The shape parameter of the Gamma size distribution plays a key role in the evolution of the cloud droplet spectrum in the bulk parameterization schemes. However, due to the inaccurate specification of the shape parame...The shape parameter of the Gamma size distribution plays a key role in the evolution of the cloud droplet spectrum in the bulk parameterization schemes. However, due to the inaccurate specification of the shape parameter in the commonly used bulk double-moment schemes, the cloud droplet spectra cannot reasonably be described during the condensation process. Therefore, a newly-developed triple-parameter condensation scheme with the shape parameter diagnosed through the number concentration, cloud water content, and reflectivity factor of cloud droplets can be applied to improve the evolution of the cloud droplet spectrum. The simulation with the new parameterization scheme was compared to those with a high-resolution Lagrangian bin scheme, the double-moment schemes in a parcel model, and the observation in a 1.5D Eulerian model that consists of two cylinders. The new scheme with the shape parameter varying with time and space can accurately simulate the evolution of the cloud droplet spectrum. Furthermore, the volume-mean radius and cloud water content simulated with the new scheme match the Lagrangian analytical solutions well, and the errors are steady, within approximately 0.2%.展开更多
Several hundred million tons of ion-adsorption rare earth tailings exist in Ganzhou, Southern China, which is a severe environmental hazard. To reduce and reutilize the tailing, kaolinite has been separated from the t...Several hundred million tons of ion-adsorption rare earth tailings exist in Ganzhou, Southern China, which is a severe environmental hazard. To reduce and reutilize the tailing, kaolinite has been separated from the tailings by mechanical separation in laboratory scale and pilot scale. The results show that the tailing is mainly composed of fine kaolinite and coarse quart. Quartz and kaolinite can be separated by sieves, shaker, spiral chute or hydrocyclone, which has the similar results in laboratory scale and pilot scale. 30.2% of the tailings can be re-sourced and applied in ceramic industries. 41.7% of kaolinite can be obtained after sorting and iron removal by magnetic separator in pilot scale, which can be applied in ceramic industries according to the Chinese national standard (TC-3). The results give a progressive solution to re-source the tailings economically.展开更多
The ion-adsorption rare earth tailings have become a serious environmental pollution in Southern China, yet the potential of their economical value has not been fully exploited. In this work, the chemical and mineral ...The ion-adsorption rare earth tailings have become a serious environmental pollution in Southern China, yet the potential of their economical value has not been fully exploited. In this work, the chemical and mineral compositions of the ion-adsorption rare earth tailings were characterized by Mineral Liberation Analyze (MLA) and XRF. The results show that 91.98 wt% of the tailings are composed of kaolinite and quartz, latter of which was removed by the sieving method. The other minor minerals contain feldspar, biotite, muscovite, titanomagnetite and limonite. Amongst these, the iron-bearing minerals are mostly found in the titanomagnetite and limonite which can be mostly removed by using a periodic high-gradient magnetic separator with a magnetic induction of 0.6 Tesla. The Fe<sub>2</sub>O<sub>3</sub> content of the tailings changed from 2.11 wt% to 1.06 wt% after the sorting process, which met the Chinese national standard of TC-3 grade raw materials for ceramic industry applications. The Fe<sub>2</sub>O<sub>3</sub> content in kaolinite was further decreased after Na<sub>2</sub>S<sub>2</sub>O<sub>4</sub> treatment.展开更多
A honeycomb structure is widely used in sandwich structure components in aeronautics and astronautics;however,machining is required to reveal some of its features.In honeycomb structures,deficiencies,such as burrs,edg...A honeycomb structure is widely used in sandwich structure components in aeronautics and astronautics;however,machining is required to reveal some of its features.In honeycomb structures,deficiencies,such as burrs,edge subsiding,and cracking,can easily appear,owing to poor specific sti ness in the radial direction.Some e ective fixation methods based on a filling principle have been applied by researchers,including approaches based on wax,polyethylene glycol,iron powder,and(especially)ice.However,few studies have addressed the optimization of the cutting parameters.This study focused on optimizing the cutting parameters to obtain a better surface roughness(calculated as a roughness average or Ra)and surface morphology in the machining of an aluminum alloy honeycomb by an ice fixation method.A Taguchi method and an analysis of variance were used to analyze the e ects and contributions of spindle speed,cutting depth,and feed rate.The optimal cutting parameters were determined using the signal-to-noise ratio combined with the surface morphology.An F-value and P-value were calculated for the value of the Ra,according to a"smaller is better"model.Additionally,the optimum cutting parameters for machining the aluminum honeycomb by ice fixation were found at different levels.The results of this study showed that the optimal parameters were a feed rate of 50 mm/min,cutting depth of 1.2 mm,and spindle speed of 4000 r/min.Feed rate was the most significant factor for minimizing Ra and improving the surface morphology,followed by spindle speed.The cutting depth had little e ect on Ra and surface morphology.After optimization,the value of Ra could reach 0.218μm,and no surface morphology deterioration was observed in the verified experiment.Thus,this research proposes optimal parameters based on ice fixation for improving the surface quality.展开更多
Satellite networking communications in navigation satellite system and spacebased deep space exploration have the features of a long delay and high bit error rate （BER）. Through analyzing the advantages and disadvan...Satellite networking communications in navigation satellite system and spacebased deep space exploration have the features of a long delay and high bit error rate （BER）. Through analyzing the advantages and disadvantages of the Consulta tive Committee for the Space Data System （CCSDS） file delivery protocol （CFDP）, a new improved repeated sending file delivery protocol （RSFDP） based on the adaptive repeated sending is put forward to build an efficient and reliable file transmission. According to the estimation of the BER of the transmission link, RSFDP repeatedly sends the lost protocol data units （PDUs） at the stage of the retransmission to improve the success rate and reduce time of the retransmission. Theoretical analyses and results of the Opnet simulation indicate that the performance of RSFDP has significant improvement gains over CFDP in the link with a long delay and high BER. The realizing results based on the space borne filed programmable gate array （FPGA） platform show the applicability of the proposed algorithm.展开更多
An interference mitigation for acquisition method,based on both energy center and spectrum symmetry detection,has been proposed as a possible solution to the problem of signal acquisition susceptibility to continuous-...An interference mitigation for acquisition method,based on both energy center and spectrum symmetry detection,has been proposed as a possible solution to the problem of signal acquisition susceptibility to continuous-wave interference(CWI)in unified carrier telemetry,tracking,and command(TT&C)systems.With subcarrier modulation index as a priori condition,the existence of CWI is determined by comparing the energy center with the symmetric center.In the presence of interference,the interference frequency point is assumed and culled;sequentially,the spectral symmetry is used to verify whether the signal acquisition is realized.Theoretical analysis,simulations,and experimental results demonstrate that the method can realize the acquisition of the main carrier target signal with an interference-to-signal ratio of 31 dB,which represents an improvement over the existing continuous-wave interference mitigation for acquisition methods.展开更多
A Lagrangian advection scheme(LAS)for solving cloud drop diffusion growth was previously proposed(in 2020)and validated with simulations of cloud droplet spectra with a one-and-a-half dimensional(1.5D)cloud bin model ...A Lagrangian advection scheme(LAS)for solving cloud drop diffusion growth was previously proposed(in 2020)and validated with simulations of cloud droplet spectra with a one-and-a-half dimensional(1.5D)cloud bin model for a deep convection case.The simulation results were improved with the new scheme over the original Eulerian scheme.In the present study,the authors simulated rain embryo formation with the LAS for a maritime shallow cumulus cloud case from the RICO(Rain in Cumulus over the Ocean)campaign.The model used to simulate the case was the same 1.5D cloud bin model coupled with the LAS.Comparing the model simulation results with aircraft observation data,the authors conclude that both the general microphysical properties and the detailed cloud droplet spectra are well captured.The LAS is robust and reliable for the simulation of rain embryo formation.展开更多
Continuum robots,which are characterized by high length-to-diameter ratios and flexible structures,show great potential for various applications in confined and irregular environments.Due to the combination of motion ...Continuum robots,which are characterized by high length-to-diameter ratios and flexible structures,show great potential for various applications in confined and irregular environments.Due to the combination of motion modes,the existence of multiple solutions,and the presence of complex obstacle constraints,motion planning for these robots is highly challenging.To tackle the challenges of online and flexible operation for continuum robots,we propose a flexible head-following motion planning method that is suitable for scalable and bendable continuum robots.Firstly,we establish a piecewise constant curvature(PCC)kinematic model for scalable and bendable continuum robots.The article proposes an adaptive auxiliary points model and a method for updating key nodes in head-following motion to enhance the precise tracking capability for paths with different curvatures.Additionally,the article integrates the strategy for adjusting the posture of local joints of the robot into the head-following motion planning method,which is beneficial for achieving safe obstacle avoidance in local areas.The article concludes by presenting the results of multiple sets of motion simulation experiments and prototype experiments.The study demonstrates that the algorithm presented in this paper effectively navigates and adjusts posture to avoid obstacles,meeting the real-time demands of online operations.The average time for a single-step solution is 4.41×10^(-5) s,and the average tracking accuracy forcircular paths is 7.8928mm.展开更多
The development of low-cost,stable,and robust non-noble metal catalysts for water oxidation is a pivotal challenge for sustainable hydrogen production through electrocatalytic water splitting.Currently,such catalysts ...The development of low-cost,stable,and robust non-noble metal catalysts for water oxidation is a pivotal challenge for sustainable hydrogen production through electrocatalytic water splitting.Currently,such catalysts suffer from high overpotential and sluggish kinetics in oxygen evolution reactions(OERs).Herein,we report a“continuous”single-crystal honeycomb-like MXene/NiFeP_(x)–N-doped carbon(NC)heterostructure,in which ultrasmall NiFeP_(x)nanoparticles(NPs)encapsulated in the NC are tightly anchored on a layered MXene.Interestingly,this MXene/NiFeP_(x)–NC delivers outstanding OER catalytic performance,which stems from“continuous”single-crystal characteristics,abundant active sites derived from the ultrasmall NiFeP_(x)NPs,and the stable honeycomb-like heterostructure with an open structure.The experimental results are rationalized theoretically(by density functional theory(DFT)calculations),which suggests that it is the unique MXene/NiFeP_(x)–NC heterostructure that promotes the sluggish OER,thereby enabling superior durability and excellent activity with an ultralow overpotential of 240 mV at a current density of 10 mA×cm^(−2).展开更多
Because of the uncertainty and randomness of wind speed, wind power has characteristics such as nonlinearity and multiple frequencies. Accurate prediction of wind power is one effective means of improving wind power i...Because of the uncertainty and randomness of wind speed, wind power has characteristics such as nonlinearity and multiple frequencies. Accurate prediction of wind power is one effective means of improving wind power integration. Because the traditional single model cannot fully characterize the fluctuating characteristics of wind power, scholars have attempted to build other prediction models based on empirical mode decomposition(EMD) or ensemble empirical mode decomposition(EEMD) to tackle this problem. However, the prediction accuracy of these models is affected by modal aliasing and illusive components. Aimed at these defects, this paper proposes a multi-frequency combination prediction model based on variational mode decomposition(VMD). We use a back propagation neural network(BPNN),autoregressive moving average(ARMA)model, and least square support vector machine(LS-SVM) to predict high, intermediate,and low frequency components,respectively. Based on the predicted values of each component, the BPNN is applied to combine them into a final wind power prediction value.Finally,the prediction performance of the single prediction models(ARMA,BPNN and LS-SVM)and the decomposition prediction models(EMD and EEMD) are used to compare with the proposed VMD model according to the evaluation indices such as average absolute error, mean square error,and root mean square error to validate its feasibility and accuracy. The results show that the prediction accuracy of the proposed VMD model is higher.展开更多
Interval prediction of wind power,which features the upper and lower limits of wind power at a given confidence level,plays a significant role in accurate prediction and stability of the power grid integrated with win...Interval prediction of wind power,which features the upper and lower limits of wind power at a given confidence level,plays a significant role in accurate prediction and stability of the power grid integrated with wind power.However,the conventional methods of interval prediction are commonly based on a hypothetic probability distribution function,which neglects the correlations among various variables,leading to the decrease of prediction accuracy.Therefore,we improve the multi-objective interval prediction based on the conditional copula function,through which we can fully utilize the correlations among variables to improve prediction accuracy without an assumed probability distribution function.We use the multi-objective optimization method of nondominated sorting genetic algorithm-II(NSGA-II)to obtain the optimal solution set.The particular best solution is weighted by the prediction interval average width(PIAW)and prediction interval coverage probability(PICP)to pick the optimized solution in practical examples.Finally,we apply the proposed method to three wind power plants in different cities in China as examples forvalidation and obtain higher prediction accuracy compared with other methods,i.e.,relevance vector machine(RVM),artificial neural network(ANN),and particle swarm optimization kernel extreme learning machine(PSO-KELM).These results demonstrate the superiority and practicability of this method in interval prediction of wind power.展开更多
The impact of habitat fragmentation and isola-tion on the genetic diversity of populations has attracted much attention in studies of meta-population and conserva-tion biology. In this work, using the randomly amplifi...The impact of habitat fragmentation and isola-tion on the genetic diversity of populations has attracted much attention in studies of meta-population and conserva-tion biology. In this work, using the randomly amplified po-lymorphic DNA (RAPD) technique, we studied the genetic diversity of central, peripheral and peninsular populations of ratlike hamster, which were collected in five locations of the North China Plain and its surrounding areas, in 1999. The study revealed that, i ) the genetic diversity of central population of Raoyang County 】 the sub-central populations of Gu’an County and Taikang County 】 the peripheral population of Shunyi District 】 the peninsular population of Mentougou District; ii) the genetic diversities of the five populations were positively correlated to the nearest dis-tances to the peripheral line of population distribution; iii) there were significant differences of gene frequencies of some RAPD fragments among the five populations. More RAPD fragments disappeared in展开更多
During the overall processing of thin-walled parts(TWPs),the guaranteed capability of the machining process and quality is determined by fixtures.Therefore,reliable fixtures suitable for the structure and machining pr...During the overall processing of thin-walled parts(TWPs),the guaranteed capability of the machining process and quality is determined by fixtures.Therefore,reliable fixtures suitable for the structure and machining process of TWP are essential.In this review,the key role of fixtures in the manufacturing system is initially discussed.The main problems in machining and workholding due to the characteristics of TWP are then analyzed in detail.Afterward,the definition of TWP fixtures is reinterpreted from narrow and broad perspectives.Fixture functions corresponding to the issues of machining and workholding are then clearly stated.Fixture categories are classified systematically according to previous research achievements,and the operation mode,functional characteristics,and structure of each fixture are comprehensively described.The function and execution mode of TWP fixtures are then systematically summarized and analyzed,and the functions of various TWP fixtures are evaluated.Some directions for future research on TWP fixtures technology are also proposed.The main purpose of this review is to provide some reference and guidance for scholars to examine TWP fixtures.展开更多
Combination products with a wide range of clinical applications represent a unique class of medical products that are composed of more than a singular medical device or drug/biological product.The product research and...Combination products with a wide range of clinical applications represent a unique class of medical products that are composed of more than a singular medical device or drug/biological product.The product research and development,clinical translation as well as regulatory evaluation of combination products are complex and challenging.This review firstly introduced the origin,definition and designation of combination products.Key areas of systematic regulatory review on the safety and efficacy of device-led/supervised combination products were then presented.Preclinical and clinical evaluation of combination products was discussed.Lastly,the research prospect of regulatory science for combination products was described.New tools of computational modeling and simulation,novel technologies such as artificial intelligence,needs of developing new standards,evidence-based research methods,new approaches including the designation of innovative or breakthrough medical products have been developed and could be used to assess the safety,efficacy,quality and performance of combination products.Taken together,the fast development of combination products with great potentials in healthcare provides new opportunities for the advancement of regulatory review as well as regulatory science.展开更多
The fluid flow of unconsolidated sandstone reservoir can be affected by compaction and sand production which will damage the reservoir and affect oil well productivity.This study aims to measure how the two factors af...The fluid flow of unconsolidated sandstone reservoir can be affected by compaction and sand production which will damage the reservoir and affect oil well productivity.This study aims to measure how the two factors affect the fluid flow.Firstly,single-phase displacement test was applied to investigate how the permeability changed with compaction.Then two-phase displacement test assessed the influence of compaction on oil production.Finally,the characteristics of fluid flow with compaction and sand production were studied under different water content.The results demonstrate that the reduction of permeability with compaction is irreversible,which will result in lower productivity.In contrast,sand production can increase the permeability at mid and high water content,which slows down the decline of oil production.Generally,the oil well productivity is reduced because of compaction even with sand production,especially when the formation pressure drop varies from 2MPa to 4MPa.Consequently,advance water injection is necessary to keep the formation pressure and oil production during oilfield development of unconsolidated sandstone reservoir.Simultaneously,the study can provide theoretical basis and references for the similar reservoirs.展开更多
TotheEditor:Coronavirus disease2019(COVID-19)has rapidly become a great global infection and broughtabout a wide range of health consequences,including a high number of deaths due to continuous spread.
Listwise approaches are an important class of learning to rank, which utilizes automatic learning techniques to discover useful information. Most previous research on listwise approaches has focused on optimizing rank...Listwise approaches are an important class of learning to rank, which utilizes automatic learning techniques to discover useful information. Most previous research on listwise approaches has focused on optimizing ranking models using weights and has used imprecisely labeled training data; optimizing ranking models using features was largely ignored thus the continuous performance improvement of these approaches was hindered. To address the limitations of previous listwise work, we propose a quasi-KNN model to discover the ranking of features and employ rank addition rule to calculate the weight of combination. On the basis of this, we propose three listwise algorithms, FeatureRank, BL-FeatureRank, and DiffRank. The experimental results show that our proposed algorithms can be applied to a strict ordered ranking training set and gain better performance than state-of-the-art listwise algorithms.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 41275147 and 41875173)the STS Program of Inner Mongolia Meteorological Service, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences and Institute of Atmospheric Physics, Chinese Academy of Sciences (Grant No. 2021CG0047)
文摘The shape parameter of the Gamma size distribution plays a key role in the evolution of the cloud droplet spectrum in the bulk parameterization schemes. However, due to the inaccurate specification of the shape parameter in the commonly used bulk double-moment schemes, the cloud droplet spectra cannot reasonably be described during the condensation process. Therefore, a newly-developed triple-parameter condensation scheme with the shape parameter diagnosed through the number concentration, cloud water content, and reflectivity factor of cloud droplets can be applied to improve the evolution of the cloud droplet spectrum. The simulation with the new parameterization scheme was compared to those with a high-resolution Lagrangian bin scheme, the double-moment schemes in a parcel model, and the observation in a 1.5D Eulerian model that consists of two cylinders. The new scheme with the shape parameter varying with time and space can accurately simulate the evolution of the cloud droplet spectrum. Furthermore, the volume-mean radius and cloud water content simulated with the new scheme match the Lagrangian analytical solutions well, and the errors are steady, within approximately 0.2%.
文摘Several hundred million tons of ion-adsorption rare earth tailings exist in Ganzhou, Southern China, which is a severe environmental hazard. To reduce and reutilize the tailing, kaolinite has been separated from the tailings by mechanical separation in laboratory scale and pilot scale. The results show that the tailing is mainly composed of fine kaolinite and coarse quart. Quartz and kaolinite can be separated by sieves, shaker, spiral chute or hydrocyclone, which has the similar results in laboratory scale and pilot scale. 30.2% of the tailings can be re-sourced and applied in ceramic industries. 41.7% of kaolinite can be obtained after sorting and iron removal by magnetic separator in pilot scale, which can be applied in ceramic industries according to the Chinese national standard (TC-3). The results give a progressive solution to re-source the tailings economically.
文摘The ion-adsorption rare earth tailings have become a serious environmental pollution in Southern China, yet the potential of their economical value has not been fully exploited. In this work, the chemical and mineral compositions of the ion-adsorption rare earth tailings were characterized by Mineral Liberation Analyze (MLA) and XRF. The results show that 91.98 wt% of the tailings are composed of kaolinite and quartz, latter of which was removed by the sieving method. The other minor minerals contain feldspar, biotite, muscovite, titanomagnetite and limonite. Amongst these, the iron-bearing minerals are mostly found in the titanomagnetite and limonite which can be mostly removed by using a periodic high-gradient magnetic separator with a magnetic induction of 0.6 Tesla. The Fe<sub>2</sub>O<sub>3</sub> content of the tailings changed from 2.11 wt% to 1.06 wt% after the sorting process, which met the Chinese national standard of TC-3 grade raw materials for ceramic industry applications. The Fe<sub>2</sub>O<sub>3</sub> content in kaolinite was further decreased after Na<sub>2</sub>S<sub>2</sub>O<sub>4</sub> treatment.
基金Supported by National Key Research and Development Program of China(Grant No.2019YFB2005400)National Natural Science Foundation of China(Grant No.U1608251)+1 种基金Open project of State Key Laboratory of high performance complex manufacturing(Grant No.Kfkt2016-05)Changjiang Scholar Program of Chinese Ministry of Education(Grant No.T2017030).
文摘A honeycomb structure is widely used in sandwich structure components in aeronautics and astronautics;however,machining is required to reveal some of its features.In honeycomb structures,deficiencies,such as burrs,edge subsiding,and cracking,can easily appear,owing to poor specific sti ness in the radial direction.Some e ective fixation methods based on a filling principle have been applied by researchers,including approaches based on wax,polyethylene glycol,iron powder,and(especially)ice.However,few studies have addressed the optimization of the cutting parameters.This study focused on optimizing the cutting parameters to obtain a better surface roughness(calculated as a roughness average or Ra)and surface morphology in the machining of an aluminum alloy honeycomb by an ice fixation method.A Taguchi method and an analysis of variance were used to analyze the e ects and contributions of spindle speed,cutting depth,and feed rate.The optimal cutting parameters were determined using the signal-to-noise ratio combined with the surface morphology.An F-value and P-value were calculated for the value of the Ra,according to a"smaller is better"model.Additionally,the optimum cutting parameters for machining the aluminum honeycomb by ice fixation were found at different levels.The results of this study showed that the optimal parameters were a feed rate of 50 mm/min,cutting depth of 1.2 mm,and spindle speed of 4000 r/min.Feed rate was the most significant factor for minimizing Ra and improving the surface morphology,followed by spindle speed.The cutting depth had little e ect on Ra and surface morphology.After optimization,the value of Ra could reach 0.218μm,and no surface morphology deterioration was observed in the verified experiment.Thus,this research proposes optimal parameters based on ice fixation for improving the surface quality.
基金supported by the National High Technology Research and Development Program of China (863 Program) (2011AA1569)
文摘Satellite networking communications in navigation satellite system and spacebased deep space exploration have the features of a long delay and high bit error rate （BER）. Through analyzing the advantages and disadvantages of the Consulta tive Committee for the Space Data System （CCSDS） file delivery protocol （CFDP）, a new improved repeated sending file delivery protocol （RSFDP） based on the adaptive repeated sending is put forward to build an efficient and reliable file transmission. According to the estimation of the BER of the transmission link, RSFDP repeatedly sends the lost protocol data units （PDUs） at the stage of the retransmission to improve the success rate and reduce time of the retransmission. Theoretical analyses and results of the Opnet simulation indicate that the performance of RSFDP has significant improvement gains over CFDP in the link with a long delay and high BER. The realizing results based on the space borne filed programmable gate array （FPGA） platform show the applicability of the proposed algorithm.
基金Supported by the National Natural Science Foundation of China(61401026)
文摘An interference mitigation for acquisition method,based on both energy center and spectrum symmetry detection,has been proposed as a possible solution to the problem of signal acquisition susceptibility to continuous-wave interference(CWI)in unified carrier telemetry,tracking,and command(TT&C)systems.With subcarrier modulation index as a priori condition,the existence of CWI is determined by comparing the energy center with the symmetric center.In the presence of interference,the interference frequency point is assumed and culled;sequentially,the spectral symmetry is used to verify whether the signal acquisition is realized.Theoretical analysis,simulations,and experimental results demonstrate that the method can realize the acquisition of the main carrier target signal with an interference-to-signal ratio of 31 dB,which represents an improvement over the existing continuous-wave interference mitigation for acquisition methods.
基金This research was funded by the National Natural Science Foundation of China[grant number 41705119]a basic research project[grant number xxx0109-301].
文摘A Lagrangian advection scheme(LAS)for solving cloud drop diffusion growth was previously proposed(in 2020)and validated with simulations of cloud droplet spectra with a one-and-a-half dimensional(1.5D)cloud bin model for a deep convection case.The simulation results were improved with the new scheme over the original Eulerian scheme.In the present study,the authors simulated rain embryo formation with the LAS for a maritime shallow cumulus cloud case from the RICO(Rain in Cumulus over the Ocean)campaign.The model used to simulate the case was the same 1.5D cloud bin model coupled with the LAS.Comparing the model simulation results with aircraft observation data,the authors conclude that both the general microphysical properties and the detailed cloud droplet spectra are well captured.The LAS is robust and reliable for the simulation of rain embryo formation.
基金supported in part by the Fundamental Research Funds for the Central Universities,China(DUT22GF301).
文摘Continuum robots,which are characterized by high length-to-diameter ratios and flexible structures,show great potential for various applications in confined and irregular environments.Due to the combination of motion modes,the existence of multiple solutions,and the presence of complex obstacle constraints,motion planning for these robots is highly challenging.To tackle the challenges of online and flexible operation for continuum robots,we propose a flexible head-following motion planning method that is suitable for scalable and bendable continuum robots.Firstly,we establish a piecewise constant curvature(PCC)kinematic model for scalable and bendable continuum robots.The article proposes an adaptive auxiliary points model and a method for updating key nodes in head-following motion to enhance the precise tracking capability for paths with different curvatures.Additionally,the article integrates the strategy for adjusting the posture of local joints of the robot into the head-following motion planning method,which is beneficial for achieving safe obstacle avoidance in local areas.The article concludes by presenting the results of multiple sets of motion simulation experiments and prototype experiments.The study demonstrates that the algorithm presented in this paper effectively navigates and adjusts posture to avoid obstacles,meeting the real-time demands of online operations.The average time for a single-step solution is 4.41×10^(-5) s,and the average tracking accuracy forcircular paths is 7.8928mm.
基金supported by the National Natural Science Foundation of China(No.22269010)the Training Program for Academic and Technical Leaders of Major Disciplines in Jiangxi Province(No.20212BCJ23020)+1 种基金the Science and Technology Project of Jiangxi Provincial Department of Education(No.GJJ211305)Jingdezhen Science and Technology Planning Project(No.20212GYZD009-04)。
文摘The development of low-cost,stable,and robust non-noble metal catalysts for water oxidation is a pivotal challenge for sustainable hydrogen production through electrocatalytic water splitting.Currently,such catalysts suffer from high overpotential and sluggish kinetics in oxygen evolution reactions(OERs).Herein,we report a“continuous”single-crystal honeycomb-like MXene/NiFeP_(x)–N-doped carbon(NC)heterostructure,in which ultrasmall NiFeP_(x)nanoparticles(NPs)encapsulated in the NC are tightly anchored on a layered MXene.Interestingly,this MXene/NiFeP_(x)–NC delivers outstanding OER catalytic performance,which stems from“continuous”single-crystal characteristics,abundant active sites derived from the ultrasmall NiFeP_(x)NPs,and the stable honeycomb-like heterostructure with an open structure.The experimental results are rationalized theoretically(by density functional theory(DFT)calculations),which suggests that it is the unique MXene/NiFeP_(x)–NC heterostructure that promotes the sluggish OER,thereby enabling superior durability and excellent activity with an ultralow overpotential of 240 mV at a current density of 10 mA×cm^(−2).
基金supported by the National Natural Science Foundation of China (No. 51507141)the National Key Research and Development Program of China (No. 2016YFC0401409)the Shaanxi provincial education office fund (No. 17JK0547)
文摘Because of the uncertainty and randomness of wind speed, wind power has characteristics such as nonlinearity and multiple frequencies. Accurate prediction of wind power is one effective means of improving wind power integration. Because the traditional single model cannot fully characterize the fluctuating characteristics of wind power, scholars have attempted to build other prediction models based on empirical mode decomposition(EMD) or ensemble empirical mode decomposition(EEMD) to tackle this problem. However, the prediction accuracy of these models is affected by modal aliasing and illusive components. Aimed at these defects, this paper proposes a multi-frequency combination prediction model based on variational mode decomposition(VMD). We use a back propagation neural network(BPNN),autoregressive moving average(ARMA)model, and least square support vector machine(LS-SVM) to predict high, intermediate,and low frequency components,respectively. Based on the predicted values of each component, the BPNN is applied to combine them into a final wind power prediction value.Finally,the prediction performance of the single prediction models(ARMA,BPNN and LS-SVM)and the decomposition prediction models(EMD and EEMD) are used to compare with the proposed VMD model according to the evaluation indices such as average absolute error, mean square error,and root mean square error to validate its feasibility and accuracy. The results show that the prediction accuracy of the proposed VMD model is higher.
基金supported by the National Natural Science Foundation of China(No.51507141)Key research and development plan of Shaanxi Province(No.2018ZDCXL-GY-10-04)+1 种基金the National Key Research and Development Program of China(No.2016YFC0401409)the Shaanxi provincial education office fund(No.17JK0547).
文摘Interval prediction of wind power,which features the upper and lower limits of wind power at a given confidence level,plays a significant role in accurate prediction and stability of the power grid integrated with wind power.However,the conventional methods of interval prediction are commonly based on a hypothetic probability distribution function,which neglects the correlations among various variables,leading to the decrease of prediction accuracy.Therefore,we improve the multi-objective interval prediction based on the conditional copula function,through which we can fully utilize the correlations among variables to improve prediction accuracy without an assumed probability distribution function.We use the multi-objective optimization method of nondominated sorting genetic algorithm-II(NSGA-II)to obtain the optimal solution set.The particular best solution is weighted by the prediction interval average width(PIAW)and prediction interval coverage probability(PICP)to pick the optimized solution in practical examples.Finally,we apply the proposed method to three wind power plants in different cities in China as examples forvalidation and obtain higher prediction accuracy compared with other methods,i.e.,relevance vector machine(RVM),artificial neural network(ANN),and particle swarm optimization kernel extreme learning machine(PSO-KELM).These results demonstrate the superiority and practicability of this method in interval prediction of wind power.
基金This work was supported by the National NaturalScience Foundation of China (Grant No. 39730090) the Key Projects of the Chinese Academy of Sciences (Grant Nos. KSCX2-1-03 and KZ951-B1-106).
文摘The impact of habitat fragmentation and isola-tion on the genetic diversity of populations has attracted much attention in studies of meta-population and conserva-tion biology. In this work, using the randomly amplified po-lymorphic DNA (RAPD) technique, we studied the genetic diversity of central, peripheral and peninsular populations of ratlike hamster, which were collected in five locations of the North China Plain and its surrounding areas, in 1999. The study revealed that, i ) the genetic diversity of central population of Raoyang County 】 the sub-central populations of Gu’an County and Taikang County 】 the peripheral population of Shunyi District 】 the peninsular population of Mentougou District; ii) the genetic diversities of the five populations were positively correlated to the nearest dis-tances to the peripheral line of population distribution; iii) there were significant differences of gene frequencies of some RAPD fragments among the five populations. More RAPD fragments disappeared in
基金support from the National Natural Science Foundation of China(Grant Nos.U20B2033,51975093)the Natural Science Foundation of Liaoning,China(Grant No.2020-YQ-09)。
文摘During the overall processing of thin-walled parts(TWPs),the guaranteed capability of the machining process and quality is determined by fixtures.Therefore,reliable fixtures suitable for the structure and machining process of TWP are essential.In this review,the key role of fixtures in the manufacturing system is initially discussed.The main problems in machining and workholding due to the characteristics of TWP are then analyzed in detail.Afterward,the definition of TWP fixtures is reinterpreted from narrow and broad perspectives.Fixture functions corresponding to the issues of machining and workholding are then clearly stated.Fixture categories are classified systematically according to previous research achievements,and the operation mode,functional characteristics,and structure of each fixture are comprehensively described.The function and execution mode of TWP fixtures are then systematically summarized and analyzed,and the functions of various TWP fixtures are evaluated.Some directions for future research on TWP fixtures technology are also proposed.The main purpose of this review is to provide some reference and guidance for scholars to examine TWP fixtures.
基金supported by China’s Action Plan on Scientific Drug Administration(technical evaluation of drug-device combination products)National Natural Science Foundation of China(NSFC,No.32001002)+2 种基金National Key Research and Development Program of China(No.2017YFE0102600)Sichuan Major Science and Technology Project on Biotechnology and Medicine(No.2018SZDZX0018)Sichuan University Postdoctoral Interdisciplinary Innovation Startup Found.
文摘Combination products with a wide range of clinical applications represent a unique class of medical products that are composed of more than a singular medical device or drug/biological product.The product research and development,clinical translation as well as regulatory evaluation of combination products are complex and challenging.This review firstly introduced the origin,definition and designation of combination products.Key areas of systematic regulatory review on the safety and efficacy of device-led/supervised combination products were then presented.Preclinical and clinical evaluation of combination products was discussed.Lastly,the research prospect of regulatory science for combination products was described.New tools of computational modeling and simulation,novel technologies such as artificial intelligence,needs of developing new standards,evidence-based research methods,new approaches including the designation of innovative or breakthrough medical products have been developed and could be used to assess the safety,efficacy,quality and performance of combination products.Taken together,the fast development of combination products with great potentials in healthcare provides new opportunities for the advancement of regulatory review as well as regulatory science.
基金The project was supported by the China Important National Science and Technology Specific Projects(2011ZX05024-002-005)the China Important National Science and Technology Specific Projects(2016ZX05025-001-004)the National Natural Science Foundation of China(Grant No.51534006).
文摘The fluid flow of unconsolidated sandstone reservoir can be affected by compaction and sand production which will damage the reservoir and affect oil well productivity.This study aims to measure how the two factors affect the fluid flow.Firstly,single-phase displacement test was applied to investigate how the permeability changed with compaction.Then two-phase displacement test assessed the influence of compaction on oil production.Finally,the characteristics of fluid flow with compaction and sand production were studied under different water content.The results demonstrate that the reduction of permeability with compaction is irreversible,which will result in lower productivity.In contrast,sand production can increase the permeability at mid and high water content,which slows down the decline of oil production.Generally,the oil well productivity is reduced because of compaction even with sand production,especially when the formation pressure drop varies from 2MPa to 4MPa.Consequently,advance water injection is necessary to keep the formation pressure and oil production during oilfield development of unconsolidated sandstone reservoir.Simultaneously,the study can provide theoretical basis and references for the similar reservoirs.
基金This study was supported by a grant from the Opening Project of Key Laboratory of Forensic Pathology,Ministry of Public Security(No.GAFYBL201802).
文摘TotheEditor:Coronavirus disease2019(COVID-19)has rapidly become a great global infection and broughtabout a wide range of health consequences,including a high number of deaths due to continuous spread.
文摘Listwise approaches are an important class of learning to rank, which utilizes automatic learning techniques to discover useful information. Most previous research on listwise approaches has focused on optimizing ranking models using weights and has used imprecisely labeled training data; optimizing ranking models using features was largely ignored thus the continuous performance improvement of these approaches was hindered. To address the limitations of previous listwise work, we propose a quasi-KNN model to discover the ranking of features and employ rank addition rule to calculate the weight of combination. On the basis of this, we propose three listwise algorithms, FeatureRank, BL-FeatureRank, and DiffRank. The experimental results show that our proposed algorithms can be applied to a strict ordered ranking training set and gain better performance than state-of-the-art listwise algorithms.
