Carotenoids are lipophilic isoprenoid pigments with essential roles in plants.While the cultivated allotetraploid cottons exhibit distinct mature anther coloration—yellow in Gossypium barbadense versus predominantly ...Carotenoids are lipophilic isoprenoid pigments with essential roles in plants.While the cultivated allotetraploid cottons exhibit distinct mature anther coloration—yellow in Gossypium barbadense versus predominantly white in G.hirsutum—the genetic basis of this divergence remains unclear.The purpose of this study was to identify the genetic basis of anther-color variation in cotton(Gossypium)species.We firstly identified carotenoids as the primary pigments underlying yellow-anthers coloration.Comparative transcriptomics of anthers revealed that the carotenoid biosynthesis gene GbPSY4 was expressed as a key regulator in G.barbadense.Functional validation via tissue-specific expression,subcellular localization,in vivo enzymatic assays,and virus-induced gene silencing confirmed its role in carotenoid biosynthesis and yellow pigmentation.Genome-wide association studies in a G.hirsutum population revealed GhPSY4_At,an ortholog of GbPSY4,as the causal gene of anther-color variation.We conclude that PSY4-regulated carotenoid biosynthesis governs yellow pigmentation.Furthermore,a finding that G.hirsutum accessions with yellow anthers showed greater pollen viability under high-temperature stress than those with white anthers suggests that the same pathway that governs yellow pigmentation influences heat tolerance.PSY4 is a promising target for breeding stress-tolerant cotton varieties.展开更多
The ice-phase microphysical characteristics of a stratiform cloud system over the Qilian Mountains in northwestern China on 15 September 2022 were analyzed via aircraft data.The stratiform cloud system developed under...The ice-phase microphysical characteristics of a stratiform cloud system over the Qilian Mountains in northwestern China on 15 September 2022 were analyzed via aircraft data.The stratiform cloud system developed under southwesterly flows at 500 hPa and was affected locally by topography.Synoptic features and aircraft observations revealed strengthened cloud development on the leeward slope.The ice particle habits and microphysical processes at heights of 6-8 km were investigated.The cloud system was characterized by extremely low supercooled liquid water content at temperatures between−4℃ and−17℃.The ice particle concentrations ranged predominantly from 10 to 30 L^(−1),corresponding to ice water content ranging from 0.01 to 0.05 g m^(−3).Active ice aggregation was observed at temperatures colder than−10°C.The windward side of the cloud system exhibited weaker development and two distinct cloud layers.Intense orographic uplift on the leeward slope enhanced ice particle aggregation.The clouds on the leeside presented lower ice particle concentrations but larger sizes than those on the windward side.The influence of aggregation on the ice particle size distribution was reflected in two main aspects.One aspect was the bimodal spectra at−16℃,with the first peak at 125μm and subpeak at 400-500μm;the other was the broadened size spectra at−13℃ due to significant aggregation of dendrites.展开更多
Weather forecasting is crucial for agriculture,transportation,and industry.Deep Learning(DL)has greatly improved the prediction accuracy.Among them,Graph Neural Networks(GNNs)excel at processing weather data by establ...Weather forecasting is crucial for agriculture,transportation,and industry.Deep Learning(DL)has greatly improved the prediction accuracy.Among them,Graph Neural Networks(GNNs)excel at processing weather data by establishing connections between regions.This allows them to understand complex patterns that traditional methods might miss.As a result,achieving more accurate predictions becomes possible.The paper reviews the role of GNNs in short-to medium-range weather forecasting.The methods are classified into three categories based on dataset differences.The paper also further identifies five promising research frontiers.These areas aim to boost forecasting precision and enhance computational efficiency.They offer valuable insights for future weather forecasting systems.展开更多
Cotton fiber quality is a persistent concern that determines planting benefits and the quality of finished textile products.However,the limitations of measurement instruments have hindered the accurate evaluation of s...Cotton fiber quality is a persistent concern that determines planting benefits and the quality of finished textile products.However,the limitations of measurement instruments have hindered the accurate evaluation of some important fiber characteristics such as fiber maturity,fineness,and neps,which in turn has impeded the genetic improvement and industrial utilization of cotton fiber.Here,12 single fiber quality traits were measured using Advanced Fiber Information System(AFIS)equipment among 383 accessions of upland cotton(Gossypium hirsutum L.).In addition,eight conventional fiber quality traits were assessed by the High Volume Instrument(HVI)System.Genome-wide association study(GWAS),linkage disequilibrium(LD)block genotyping and functional identification were conducted sequentially to uncover the associated elite loci and candidate genes of fiber quality traits.As a result,the previously reported pleiotropic locus FL_D11 regulating fiber length-related traits was identified in this study.More importantly,three novel pleiotropic loci(FM_A03,FF_A05,and FN_A07)regulating fiber maturity,fineness and neps,respectively,were detected based on AFIS traits.Numerous highly promising candidate genes were screened out by integrating RNA-seq and qRT-PCR analyses,including the reported GhKRP6 for fiber length,the newly identified GhMAP8 for maturity and GhDFR for fineness.The origin and evolutionary analysis of pleiotropic loci indicated that the selection pressure on FL_D11,FM_A03 and FF_A05 increased as the breeding period approached the present and the origins of FM_A03 and FF_A05 were traced back to cotton landraces.These findings reveal the genetic basis underlying fiber quality and provide insight into the genetic improvement and textile utilization of fiber in G.hirsutum.展开更多
The rotator cuff tear has emerged as a significant global health concern.However,existing therapies fail to fully restore the intricate bone-to-tendon gradients,resulting in compromised biomechanical functionalities o...The rotator cuff tear has emerged as a significant global health concern.However,existing therapies fail to fully restore the intricate bone-to-tendon gradients,resulting in compromised biomechanical functionalities of the reconstructed enthesis tissues.Herein,a tri-layered core–shell microfibrous scaffold with layer-specific growth factors(GFs)release is developed using coaxial electrohydrodynamic(EHD)printing for in situ cell recruitment and differentiation to facilitate gradient enthesis tissue repair.Stromal cell-derived factor-1(SDF-1)is loaded in the shell,while basic fibroblast GF,transforming GF-beta,and bone morphogenetic protein-2 are loaded in the core of the EHD-printed microfibrous scaffolds in a layer-specific manner.Correspondingly,the tri-layered microfibrous scaffolds have a core–shell fiber size of(25.7±5.1)μm,with a pore size sequentially increasing from(81.5±4.6)μm to(173.3±6.9)μm,and to(388.9±6.9μm)for the tenogenic,chondrogenic,and osteogenic instructive layers.A rapid release of embedded GFs is observed within the first 2 d,followed by a faster release of SDF-1 and a slightly slower release of differentiation GFs for approximately four weeks.The coaxial EHD-printed microfibrous scaffolds significantly promote stem cell recruitment and direct their differentiation toward tenocyte,chondrocyte,and osteocyte phenotypes in vitro.When implanted in vivo,the tri-layered core–shell microfibrous scaffolds rapidly restored the biomechanical functions and promoted enthesis tissue regeneration with native-like bone-to-tendon gradients.Our findings suggest that the microfibrous scaffolds with layer-specific GFs release may offer a promising clinical solution for enthesis regeneration.展开更多
To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with...To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.展开更多
Optimal plant height is crucial in modern agriculture, influencing lodging resistance and facilitating mechanized crop production. Upland cotton (Gossypium hirsutum) is the most important fiber crop globally;however, ...Optimal plant height is crucial in modern agriculture, influencing lodging resistance and facilitating mechanized crop production. Upland cotton (Gossypium hirsutum) is the most important fiber crop globally;however, the genetic basis underlying plant height remains largely unexplored. In this study, we conducted a genome-wide association study to identify a major locus controlling plant height (PH1) in upland cotton. This locus encodes gibberellin 2-oxidase 1A (GhPH1) and features a 1133-bp structural variation (PAVPH1) located approximately 16 kb upstream. The presence or absence of PAVPH1 influences the expression of GhPH1, thereby affecting plant height. Further analysis revealed that a gibberellin-regulating transcription factor (GhGARF) recognizes and binds to a specific CATTTG motif in both the GhPH1 promoter and PAVPH1. This interaction downregulates GhPH1, indicating that PAVPH1 functions as a distant upstream silencer. Intriguingly, we found that DWARF53 (D53), a key repressor of the strigolactone (SL) signaling pathway, directly interacts with GhGARF to inhibit its binding to targets. Moreover, we identified a previously unrecognized gibberellin-SL crosstalk mechanism mediated by the GhD53-GhGARF-GhPH1/PAVPH1 module, which is crucial for regulating plant height in upland cotton. These findings shed light on the genetic basis and gene interaction network underlying plant height, providing valuable insights for the development of semi-dwarf cotton varieties through precise modulation of GhPH1 expression.展开更多
Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usa...Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or not.However,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation method.In order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this paper.At first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is proposed.Then,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function model.Finally,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of GCA.The proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.展开更多
Materials with a hollow structure have drawn a lot of attentions due to their potential applications in controlled drug delivery and catalysis.When these hollow materials are integrated with upconversion nanocrystals,...Materials with a hollow structure have drawn a lot of attentions due to their potential applications in controlled drug delivery and catalysis.When these hollow materials are integrated with upconversion nanocrystals,it is possible to modulate the release of loaded drugs with ultraviolet emission and to further trace the particles by near-infrared emission.However,reports of upconversion particles with intrinsic pores are scarce.In this work,monodispersed submicrometer GdF_(3):Er,Yb hollow spheres have been synthesized via an effective one-pot hydrothermal route.These hollow spheres show an average diameter of∼260 nm,and a shell thickness of about 90 nm.The surface of the hollow spheres is composed of small nanoparticles with a size of 16 nm.By modulating the amount of chelator,a formation mechanism for the hollow spheres has been proposed.Under excitation at 980 nm,these hollow spheres exhibit unique strong upconversion emissions spanning from the UV to the NIR,indicating that these hollow spheres hold promise for encapsulating drugs with controlled release and bioimaging in the NIR tissue transparent window.展开更多
基金the National Natural Science Foundation of China(32170271,32470277)the Project of Sanya Yazhou Bay Science and Technology City(SCKJ-JYRC-2023-52)the Natural Science Foundation of Henan Province(252300421076,222300420024).
文摘Carotenoids are lipophilic isoprenoid pigments with essential roles in plants.While the cultivated allotetraploid cottons exhibit distinct mature anther coloration—yellow in Gossypium barbadense versus predominantly white in G.hirsutum—the genetic basis of this divergence remains unclear.The purpose of this study was to identify the genetic basis of anther-color variation in cotton(Gossypium)species.We firstly identified carotenoids as the primary pigments underlying yellow-anthers coloration.Comparative transcriptomics of anthers revealed that the carotenoid biosynthesis gene GbPSY4 was expressed as a key regulator in G.barbadense.Functional validation via tissue-specific expression,subcellular localization,in vivo enzymatic assays,and virus-induced gene silencing confirmed its role in carotenoid biosynthesis and yellow pigmentation.Genome-wide association studies in a G.hirsutum population revealed GhPSY4_At,an ortholog of GbPSY4,as the causal gene of anther-color variation.We conclude that PSY4-regulated carotenoid biosynthesis governs yellow pigmentation.Furthermore,a finding that G.hirsutum accessions with yellow anthers showed greater pollen viability under high-temperature stress than those with white anthers suggests that the same pathway that governs yellow pigmentation influences heat tolerance.PSY4 is a promising target for breeding stress-tolerant cotton varieties.
基金supported by the National Natural Science Foundation of China(Grant Nos.42475100 and 42405091)supported by the CMA Key Innovation Team(Grant No.CMA2022ZD10)+1 种基金the CMA Weather Modification Centre Innovation Team(Grant No.WMC2023IT02)the National Key R&D Program of China(Grant No.2019YFC1510305).
文摘The ice-phase microphysical characteristics of a stratiform cloud system over the Qilian Mountains in northwestern China on 15 September 2022 were analyzed via aircraft data.The stratiform cloud system developed under southwesterly flows at 500 hPa and was affected locally by topography.Synoptic features and aircraft observations revealed strengthened cloud development on the leeward slope.The ice particle habits and microphysical processes at heights of 6-8 km were investigated.The cloud system was characterized by extremely low supercooled liquid water content at temperatures between−4℃ and−17℃.The ice particle concentrations ranged predominantly from 10 to 30 L^(−1),corresponding to ice water content ranging from 0.01 to 0.05 g m^(−3).Active ice aggregation was observed at temperatures colder than−10°C.The windward side of the cloud system exhibited weaker development and two distinct cloud layers.Intense orographic uplift on the leeward slope enhanced ice particle aggregation.The clouds on the leeside presented lower ice particle concentrations but larger sizes than those on the windward side.The influence of aggregation on the ice particle size distribution was reflected in two main aspects.One aspect was the bimodal spectra at−16℃,with the first peak at 125μm and subpeak at 400-500μm;the other was the broadened size spectra at−13℃ due to significant aggregation of dendrites.
基金supported by Key Laboratory of Smart Earth(KF2023ZD03-05)CMA Innovative and Development Program(CXFZ.20231035)+2 种基金National Key R&D Program of China(No.2021ZD0111902)National Natural Science Foundation of China(Nos.62472014,U21B2038)the Scientific and Technological Project of China Meteorological Administration(CMAJBGS202505).
文摘Weather forecasting is crucial for agriculture,transportation,and industry.Deep Learning(DL)has greatly improved the prediction accuracy.Among them,Graph Neural Networks(GNNs)excel at processing weather data by establishing connections between regions.This allows them to understand complex patterns that traditional methods might miss.As a result,achieving more accurate predictions becomes possible.The paper reviews the role of GNNs in short-to medium-range weather forecasting.The methods are classified into three categories based on dataset differences.The paper also further identifies five promising research frontiers.These areas aim to boost forecasting precision and enhance computational efficiency.They offer valuable insights for future weather forecasting systems.
基金supported by the National Key Research and Development Program of China(2022YFD1200300)the Central Plain Scholar Program,China(234000510004)the National Supercomputing Center in Zhengzhou,China。
文摘Cotton fiber quality is a persistent concern that determines planting benefits and the quality of finished textile products.However,the limitations of measurement instruments have hindered the accurate evaluation of some important fiber characteristics such as fiber maturity,fineness,and neps,which in turn has impeded the genetic improvement and industrial utilization of cotton fiber.Here,12 single fiber quality traits were measured using Advanced Fiber Information System(AFIS)equipment among 383 accessions of upland cotton(Gossypium hirsutum L.).In addition,eight conventional fiber quality traits were assessed by the High Volume Instrument(HVI)System.Genome-wide association study(GWAS),linkage disequilibrium(LD)block genotyping and functional identification were conducted sequentially to uncover the associated elite loci and candidate genes of fiber quality traits.As a result,the previously reported pleiotropic locus FL_D11 regulating fiber length-related traits was identified in this study.More importantly,three novel pleiotropic loci(FM_A03,FF_A05,and FN_A07)regulating fiber maturity,fineness and neps,respectively,were detected based on AFIS traits.Numerous highly promising candidate genes were screened out by integrating RNA-seq and qRT-PCR analyses,including the reported GhKRP6 for fiber length,the newly identified GhMAP8 for maturity and GhDFR for fineness.The origin and evolutionary analysis of pleiotropic loci indicated that the selection pressure on FL_D11,FM_A03 and FF_A05 increased as the breeding period approached the present and the origins of FM_A03 and FF_A05 were traced back to cotton landraces.These findings reveal the genetic basis underlying fiber quality and provide insight into the genetic improvement and textile utilization of fiber in G.hirsutum.
基金financially supported by the National Key Research and Development Program of China(2018YFA0703003)National Natural Science Foundation of China(82072429,52125501,82371590)+6 种基金the Program for Innovation Team of Shaanxi Province(2023-CX-TD-17)the Key Research&Development Program of Shaanxi Province(2024SF-YBXM-355,2020SF-093,2021LLRH-08)the Natural Science Foundation of Henan Province(222300420358)the Postdoctoral Project of Shaanxi Province(2023BSHYDZZ30)the Postdoctoral Fellowship Program of CPSF(GZB20230573)the Institutional Foundation of the First Affiliated Hospital of Xi’an Jiaotong University(2019ZYTS-02)the Fundamental Research Funds for the Central Universities.
文摘The rotator cuff tear has emerged as a significant global health concern.However,existing therapies fail to fully restore the intricate bone-to-tendon gradients,resulting in compromised biomechanical functionalities of the reconstructed enthesis tissues.Herein,a tri-layered core–shell microfibrous scaffold with layer-specific growth factors(GFs)release is developed using coaxial electrohydrodynamic(EHD)printing for in situ cell recruitment and differentiation to facilitate gradient enthesis tissue repair.Stromal cell-derived factor-1(SDF-1)is loaded in the shell,while basic fibroblast GF,transforming GF-beta,and bone morphogenetic protein-2 are loaded in the core of the EHD-printed microfibrous scaffolds in a layer-specific manner.Correspondingly,the tri-layered microfibrous scaffolds have a core–shell fiber size of(25.7±5.1)μm,with a pore size sequentially increasing from(81.5±4.6)μm to(173.3±6.9)μm,and to(388.9±6.9μm)for the tenogenic,chondrogenic,and osteogenic instructive layers.A rapid release of embedded GFs is observed within the first 2 d,followed by a faster release of SDF-1 and a slightly slower release of differentiation GFs for approximately four weeks.The coaxial EHD-printed microfibrous scaffolds significantly promote stem cell recruitment and direct their differentiation toward tenocyte,chondrocyte,and osteocyte phenotypes in vitro.When implanted in vivo,the tri-layered core–shell microfibrous scaffolds rapidly restored the biomechanical functions and promoted enthesis tissue regeneration with native-like bone-to-tendon gradients.Our findings suggest that the microfibrous scaffolds with layer-specific GFs release may offer a promising clinical solution for enthesis regeneration.
基金supported by the National Key R&D Program of China(2019YFC1510305)the National Natural Science Foundation of China(Grant Nos.41705119 and 41575131)+2 种基金Baojun CHEN also acknowledges support from the CMA Key Innovation Team(CMA2022ZD10)Qiujuan FENG was supported by the General Project of Natural Science Research in Shanxi Province(20210302123358)the Key Projects of Shanxi Meteorological Bureau(SXKZDDW20217104).
文摘To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.
基金funded by The National Key Research and Development Program of China(grant nos.2021YFF1000101 to S.H.and 2022YFD1200300 to X.D.)the National Natural Science Foundation of China(grant no.32122062 to S.H.)the Agricultural Science,Technology Innovation Program of the Chinese Academy of Agricultural Sciences and Henan Provincial Department of Science and Technology research project(grant no.232102111076).
文摘Optimal plant height is crucial in modern agriculture, influencing lodging resistance and facilitating mechanized crop production. Upland cotton (Gossypium hirsutum) is the most important fiber crop globally;however, the genetic basis underlying plant height remains largely unexplored. In this study, we conducted a genome-wide association study to identify a major locus controlling plant height (PH1) in upland cotton. This locus encodes gibberellin 2-oxidase 1A (GhPH1) and features a 1133-bp structural variation (PAVPH1) located approximately 16 kb upstream. The presence or absence of PAVPH1 influences the expression of GhPH1, thereby affecting plant height. Further analysis revealed that a gibberellin-regulating transcription factor (GhGARF) recognizes and binds to a specific CATTTG motif in both the GhPH1 promoter and PAVPH1. This interaction downregulates GhPH1, indicating that PAVPH1 functions as a distant upstream silencer. Intriguingly, we found that DWARF53 (D53), a key repressor of the strigolactone (SL) signaling pathway, directly interacts with GhGARF to inhibit its binding to targets. Moreover, we identified a previously unrecognized gibberellin-SL crosstalk mechanism mediated by the GhD53-GhGARF-GhPH1/PAVPH1 module, which is crucial for regulating plant height in upland cotton. These findings shed light on the genetic basis and gene interaction network underlying plant height, providing valuable insights for the development of semi-dwarf cotton varieties through precise modulation of GhPH1 expression.
基金the Scientific Research Funding Project of Liaoning Education Department of China under Grant No.JDL2020005,No.LJKZ0485the National Key Research and Development Program of China under Grant No.2018YFA0704605.
文摘Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or not.However,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation method.In order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this paper.At first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is proposed.Then,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function model.Finally,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of GCA.The proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.
基金financially supported by National Natural Science Foundation of China(21871139 and 21975122)Natural Science Foundation of Jiangsu Province,China(BK20191360)。
文摘Materials with a hollow structure have drawn a lot of attentions due to their potential applications in controlled drug delivery and catalysis.When these hollow materials are integrated with upconversion nanocrystals,it is possible to modulate the release of loaded drugs with ultraviolet emission and to further trace the particles by near-infrared emission.However,reports of upconversion particles with intrinsic pores are scarce.In this work,monodispersed submicrometer GdF_(3):Er,Yb hollow spheres have been synthesized via an effective one-pot hydrothermal route.These hollow spheres show an average diameter of∼260 nm,and a shell thickness of about 90 nm.The surface of the hollow spheres is composed of small nanoparticles with a size of 16 nm.By modulating the amount of chelator,a formation mechanism for the hollow spheres has been proposed.Under excitation at 980 nm,these hollow spheres exhibit unique strong upconversion emissions spanning from the UV to the NIR,indicating that these hollow spheres hold promise for encapsulating drugs with controlled release and bioimaging in the NIR tissue transparent window.
