The YOLOx-s network does not sufficiently meet the accuracy demand of equipment detection in the autonomous inspection of distribution lines by Unmanned Aerial Vehicle(UAV)due to the complex background of distribution...The YOLOx-s network does not sufficiently meet the accuracy demand of equipment detection in the autonomous inspection of distribution lines by Unmanned Aerial Vehicle(UAV)due to the complex background of distribution lines,variable morphology of equipment,and large differences in equipment sizes.Therefore,aiming at the difficult detection of power equipment in UAV inspection images,we propose a multi-equipment detection method for inspection of distribution lines based on the YOLOx-s.Based on the YOLOx-s network,we make the following improvements:1)The Receptive Field Block(RFB)module is added after the shallow feature layer of the backbone network to expand the receptive field of the network.2)The Coordinate Attention(CA)module is added to obtain the spatial direction information of the targets and improve the accuracy of target localization.3)After the first fusion of features in the Path Aggregation Network(PANet),the Adaptively Spatial Feature Fusion(ASFF)module is added to achieve efficient re-fusion of multi-scale deep and shallow feature maps by assigning adaptive weight parameters to features at different scales.4)The loss function Binary Cross Entropy(BCE)Loss in YOLOx-s is replaced by Focal Loss to alleviate the difficulty of network convergence caused by the imbalance between positive and negative samples of small-sized targets.The experiments take a private dataset consisting of four types of power equipment:Transformers,Isolators,Drop Fuses,and Lightning Arrestors.On average,the mean Average Precision(mAP)of the proposed method can reach 93.64%,an increase of 3.27%.The experimental results show that the proposed method can better identify multiple types of power equipment of different scales at the same time,which helps to improve the intelligence of UAV autonomous inspection in distribution lines.展开更多
Due to the large unexplored compositional space,long development cycle,and high cost of traditional trial-anderror experiments,designing high strength aluminum-lithium alloys is a great challenge.This work establishes...Due to the large unexplored compositional space,long development cycle,and high cost of traditional trial-anderror experiments,designing high strength aluminum-lithium alloys is a great challenge.This work establishes a performance-oriented machine learning design strategy for aluminum-lithium alloys to simplify and shorten the development cycle.The calculation results indicate that radial basis function(RBF)neural networks exhibit better predictive ability than back propagation(BP)neural networks.The RBF neural network predicted tensile and yield strengths with determination coefficients of 0.90 and 0.96,root mean square errors of 30.68 and 25.30,and mean absolute errors of 28.15 and 19.08,respectively.In the validation experiment,the comparison between experimental data and predicted data demonstrated the robustness of the two neural network models.The tensile and yield strengths of Al-2Li-1Cu-3Mg-0.2Zr(wt.%)alloy are 17.8 and 3.5 MPa higher than those of the Al-1Li4.5Cu-0.2Zr(wt.%)alloy,which has the best overall performance,respectively.It demonstrates the reliability of the neural network model in designing high strength aluminum-lithium alloys,which provides a way to improve research and development efficiency.展开更多
The prediction of particles less than 2.5 micrometers in diameter(PM2.5)in fog and haze has been paid more and more attention,but the prediction accuracy of the results is not ideal.Haze prediction algorithms based on...The prediction of particles less than 2.5 micrometers in diameter(PM2.5)in fog and haze has been paid more and more attention,but the prediction accuracy of the results is not ideal.Haze prediction algorithms based on traditional numerical and statistical prediction have poor effects on nonlinear data prediction of haze.In order to improve the effects of prediction,this paper proposes a haze feature extraction and pollution level identification pre-warning algorithm based on feature selection and integrated learning.Minimum Redundancy Maximum Relevance method is used to extract low-level features of haze,and deep confidence network is utilized to extract high-level features.eXtreme Gradient Boosting algorithm is adopted to fuse low-level and high-level features,as well as predict haze.Establish PM2.5 concentration pollution grade classification index,and grade the forecast data.The expert experience knowledge is utilized to assist the optimization of the pre-warning results.The experiment results show the presented algorithm can get better prediction effects than the results of Support Vector Machine(SVM)and Back Propagation(BP)widely used at present,the accuracy has greatly improved compared with SVM and BP.展开更多
The performances of diesel contrasted with that of biodiesel, such as HC and CO and NOx and fume and particles discharge, are studied on. The contents of HC, CO, NOx and flue gas are measured by Japan 163 Gas Chromato...The performances of diesel contrasted with that of biodiesel, such as HC and CO and NOx and fume and particles discharge, are studied on. The contents of HC, CO, NOx and flue gas are measured by Japan 163 Gas Chromatograph, USA 48 CO Analyser, Japan MEXA-7200H and FBY-201 flue gas analyzer, respectively. The experimental results shows HC dis-charge of biodiesel B20 decreases with the increase of rate of revolution;NOx discharge of biodiesel B5 and biodiesel B20 increase with the increase of torque;NOx discharge increases with the increase of adding biodiesel at the same torque;Flue gas discharge of biodiesel B5 and biodiesel B20 firstly increase and then decrease with the increase of torque;Particle discharge decreases with the increase of the amount of biodiesel.展开更多
We study two particle quantum walks on one dimensional chain. Probability distribution of two particle quantum walks is dependent on the initial state, and symmetric quantum walk or asymmetric quantum walk is analogou...We study two particle quantum walks on one dimensional chain. Probability distribution of two particle quantum walks is dependent on the initial state, and symmetric quantum walk or asymmetric quantum walk is analogous to that of one particle quantum walk. The quantum correlation probability is much different from classical coincidence probability. The difference reflects quantum interference between two particles.展开更多
Metformin has been used for the treatment of type II diabetes mellitus for decades due to its safety,low cost,and outstanding hypoglycemic effect clinically.The mechanisms underlying these benefits are complex and sti...Metformin has been used for the treatment of type II diabetes mellitus for decades due to its safety,low cost,and outstanding hypoglycemic effect clinically.The mechanisms underlying these benefits are complex and still not fully understood.Inhibition of mitochondrial respiratory-chain complex I is the most described downstream mechanism of metformin,leading to reduced ATP production and activation of AMP-activated protein kinase(AMPK).Meanwhile,many novel targets of metformin have been gradually discovered.In recent years,multiple pre-clinical and clinical studies are committed to extend the indications of metformin in addition to diabetes.Herein,we summarized the benefits of metformin in four types of diseases,including metabolic associated diseases,cancer,aging and age-related diseases,neurological disorders.We comprehensively discussed the pharmacokinetic properties and the mechanisms of action,treatment strategies,the clinical application,the potential risk of metformin in various diseases.This review provides a brief summary of the benefits and concerns of metformin,aiming to interest scientists to consider and explore the common and specific mechanisms and guiding for the further research.Although there have been countless studies of metformin,longitudinal research in each field is still much warranted.展开更多
Although commercial gas flow was produced in several wells with recent years'exploration of Longfengshan area in Changling fault sag,the formation mechanism and controlling factors for high-quality reservoirs stil...Although commercial gas flow was produced in several wells with recent years'exploration of Longfengshan area in Changling fault sag,the formation mechanism and controlling factors for high-quality reservoirs still remained undefined.Here,the Yingcheng tight gas reservoirs of Longfengshan area are used as an example to characterize high-quality reservoir formation mechanism and distribution rules.Based on the thin section,SEM,X-ray diffraction,computed tomography(CT)scanning,burial history,constant-rate mercury penetration and physical properties testing,formation mechanism and controlling factors for high-quality reservoirs were analyzed.Results show the following characteristics.First,the reservoir is dominated by chlorite and laumontite cements,and compaction is the most important factor to control reservoir physical properties.According to this,the reservoir can be divided into compacted tight sandstones,chlorite-cemented sandstones and laumontite-cemented sandstones.Second,the high-quality reservoirs are formed due to early extensive laumontite precipitation and the later dissolution of laumontite by organic acid.Meanwhile,it is found that the distribution of cementation and dissolution exhibits some regulations in sedimentary facies,and the distribution is mainly effected and controlled by the lake water and charging of fresh water.Besides,the distribution model of various types of sandstones was established.Studies over diagenesis and sedimentary facies reveal that the high-quality laumontite-cemented sandstones exist in the outside subaqueous fan-delta of the deep sag in Longfengshan area.These findings have been validated by recent exploration wells which obtained high industrial gas flow.展开更多
To solve the problem of directional arrangement of small template particles,we designed a lamination technique for the preparation of dense ceramics with high texture degree based on the phase-field simulation.Referri...To solve the problem of directional arrangement of small template particles,we designed a lamination technique for the preparation of dense ceramics with high texture degree based on the phase-field simulation.Referring to the experimental data,the initial microstructures of the template and matrix layers were constructed.The effect of the average length of template on the coarsening behavior of the template layer was investigated in detail.The results suggested that there was a stable stage in the growth process of template grains,which would be conducive to the densification of textured ceramics.This phenomenon has been confirmed by corresponding experiments.In addition,we demonstrated a critical thickness of matrix layer for the preparation of highly textured ceramics by using the template with various average lengths.The grain size of highly textured ceramics could be controlled by adjusting the template size and thickness of matrix layer.展开更多
基金supported by the National Natural Science Foundation of China under Grants 62362040,61662033supported by the Science and Technology Project of the State Grid Jiangxi Electric Power Co.,Ltd.of China under Grant 521820210006.
文摘The YOLOx-s network does not sufficiently meet the accuracy demand of equipment detection in the autonomous inspection of distribution lines by Unmanned Aerial Vehicle(UAV)due to the complex background of distribution lines,variable morphology of equipment,and large differences in equipment sizes.Therefore,aiming at the difficult detection of power equipment in UAV inspection images,we propose a multi-equipment detection method for inspection of distribution lines based on the YOLOx-s.Based on the YOLOx-s network,we make the following improvements:1)The Receptive Field Block(RFB)module is added after the shallow feature layer of the backbone network to expand the receptive field of the network.2)The Coordinate Attention(CA)module is added to obtain the spatial direction information of the targets and improve the accuracy of target localization.3)After the first fusion of features in the Path Aggregation Network(PANet),the Adaptively Spatial Feature Fusion(ASFF)module is added to achieve efficient re-fusion of multi-scale deep and shallow feature maps by assigning adaptive weight parameters to features at different scales.4)The loss function Binary Cross Entropy(BCE)Loss in YOLOx-s is replaced by Focal Loss to alleviate the difficulty of network convergence caused by the imbalance between positive and negative samples of small-sized targets.The experiments take a private dataset consisting of four types of power equipment:Transformers,Isolators,Drop Fuses,and Lightning Arrestors.On average,the mean Average Precision(mAP)of the proposed method can reach 93.64%,an increase of 3.27%.The experimental results show that the proposed method can better identify multiple types of power equipment of different scales at the same time,which helps to improve the intelligence of UAV autonomous inspection in distribution lines.
基金supported by the National Natural Science Foundation of China(Nos.52074246,52275390,52205429,52201146)National Defense Basic Scientific Research Program of China(JCKY2020408B002)Key Research and Development Program of Shanxi Province(202102050201011,202202050201014).
文摘Due to the large unexplored compositional space,long development cycle,and high cost of traditional trial-anderror experiments,designing high strength aluminum-lithium alloys is a great challenge.This work establishes a performance-oriented machine learning design strategy for aluminum-lithium alloys to simplify and shorten the development cycle.The calculation results indicate that radial basis function(RBF)neural networks exhibit better predictive ability than back propagation(BP)neural networks.The RBF neural network predicted tensile and yield strengths with determination coefficients of 0.90 and 0.96,root mean square errors of 30.68 and 25.30,and mean absolute errors of 28.15 and 19.08,respectively.In the validation experiment,the comparison between experimental data and predicted data demonstrated the robustness of the two neural network models.The tensile and yield strengths of Al-2Li-1Cu-3Mg-0.2Zr(wt.%)alloy are 17.8 and 3.5 MPa higher than those of the Al-1Li4.5Cu-0.2Zr(wt.%)alloy,which has the best overall performance,respectively.It demonstrates the reliability of the neural network model in designing high strength aluminum-lithium alloys,which provides a way to improve research and development efficiency.
基金The work was financially supported by National Natural Science Fund of China,specific grant numbers were 61371143 and 61662033initials of authors who received the grants were respectively Z.YM,H.L,and the URLs to sponsors’websites was http://www.nsfc.gov.cn/.This paper was supported by National Natural Science Fund of China(Grant Nos.61371143,61662033).
文摘The prediction of particles less than 2.5 micrometers in diameter(PM2.5)in fog and haze has been paid more and more attention,but the prediction accuracy of the results is not ideal.Haze prediction algorithms based on traditional numerical and statistical prediction have poor effects on nonlinear data prediction of haze.In order to improve the effects of prediction,this paper proposes a haze feature extraction and pollution level identification pre-warning algorithm based on feature selection and integrated learning.Minimum Redundancy Maximum Relevance method is used to extract low-level features of haze,and deep confidence network is utilized to extract high-level features.eXtreme Gradient Boosting algorithm is adopted to fuse low-level and high-level features,as well as predict haze.Establish PM2.5 concentration pollution grade classification index,and grade the forecast data.The expert experience knowledge is utilized to assist the optimization of the pre-warning results.The experiment results show the presented algorithm can get better prediction effects than the results of Support Vector Machine(SVM)and Back Propagation(BP)widely used at present,the accuracy has greatly improved compared with SVM and BP.
文摘The performances of diesel contrasted with that of biodiesel, such as HC and CO and NOx and fume and particles discharge, are studied on. The contents of HC, CO, NOx and flue gas are measured by Japan 163 Gas Chromatograph, USA 48 CO Analyser, Japan MEXA-7200H and FBY-201 flue gas analyzer, respectively. The experimental results shows HC dis-charge of biodiesel B20 decreases with the increase of rate of revolution;NOx discharge of biodiesel B5 and biodiesel B20 increase with the increase of torque;NOx discharge increases with the increase of adding biodiesel at the same torque;Flue gas discharge of biodiesel B5 and biodiesel B20 firstly increase and then decrease with the increase of torque;Particle discharge decreases with the increase of the amount of biodiesel.
文摘We study two particle quantum walks on one dimensional chain. Probability distribution of two particle quantum walks is dependent on the initial state, and symmetric quantum walk or asymmetric quantum walk is analogous to that of one particle quantum walk. The quantum correlation probability is much different from classical coincidence probability. The difference reflects quantum interference between two particles.
基金founded by China Postdoctoral Science Foundation(No.2021M703345)the National Natural Science Foundation of China(Nos.82130099,81971265,and 81821005)+3 种基金Shanghai Science and Technology Development Funds(Nos.22YF1457100 and 22ZR1415200)National Key R&D Program of China(No.2022YFA1303802)the National Natural Science Foundation of China for Innovation Research Group(No.81821005)the Lingang Laboratory(Nos.LG202103-03-04,LG202103-03-01,and LG202103-03-05).
文摘Metformin has been used for the treatment of type II diabetes mellitus for decades due to its safety,low cost,and outstanding hypoglycemic effect clinically.The mechanisms underlying these benefits are complex and still not fully understood.Inhibition of mitochondrial respiratory-chain complex I is the most described downstream mechanism of metformin,leading to reduced ATP production and activation of AMP-activated protein kinase(AMPK).Meanwhile,many novel targets of metformin have been gradually discovered.In recent years,multiple pre-clinical and clinical studies are committed to extend the indications of metformin in addition to diabetes.Herein,we summarized the benefits of metformin in four types of diseases,including metabolic associated diseases,cancer,aging and age-related diseases,neurological disorders.We comprehensively discussed the pharmacokinetic properties and the mechanisms of action,treatment strategies,the clinical application,the potential risk of metformin in various diseases.This review provides a brief summary of the benefits and concerns of metformin,aiming to interest scientists to consider and explore the common and specific mechanisms and guiding for the further research.Although there have been countless studies of metformin,longitudinal research in each field is still much warranted.
基金the financial support of the National Nature and Science Fund project(41302115)Post-doctoral Science Fund(2012M511941).
文摘Although commercial gas flow was produced in several wells with recent years'exploration of Longfengshan area in Changling fault sag,the formation mechanism and controlling factors for high-quality reservoirs still remained undefined.Here,the Yingcheng tight gas reservoirs of Longfengshan area are used as an example to characterize high-quality reservoir formation mechanism and distribution rules.Based on the thin section,SEM,X-ray diffraction,computed tomography(CT)scanning,burial history,constant-rate mercury penetration and physical properties testing,formation mechanism and controlling factors for high-quality reservoirs were analyzed.Results show the following characteristics.First,the reservoir is dominated by chlorite and laumontite cements,and compaction is the most important factor to control reservoir physical properties.According to this,the reservoir can be divided into compacted tight sandstones,chlorite-cemented sandstones and laumontite-cemented sandstones.Second,the high-quality reservoirs are formed due to early extensive laumontite precipitation and the later dissolution of laumontite by organic acid.Meanwhile,it is found that the distribution of cementation and dissolution exhibits some regulations in sedimentary facies,and the distribution is mainly effected and controlled by the lake water and charging of fresh water.Besides,the distribution model of various types of sandstones was established.Studies over diagenesis and sedimentary facies reveal that the high-quality laumontite-cemented sandstones exist in the outside subaqueous fan-delta of the deep sag in Longfengshan area.These findings have been validated by recent exploration wells which obtained high industrial gas flow.
基金supported by the National Natural Science Foundation of China(No.52102138)Fundamental Research Program of Shanxi Province(No.202103021224080).
文摘To solve the problem of directional arrangement of small template particles,we designed a lamination technique for the preparation of dense ceramics with high texture degree based on the phase-field simulation.Referring to the experimental data,the initial microstructures of the template and matrix layers were constructed.The effect of the average length of template on the coarsening behavior of the template layer was investigated in detail.The results suggested that there was a stable stage in the growth process of template grains,which would be conducive to the densification of textured ceramics.This phenomenon has been confirmed by corresponding experiments.In addition,we demonstrated a critical thickness of matrix layer for the preparation of highly textured ceramics by using the template with various average lengths.The grain size of highly textured ceramics could be controlled by adjusting the template size and thickness of matrix layer.