As the climate worsens and the demand for food grows,so does the interest in nanoagriculture.The interaction between plants and nanomaterials(NMs)has been extensively and intensively examined.However,stopping at the o...As the climate worsens and the demand for food grows,so does the interest in nanoagriculture.The interaction between plants and nanomaterials(NMs)has been extensively and intensively examined.However,stopping at the outcome of a phenomenon is often insufficient.Therefore,we introduce three important processes of nanoparticleplant interactions:translocation,transformation,and plant metabolism.During the migration of nanoparticles,size and surface electrical properties are the main determining factors.Additionally,the interaction of nanoparticles with cell membranes is another key aspect of research.The transformation of nanoparticles in plants is mainly due to redox substances.The way that nanoparticles affect plant metabolism may be able to shed light on the interaction of nanoparticles with plants.This review adds to the existing knowledge on the design of nanoagrochemicals and summarizes the mechanism of interaction of NMs with plants.In this way,NMs can be used for their beneficial effects and thus contribute to the maintenance of food security and sustainable development.展开更多
To implement on-line, real-time monitoring for the surface morphology of Plasma-Facing Materials(PFMs) in tokamak, we developed a Laser Speckle Interferometry measurement approach. A laser ablation method was used to ...To implement on-line, real-time monitoring for the surface morphology of Plasma-Facing Materials(PFMs) in tokamak, we developed a Laser Speckle Interferometry measurement approach. A laser ablation method was used to simulate the erosion process during Plasma-Wall Interactions in a tokamak. In the present investigation, we evaluated the results of laser ablation morphology changes on the surface of Mo material reconstructed by four different approaches(Flood-fill, Quality-guided, Discrete Cosine Transform(DCT) and Weighted-DCT). The morphology results measured by the weighted-DCT approach are very close to the measurement results from confocal microscopy with an average error rate within 7%. It is verified that the weighted-DCT algorithm has high accuracy and can efficiently reduce the influence of noise pollution coming from laser ablation, which is used as a proxy for erosion from plasma wall interaction. Additionally, the CPU computer time has been shortened. This is of great significance for the real-time monitoring of PFMs’ morphology in the Experimental Advanced Superconducting Tokamak(EAST) in the future.展开更多
The Book of Songs is an important part of Chinese traditional culture and enjoys a high reputation at home and abroad.This article is based on Turi’s theory of translation norms,and takes the English translation of T...The Book of Songs is an important part of Chinese traditional culture and enjoys a high reputation at home and abroad.This article is based on Turi’s theory of translation norms,and takes the English translation of The Book of Songs·Jing Jing by Richard Jacob and Xu Yuanchong as the research object.Comparative studies are made on the historical nature of understanding,the normativeness of translation,and the application of the fusion of horizons in the two versions of the Book of Songs.Incorporating history into translation brings the translation closer to the roots of history.The comparative research method proposed in this article can be widely used in various ancient literature studies,and has important theoretical and application values.展开更多
With the advent of the era of big data and the development and construction of smart campuses,the campus is gradually moving towards digitalization,networking and informationization.The campus card is an important par...With the advent of the era of big data and the development and construction of smart campuses,the campus is gradually moving towards digitalization,networking and informationization.The campus card is an important part of the construction of a smart campus,and the massive data it generates can indirectly reflect the living conditions of students at school.In the face of the campus card,how to quickly and accurately obtain the information required by users from the massive data sets has become an urgent problem that needs to be solved.This paper proposes a data mining algorithm based on K-Means clustering and time series.It analyzes the consumption data of a college student’s card to deeply mine and analyze the daily life consumer behavior habits of students,and to make an accurate judgment on the specific life consumer behavior.The algorithm proposed in this paper provides a practical reference for the construction of smart campuses in universities,and has important theoretical and application values.展开更多
Background:We previously reported that interstitial injection of bleomycin(BLM)reduces the size of early-stage extracranial arteriovenous malformation(AVM).Here,we sought to investigate the potential mechanism of BLM ...Background:We previously reported that interstitial injection of bleomycin(BLM)reduces the size of early-stage extracranial arteriovenous malformation(AVM).Here,we sought to investigate the potential mechanism of BLM in treating extracranial AVM.Methods:Samples of human extracranial AVM(n=3)with no pharmacological treatment were harvested.AVM endothelial cells were isolated and cultured in primary cell culture.The transcriptome was examined using RNAsequencing,and differentially expressed C-type lectin domain family 14 member A(CLEC14A)was validated at the transcriptomic and protein levels.Immunocytochemical staining of CLEC14A was performed in samples of human extracranial AVM,with and without BLM treatment.Results:Through second-generation sequencing,we found that the expression of 5689 genes were differentially increased or decreased following 24-h BLM stimulation.We found that CLEC14A may play an important role in the progression of AVM and can be inhibited by BLM treatment.Conclusion:BLM inhibited CLEC14A expression to attenuate the progression of AVM.展开更多
Lithium's(Li)ubiquitous distribution in the environment is a rising concern due to its rapid proliferation in the modern electronic industry.Li enigmatic entry into the terrestrial food chain raises many questions...Lithium's(Li)ubiquitous distribution in the environment is a rising concern due to its rapid proliferation in the modern electronic industry.Li enigmatic entry into the terrestrial food chain raises many questions and uncertainties that may pose a grave threat to living biota.We examined the leverage existing published articles regarding advances in global Li resources,interplay with plants,and possible involvement with living organisms,especially humans and animals.Globally,Li concentration(<10 e300 mg kg1)is detected in agricultural soil,and their pollutant levels vary with space and time.High mobility of Li results in higher accumulation in plants,but the clear mechanisms and specific functions remain unknown.Our assessment reveals the causal relationship between Li level and biota health.For example,lower Li intake(<0.6 mM in serum)leads to mental disorders,while higher intake(>1.5 mM in serum)induces thyroid,stomach,kidney,and reproductive system dysfunctions in humans and animals.However,there is a serious knowledge gap regarding Li regulatory standards in environmental compartments,and mechanistic approaches to unveil its consequences are needed.Furthermore,aggressive efforts are required to define optimum levels of Li for the normal functioning of animals,plants,and humans.This review is designed to revitalize the current status of Li research and identify the key knowledge gaps to fight back against the mountainous challenges of Li during the recent digital revolution.Additionally,we propose pathways to overcome Li problems and develop a strategy for effective,safe,and acceptable applications.展开更多
The application of autonomous agricultural vehicles is gaining popularity as a way to increase production efficiency and lower operational costs.To achieve high performance,perception tasks(such as obstacle detection,...The application of autonomous agricultural vehicles is gaining popularity as a way to increase production efficiency and lower operational costs.To achieve high performance,perception tasks(such as obstacle detection,road extraction,and drivable area extraction)are of great importance.Compared with structured roads,field roads between farmlands,including unstructured roads and semi-structured roads,are unfavorable for autonomous agricultural vehicle driving due to their bumpiness and unstructured nature.This study proposed an extraction method for the straight field roads between farmlands.The proposed method was based on the point cloud data acquired by LiDAR(Velodyne VLP-16)mounted on a John Deere 12046B-1204 tractor.The proposed method has three aspects:Euclidean Clustering-based extraction,boundary-based extraction,and road point cloud curve segment modification.Firstly,Euclidean Clustering with K-Dimensional(KD)-Tree data structure was adopted to extract the road curve segments close to the LiDAR composed of road points.Secondly,the boundary lines constraint was constructed to extract the distant road curve segments.Thirdly,the local distance ratio was used to modify the extracted road curve segments.The average extraction accuracy for both semi-structured and unstructured roads exceeded 98%,and the false positive rate(FPR)was less than 0.5%.These experimental findings demonstrated that the proposed road extraction method was precise and effective.The proposed method of this study can be applied to enhance the perception ability of autonomous agricultural vehicles thereby increasing the efficiency and safety of field road driving.展开更多
Unmanned driving of agricultural machinery has garnered significant attention in recent years,especially with the development of precision farming and sensor technologies.To achieve high performance and low cost,perce...Unmanned driving of agricultural machinery has garnered significant attention in recent years,especially with the development of precision farming and sensor technologies.To achieve high performance and low cost,perception tasks are of great importance.In this study,a low-cost and high-safety method was proposed for field road recognition in unmanned agricultural machinery.The approach of this study utilized point clouds,with low-resolution Lidar point clouds as inputs,generating high-resolution point clouds and Bird's Eye View(BEV)images that were encoded with several basic statistics.Using a BEV representation,road detection was reduced to a single-scale problem that could be addressed with an improved U-Net++neural network.Three enhancements were proposed for U-Net++:1)replacing the convolutional kernel in the original U-Net++ with an Asymmetric Convolution Block(ACBlock);2)adding a multi-branch Asymmetric Dilated Convolutional Block(MADC)in the highest semantic information layer;3)adding an Attention Gate(AG)model to the long-skip-connection in the decoding stage.The results of experiments of this study showed that our algorithm achieved a Mean Intersection Over Union of 96.54% on the 16-channel point clouds,which was 7.35 percentage points higher than U-Net++.Furthermore,the average processing time of the model was about 70 ms,meeting the time requirements of unmanned driving in agricultural machinery.The proposed method of this study can be applied to enhance the perception ability of unmanned agricultural machinery thereby increasing the safety of field road driving.展开更多
Plant uptake of silver nanoparticles(Ag NPs)and ions(Ag^(+))largely depends on their exchangeable and soil-bound fractions in soils,which may be influenced by biochar amendment.This study investigated the effects of b...Plant uptake of silver nanoparticles(Ag NPs)and ions(Ag^(+))largely depends on their exchangeable and soil-bound fractions in soils,which may be influenced by biochar amendment.This study investigated the effects of biochar amendment(0.1%and 1.0%)on soil sorption of Ag NPs and Ag^(+),their soil-bound fractions,and their uptake and translocation by radish grown in a loamy sand soil spiked with 1 mg/kg Ag NPs or Ag^(+).Sorption of Ag^(+)to the soils was much greater than that of Ag NPs,mainly because negatively charged soil particles would attract Ag^(+),but repel negatively charged Ag NPs.Biochar amend-ment at 1.0%(by weight)significantly decreased the reducible fraction of Ag^(+)in the soils with and without radish plants and increased the oxidisable fraction of Ag NPs in the soils with radish plants.Biochar amendment had no significant effect on Ag uptake by radish plants(p>0.05),probably due to low exchangeable Ag fractions in all experimental treatments.In this short-term experiment(35 days),the addition of 1 mg/kg Ag NPs or Ag^(+)did not substantially elevate the level of Ag in radish roots(0.05±0.02-1.06±0.98 mg/kg)and shoots(0.01±0.00-0.03±0.01 mg/kg),compared to the blank control(p>0.05).Radish uptake of Ag NPs and Ag^(+)at the environmentally-relevant concentration was low with root concentration factors between 0.03±0.03 to 0.29±0.21 and root-to-shoot translocation factors between 0.08±0.10 to 0.89±1.21,which may partially explain the non-significant effect of biochar amendment on Ag uptake.展开更多
基金supported by the National Key R&D Program of China(2017YFD0801300,2017YFD0801103)the Key National Natural Science Foundation of China(No.41130526)+1 种基金Professor workstation in Yuhuangmiao Town,Shanghe County,China Agricultural UniversityProfessor Workstation in Sunji Town,Shanghe County,China Agricultural University.
文摘As the climate worsens and the demand for food grows,so does the interest in nanoagriculture.The interaction between plants and nanomaterials(NMs)has been extensively and intensively examined.However,stopping at the outcome of a phenomenon is often insufficient.Therefore,we introduce three important processes of nanoparticleplant interactions:translocation,transformation,and plant metabolism.During the migration of nanoparticles,size and surface electrical properties are the main determining factors.Additionally,the interaction of nanoparticles with cell membranes is another key aspect of research.The transformation of nanoparticles in plants is mainly due to redox substances.The way that nanoparticles affect plant metabolism may be able to shed light on the interaction of nanoparticles with plants.This review adds to the existing knowledge on the design of nanoagrochemicals and summarizes the mechanism of interaction of NMs with plants.In this way,NMs can be used for their beneficial effects and thus contribute to the maintenance of food security and sustainable development.
基金supported by the National Key R&D Program of China (No. 2017YFE0301304)National Natural Science Foundation of China (Nos. 11605023, 11805028, 11705020)+1 种基金China Postdoctoral Science Foundation (Nos. 2017T100172, 2016M591423)the Fundamental Research Funds for the Central Universities (Nos. DUT17RC(4)53, DUT18LK38)
文摘To implement on-line, real-time monitoring for the surface morphology of Plasma-Facing Materials(PFMs) in tokamak, we developed a Laser Speckle Interferometry measurement approach. A laser ablation method was used to simulate the erosion process during Plasma-Wall Interactions in a tokamak. In the present investigation, we evaluated the results of laser ablation morphology changes on the surface of Mo material reconstructed by four different approaches(Flood-fill, Quality-guided, Discrete Cosine Transform(DCT) and Weighted-DCT). The morphology results measured by the weighted-DCT approach are very close to the measurement results from confocal microscopy with an average error rate within 7%. It is verified that the weighted-DCT algorithm has high accuracy and can efficiently reduce the influence of noise pollution coming from laser ablation, which is used as a proxy for erosion from plasma wall interaction. Additionally, the CPU computer time has been shortened. This is of great significance for the real-time monitoring of PFMs’ morphology in the Experimental Advanced Superconducting Tokamak(EAST) in the future.
基金Science and Technology Project of Guizhou Province of China(Grant QKHJC[2019]1403)and(Grant QKHJC[2019]1041)Guizhou Province Colleges and Universities Top Technology Talent Support Program(Grant QJHKY[2016]068).
文摘The Book of Songs is an important part of Chinese traditional culture and enjoys a high reputation at home and abroad.This article is based on Turi’s theory of translation norms,and takes the English translation of The Book of Songs·Jing Jing by Richard Jacob and Xu Yuanchong as the research object.Comparative studies are made on the historical nature of understanding,the normativeness of translation,and the application of the fusion of horizons in the two versions of the Book of Songs.Incorporating history into translation brings the translation closer to the roots of history.The comparative research method proposed in this article can be widely used in various ancient literature studies,and has important theoretical and application values.
基金Science and Technology Project of Guizhou Province of China(Grant QKHJC[2019]1403)and(Grant QKHJC[2019]1041)Guizhou Province Colleges and Universities Top Technology Talent Support Program(Grant QJHKY[2016]068).
文摘With the advent of the era of big data and the development and construction of smart campuses,the campus is gradually moving towards digitalization,networking and informationization.The campus card is an important part of the construction of a smart campus,and the massive data it generates can indirectly reflect the living conditions of students at school.In the face of the campus card,how to quickly and accurately obtain the information required by users from the massive data sets has become an urgent problem that needs to be solved.This paper proposes a data mining algorithm based on K-Means clustering and time series.It analyzes the consumption data of a college student’s card to deeply mine and analyze the daily life consumer behavior habits of students,and to make an accurate judgment on the specific life consumer behavior.The algorithm proposed in this paper provides a practical reference for the construction of smart campuses in universities,and has important theoretical and application values.
基金supported,in whole or in part,by the Project of Biobank(grant no.YBKA201902)from Shanghai Ninth People’s Hospital,Shanghai Jiao Tong University School of MedicineMulti-center Clinical Research Programs(grant no.DLY201613),Clinical Research Center,Shanghai Jiao Tong University School of MedicineRare Disease Registration Platform of Shanghai Ninth People’s Hospital,Shanghai Jiao Tong University School of Medicine(grant no.JYHJB02).
文摘Background:We previously reported that interstitial injection of bleomycin(BLM)reduces the size of early-stage extracranial arteriovenous malformation(AVM).Here,we sought to investigate the potential mechanism of BLM in treating extracranial AVM.Methods:Samples of human extracranial AVM(n=3)with no pharmacological treatment were harvested.AVM endothelial cells were isolated and cultured in primary cell culture.The transcriptome was examined using RNAsequencing,and differentially expressed C-type lectin domain family 14 member A(CLEC14A)was validated at the transcriptomic and protein levels.Immunocytochemical staining of CLEC14A was performed in samples of human extracranial AVM,with and without BLM treatment.Results:Through second-generation sequencing,we found that the expression of 5689 genes were differentially increased or decreased following 24-h BLM stimulation.We found that CLEC14A may play an important role in the progression of AVM and can be inhibited by BLM treatment.Conclusion:BLM inhibited CLEC14A expression to attenuate the progression of AVM.
基金funded by the The 111 project of the Education Ministry of China(B18053)The National Natural Science Foundation(32130081).
文摘Lithium's(Li)ubiquitous distribution in the environment is a rising concern due to its rapid proliferation in the modern electronic industry.Li enigmatic entry into the terrestrial food chain raises many questions and uncertainties that may pose a grave threat to living biota.We examined the leverage existing published articles regarding advances in global Li resources,interplay with plants,and possible involvement with living organisms,especially humans and animals.Globally,Li concentration(<10 e300 mg kg1)is detected in agricultural soil,and their pollutant levels vary with space and time.High mobility of Li results in higher accumulation in plants,but the clear mechanisms and specific functions remain unknown.Our assessment reveals the causal relationship between Li level and biota health.For example,lower Li intake(<0.6 mM in serum)leads to mental disorders,while higher intake(>1.5 mM in serum)induces thyroid,stomach,kidney,and reproductive system dysfunctions in humans and animals.However,there is a serious knowledge gap regarding Li regulatory standards in environmental compartments,and mechanistic approaches to unveil its consequences are needed.Furthermore,aggressive efforts are required to define optimum levels of Li for the normal functioning of animals,plants,and humans.This review is designed to revitalize the current status of Li research and identify the key knowledge gaps to fight back against the mountainous challenges of Li during the recent digital revolution.Additionally,we propose pathways to overcome Li problems and develop a strategy for effective,safe,and acceptable applications.
基金financially supported by the National Key Research&Development Project(Grant No.2021YFB3901302)the Beijing Municipal Science and Technology Project(Grant No.Z201100008020008).
文摘The application of autonomous agricultural vehicles is gaining popularity as a way to increase production efficiency and lower operational costs.To achieve high performance,perception tasks(such as obstacle detection,road extraction,and drivable area extraction)are of great importance.Compared with structured roads,field roads between farmlands,including unstructured roads and semi-structured roads,are unfavorable for autonomous agricultural vehicle driving due to their bumpiness and unstructured nature.This study proposed an extraction method for the straight field roads between farmlands.The proposed method was based on the point cloud data acquired by LiDAR(Velodyne VLP-16)mounted on a John Deere 12046B-1204 tractor.The proposed method has three aspects:Euclidean Clustering-based extraction,boundary-based extraction,and road point cloud curve segment modification.Firstly,Euclidean Clustering with K-Dimensional(KD)-Tree data structure was adopted to extract the road curve segments close to the LiDAR composed of road points.Secondly,the boundary lines constraint was constructed to extract the distant road curve segments.Thirdly,the local distance ratio was used to modify the extracted road curve segments.The average extraction accuracy for both semi-structured and unstructured roads exceeded 98%,and the false positive rate(FPR)was less than 0.5%.These experimental findings demonstrated that the proposed road extraction method was precise and effective.The proposed method of this study can be applied to enhance the perception ability of autonomous agricultural vehicles thereby increasing the efficiency and safety of field road driving.
基金financially supported by the National Key R&D Program of China and Shandong Province,China(Grant No.2021YFB3901300).
文摘Unmanned driving of agricultural machinery has garnered significant attention in recent years,especially with the development of precision farming and sensor technologies.To achieve high performance and low cost,perception tasks are of great importance.In this study,a low-cost and high-safety method was proposed for field road recognition in unmanned agricultural machinery.The approach of this study utilized point clouds,with low-resolution Lidar point clouds as inputs,generating high-resolution point clouds and Bird's Eye View(BEV)images that were encoded with several basic statistics.Using a BEV representation,road detection was reduced to a single-scale problem that could be addressed with an improved U-Net++neural network.Three enhancements were proposed for U-Net++:1)replacing the convolutional kernel in the original U-Net++ with an Asymmetric Convolution Block(ACBlock);2)adding a multi-branch Asymmetric Dilated Convolutional Block(MADC)in the highest semantic information layer;3)adding an Attention Gate(AG)model to the long-skip-connection in the decoding stage.The results of experiments of this study showed that our algorithm achieved a Mean Intersection Over Union of 96.54% on the 16-channel point clouds,which was 7.35 percentage points higher than U-Net++.Furthermore,the average processing time of the model was about 70 ms,meeting the time requirements of unmanned driving in agricultural machinery.The proposed method of this study can be applied to enhance the perception ability of unmanned agricultural machinery thereby increasing the safety of field road driving.
基金supported by Agriculture and Food Research Initiative Competitive Grant(2016-67017-24514,2017-67017-26168)the Hatch Act Formula Grant(1012794,1021038)。
文摘Plant uptake of silver nanoparticles(Ag NPs)and ions(Ag^(+))largely depends on their exchangeable and soil-bound fractions in soils,which may be influenced by biochar amendment.This study investigated the effects of biochar amendment(0.1%and 1.0%)on soil sorption of Ag NPs and Ag^(+),their soil-bound fractions,and their uptake and translocation by radish grown in a loamy sand soil spiked with 1 mg/kg Ag NPs or Ag^(+).Sorption of Ag^(+)to the soils was much greater than that of Ag NPs,mainly because negatively charged soil particles would attract Ag^(+),but repel negatively charged Ag NPs.Biochar amend-ment at 1.0%(by weight)significantly decreased the reducible fraction of Ag^(+)in the soils with and without radish plants and increased the oxidisable fraction of Ag NPs in the soils with radish plants.Biochar amendment had no significant effect on Ag uptake by radish plants(p>0.05),probably due to low exchangeable Ag fractions in all experimental treatments.In this short-term experiment(35 days),the addition of 1 mg/kg Ag NPs or Ag^(+)did not substantially elevate the level of Ag in radish roots(0.05±0.02-1.06±0.98 mg/kg)and shoots(0.01±0.00-0.03±0.01 mg/kg),compared to the blank control(p>0.05).Radish uptake of Ag NPs and Ag^(+)at the environmentally-relevant concentration was low with root concentration factors between 0.03±0.03 to 0.29±0.21 and root-to-shoot translocation factors between 0.08±0.10 to 0.89±1.21,which may partially explain the non-significant effect of biochar amendment on Ag uptake.
