an abnormal phenotype that could be directly assessed using remote-sensing images at the tree level to predict the damage degree.These tools are highly applicable for driving quick and effective measures to reduce damage to pure poplar forests in Gansu Province,China.
基金supported by the School of Podiatry of Marseille
文摘Background: Heavy backpacks are often used by soldiers and firefighters. Weight carrying could reduce the speed and efficiency in task completion by altering the foot sole sensitivity and postural control.Methods: In fifteen healthy subjects, we measured the changes in sensitivity to vibrations applied to the foot sole when standing upright or walking after load carrying(30% body weight). The participants were asked to judge different vibration amplitudes applied on the 2 nd or 5 th metatarsal head and the heel at two frequencies(25 and 150 Hz) to determine the vibration threshold and the global perceptual representation(Ψ)of the vibration amplitude(Φ)given by the Stevens power function(Ψ=k×Φ~n). Any increase in negative k value indicated a reduction in sensitivity to the lowest loads. Pedobarographic measurements, with computation of the center of pressure(COP) and its deviations, were performed during weight carrying.Results: The 25-Hz vibration threshold significantly increased after weight carrying when standing upright or walking.After standing with the added loads, the absolute negative k value increased for the 25 Hz frequency. After walking with the added loads, the k coefficient increased for the two vibration frequencies. Weight carrying significantly increased both the CoP surface and CoP lateral deviation.Conclusions: Our data show that weight carrying reduces the sensory pathways from the foot sole and accentuates the center of pressure deviations.
基金financial support from China Scholarship Council for his Ph.D. projectThe TEM facility in Lille, France, is supported by the Conseil Regional du Nord-Pas de Calais and the European Regional Development Fund
文摘A fully dense carbon nanotubes (CNTs) reinforced AlSi matrix composite with the multiscale nacre-like architecture was designed and successfully realized by flake powder metallurgy followed by cold spraying (CS). The nanolaminated and ultrafine-grained structure initially created in the CNT/AlSi flaky powder was perfectly conserved, due to the typical ‘cold’ feature of CS. As discussed based on finite element analysis and single splat observation, self-alignment behavior of the flaky powders during impact also allowed the formation of the microlaminated structure. Hence, the scalable CS technique opens a new avenue for bioinspired material design and fabrication with complex shape.
基金financed by the Ministry of Higher Education and Scientific Research of Côte d’Ivoirethe French Development Agency and IRD (Institut de Recherche pour le Developpement) in the framework of PRESeD-CI 2 (Renewed Partnership for Research for Development in Côte d’Ivoire)C2D (Debt Reduction Contract) of the AMRUGECI project (Support for the Modernization and Reform of Universities and Grandes Ecoles of Côte d’Ivoire)
文摘Seed size and the growth environment are important variables that influence seed germination, growth and biomass of seedlings and future tree harvest and should thus be taken into account in agroforestry and reforestation programmes for endangered species like Pterocarpus erinaceus. In the present study, to assess seedling germination and vigour in P. erinaceus as a function of seed size in two environments, 1080 seeds and 360 seedlings were evaluated at two separate sites in Côte d'Ivoire. The results show that large seeds had very high germination rates (up to 100%) and produced more vigorous plants better able to adapt to climate change. The maternal environment and seed size had a significant influence on seed germination (P < 0.05) and seedling development (P < 0.05) and biomass (P < 0.05). Seedlings were most successful at the site with a humid tropical climate (Daloa). Seedling leaves had the same resistance regardless of seed size and study site, but leaf moisture content was more stable in seedlings grown from medium and small seeds. These results will help guide conservation strategies for the species and are key factors for rural populations, loggers, and forest management structures for the silviculture of this species.
