The droplet deposition is a key index to evaluate the quality of unmanned aerial vehicle(UAV)spraying.The detection of the droplet deposition is time-consuming and costly,therefore,it is difficult to achieve large-sca...The droplet deposition is a key index to evaluate the quality of unmanned aerial vehicle(UAV)spraying.The detection of the droplet deposition is time-consuming and costly,therefore,it is difficult to achieve large-scale and rapid acquisition in the field.To solve the above problems,a droplet deposition acquisition system(DDAS)was developed.It was composed of the multiple sensors,processing units,remote server database and Android-based software.A droplet deposition prediction model based on field experimental data was established by using a one-dimensional convolutional neural network(1D-CNN)algorithm,and the effects of different inputs on the prediction ability of the model were analyzed.The results showed that adding temperature and humidity data to the inputs can achieve higher prediction accuracy than only using UAV spraying operation parameters and wind speed data as the inputs to the model.In addition,the prediction accuracy of the 1D-CNN model was the highest when compared with other models such as back propagation neural network,multiple correlation vector machine,and multiple linear regression.The 1D-CNN model was embedded into the DDAS,and the evaluation experiments were carried out in the field.The correlation analysis was conducted between two datasets of the droplet deposition obtained by the DDAS and water sensitive paper(WSP),respectively.The R2 was 0.924,and the RMSE was 0.026μL/cm2.It is proved that the droplet deposition values obtained by the DDAS and WSP have high consistency,and the DDAS developed can provide an auxiliary solution for the intelligent evaluation of UAV spraying quality.展开更多
Measurements from geomagnetic satellites continue to underpin advances in geomagnetic field models that describe Earth's internally generated magnetic field.Here,we present a new field model,MSCM,that integrates v...Measurements from geomagnetic satellites continue to underpin advances in geomagnetic field models that describe Earth's internally generated magnetic field.Here,we present a new field model,MSCM,that integrates vector and scalar data from the Swarm,China Seismo-Electromagnetic Satellite(CSES),and Macao Science Satellite-1(MSS-1)missions.The model spans from 2014.0 to 2024.5,incorporating the core,lithospheric,and magnetospheric fields,and it shows characteristics similar to other published models based on different data.For the first time,we demonstrate that it is possible to successfully construct a geomagnetic field model that incorporates CSES vector data,albeit one in which the radial and azimuthal CSES vector components are Huber downweighted.We further show that data from the MSS-1 can be integrated within an explicitly smoothed,fully time-dependent model description.Using the MSCM,we identify new behavior of the South Atlantic Anomaly,the broad region of low magnetic field intensity over the southern Atlantic.This prominent feature appears split into a western part and an eastern part,each with its own intensity minimum.Since 2015,the principal western minimum has undergone only modest intensity decreases of 290 nT and westward motion of 20 km per year,whereas the recently formed eastern minimum has shown a 2–3 times greater intensity drop of 730 nT with no apparent east-west motion.展开更多
Substantial evidence points to the early onset of peripheral inflammation in the development of Parkinson's disease(PD),supporting the“body-first”hypothesis.However,there remains a notable absence of PD-specific...Substantial evidence points to the early onset of peripheral inflammation in the development of Parkinson's disease(PD),supporting the“body-first”hypothesis.However,there remains a notable absence of PD-specific animal models induced by inflammatory cytokines.This study introduces a novel mouse model of PD driven by the proinflammatory cytokine CXCL1,identified in our previous research.The involvement of CXCL1 in PD pathogenesis was validated using subacute and chronic MPTP-induced mouse models.Based on these findings,2-month-old C57BL/6J mice were intravenously administered CXCL1(20 ng/kg/day)for 2 weeks(5 days per week),successfully replicating motor deficits and pathological alterations in the substantia nigra observed in the chronic MPTP model.These results demonstrate the potential of CXCL1-induced inflammation as a mechanism for PD modeling.The model revealed activation of the PPAR signaling pathway in CXCL1-mediated neuronal damage by CXCL1.Linoleic acid,a PPAR-γactivator,significantly mitigated MPTPand CXCL1-induced toxicity and reduced serum CXCL1levels.In addition,the CXCL1-injected mouse model shortened the timeline for developing chronic PD mouse model to 2 weeks,offering an efficient platform for studying inflammation-driven processes in PD.The findings provide critical insights into the inflammatory mechanisms underlying PD and identify promising therapeutic targets for intervention.展开更多
By combining data from the Challenging Minisatellite Payload(CHAMP),Swarm-A,and newest Macao Science Satellite-1(MSS-1) missions,we constructed a lithospheric magnetic field model up to spherical harmonic degree N = 1...By combining data from the Challenging Minisatellite Payload(CHAMP),Swarm-A,and newest Macao Science Satellite-1(MSS-1) missions,we constructed a lithospheric magnetic field model up to spherical harmonic degree N = 100.To isolate the lithospheric magnetic field signals,we utilized the latest CHAOS-8(CHAMP,Φrsted,and SAC-C 8) model and MGFM(Multisource Geomagnetic Field Model) to remove nonlithospheric sources,including the core field,magnetospheric field,ocean tidal field,and ocean circulation field.Subsequently,orbit-by-orbit processing was applied to both scalar and vector data,such as spherical harmonic high-pass filtering,singular spectrum analysis,and line leveling,to suppress noise and residual signals along the satellite tracks.With an orbital inclination of only 41°,MSS-1 effectively captures fine-scale lithospheric magnetic field signals in mid-to low-latitude regions.Its data exhibit a root mean square error of only 0.77 nT relative to the final model,confirming the high quality and utility of lithospheric field modeling.The resulting model exhibits excellent consistency with the MF7(Magnetic Field Model 7),maintaining a high correlation up to N = 90 and still exceeding 0.65 at N = 100.These results demonstrate the reliability and value of MSS-1 data in global lithospheric magnetic field modeling.展开更多
Background:SARS-CoV-2,first identified in late 2019,has given rise to numerous variants of concern(VOCs),posing a significant threat to human health.The emer-gence of Omicron BA.1.1 towards the end of 2021 led to a pa...Background:SARS-CoV-2,first identified in late 2019,has given rise to numerous variants of concern(VOCs),posing a significant threat to human health.The emer-gence of Omicron BA.1.1 towards the end of 2021 led to a pandemic in early 2022.At present,the lethal mouse model for the study of SARS-CoV-2 needs supplementation,and the alterations in neutrophils and monocytes caused by different strains remain to be elucidated.Methods:Human ACE2 transgenic mice were inoculated with the SARS-CoV-2 proto-type and Omicron BA.1,respectively.The pathogenicity of the two strains was evalu-ated by observing clinical symptoms,viral load and pathology.Complete blood count,immunohistochemistry and flow cytometry were performed to detect the alterations of neutrophils and monocytes caused by the two strains.Results:Our findings revealed that Omicron BA.1 exhibited significantly lower vir-ulence compared to the SARS-CoV-2 prototype in the mouse model.Additionally,we observed a significant increase in the proportion of neutrophils late in infection with the SARS-CoV-2 prototype and Omicron BA.1.We found that the proportion of monocytes increased at first and then decreased.The trends in the changes in the proportions of neutrophils and monocytes induced by the two strains were similar.Conclusion:Our study provides valuable insights into the utility of mouse models for simulating the severe disease of SARS-CoV-2 prototype infection and the milder manifestation associated with Omicron BA.1.SARS-CoV-2 prototype and Omicron BA.1 resulted in similar trends in the changes in neutrophils and monocytes.展开更多
Porous liquid-conducting micro-heat exchangers have garnered considerable attention for their role in efficient heat dissipation in small electronic devices.This demand highlights the need for advanced mathematical mo...Porous liquid-conducting micro-heat exchangers have garnered considerable attention for their role in efficient heat dissipation in small electronic devices.This demand highlights the need for advanced mathematical models to optimize the selection of mixed heat exchange media and equipment design.A capillary bundle evaporation model for porous liquid-conducting media was developed based on the conjugate mass transfer evaporation rate prediction model of a single capillary tube,supplemented by mercury injection experimental data.Theoretical and experimental comparisons were conducted using 1,2-propanediol-glycerol(PG-VG)mixtures at molar ratios of 1:9,3:7,5:5,and 7:3 at 120,150,and 180℃.The Jouyban-Acree model was implemented to enhance the evaporation rate predictions.For the 7:3 PG-VG mixture at 180℃under the experimental conditions of the thermal medium,the model's error reduced from 16.75%to 10.84%post-correction.Overall,the mean relative error decreased from 11.76%to 5.98%after correction.展开更多
We propose the Dantzig selector based on the l_(1-q)(1<q≤2)minimization model for the sparse signal recovery.First,we discuss some properties of l_(1-q)minimization model and give some useful inequalities.Then,we ...We propose the Dantzig selector based on the l_(1-q)(1<q≤2)minimization model for the sparse signal recovery.First,we discuss some properties of l_(1-q)minimization model and give some useful inequalities.Then,we give a sufficient condition based on the restricted isometry property for the stable recovery of signals.The l_(1-2)minimization model of Yin-Lou-He is extended to the l_(1-q)minimization model.展开更多
基金the National Key Research and Development Program of China(2019YFE0125500).
文摘The droplet deposition is a key index to evaluate the quality of unmanned aerial vehicle(UAV)spraying.The detection of the droplet deposition is time-consuming and costly,therefore,it is difficult to achieve large-scale and rapid acquisition in the field.To solve the above problems,a droplet deposition acquisition system(DDAS)was developed.It was composed of the multiple sensors,processing units,remote server database and Android-based software.A droplet deposition prediction model based on field experimental data was established by using a one-dimensional convolutional neural network(1D-CNN)algorithm,and the effects of different inputs on the prediction ability of the model were analyzed.The results showed that adding temperature and humidity data to the inputs can achieve higher prediction accuracy than only using UAV spraying operation parameters and wind speed data as the inputs to the model.In addition,the prediction accuracy of the 1D-CNN model was the highest when compared with other models such as back propagation neural network,multiple correlation vector machine,and multiple linear regression.The 1D-CNN model was embedded into the DDAS,and the evaluation experiments were carried out in the field.The correlation analysis was conducted between two datasets of the droplet deposition obtained by the DDAS and water sensitive paper(WSP),respectively.The R2 was 0.924,and the RMSE was 0.026μL/cm2.It is proved that the droplet deposition values obtained by the DDAS and WSP have high consistency,and the DDAS developed can provide an auxiliary solution for the intelligent evaluation of UAV spraying quality.
基金supported by the National Natural Science Foundation of China(Grant No.42274003)PWL was supported by Swarm DISC(Swarm Data,Innovation,and Science Cluster)+2 种基金funded by the European Space Agency(ESAContract No.4000109587)HFR acknowledges funding from the UK Natural Environment Research Council(Grant No.NE/V010867/1)。
文摘Measurements from geomagnetic satellites continue to underpin advances in geomagnetic field models that describe Earth's internally generated magnetic field.Here,we present a new field model,MSCM,that integrates vector and scalar data from the Swarm,China Seismo-Electromagnetic Satellite(CSES),and Macao Science Satellite-1(MSS-1)missions.The model spans from 2014.0 to 2024.5,incorporating the core,lithospheric,and magnetospheric fields,and it shows characteristics similar to other published models based on different data.For the first time,we demonstrate that it is possible to successfully construct a geomagnetic field model that incorporates CSES vector data,albeit one in which the radial and azimuthal CSES vector components are Huber downweighted.We further show that data from the MSS-1 can be integrated within an explicitly smoothed,fully time-dependent model description.Using the MSCM,we identify new behavior of the South Atlantic Anomaly,the broad region of low magnetic field intensity over the southern Atlantic.This prominent feature appears split into a western part and an eastern part,each with its own intensity minimum.Since 2015,the principal western minimum has undergone only modest intensity decreases of 290 nT and westward motion of 20 km per year,whereas the recently formed eastern minimum has shown a 2–3 times greater intensity drop of 730 nT with no apparent east-west motion.
基金supported by the National Natural Science Foundation of China (32471049,32170984,32471188,32200802)Natural Science Foundation of Shandong Province (ZR2023QH110)。
文摘Substantial evidence points to the early onset of peripheral inflammation in the development of Parkinson's disease(PD),supporting the“body-first”hypothesis.However,there remains a notable absence of PD-specific animal models induced by inflammatory cytokines.This study introduces a novel mouse model of PD driven by the proinflammatory cytokine CXCL1,identified in our previous research.The involvement of CXCL1 in PD pathogenesis was validated using subacute and chronic MPTP-induced mouse models.Based on these findings,2-month-old C57BL/6J mice were intravenously administered CXCL1(20 ng/kg/day)for 2 weeks(5 days per week),successfully replicating motor deficits and pathological alterations in the substantia nigra observed in the chronic MPTP model.These results demonstrate the potential of CXCL1-induced inflammation as a mechanism for PD modeling.The model revealed activation of the PPAR signaling pathway in CXCL1-mediated neuronal damage by CXCL1.Linoleic acid,a PPAR-γactivator,significantly mitigated MPTPand CXCL1-induced toxicity and reduced serum CXCL1levels.In addition,the CXCL1-injected mouse model shortened the timeline for developing chronic PD mouse model to 2 weeks,offering an efficient platform for studying inflammation-driven processes in PD.The findings provide critical insights into the inflammatory mechanisms underlying PD and identify promising therapeutic targets for intervention.
基金the support of the National Natural Science Foundation of China (Nos. 42250103, 41974073, and 41404053)the Macao Foundation and the preresearch project of Civil Aerospace Technologies (Nos. D020308 and D020303)funded by China’s National Space Administration, and the Specialized Research Fund for State Key Laboratories。
文摘By combining data from the Challenging Minisatellite Payload(CHAMP),Swarm-A,and newest Macao Science Satellite-1(MSS-1) missions,we constructed a lithospheric magnetic field model up to spherical harmonic degree N = 100.To isolate the lithospheric magnetic field signals,we utilized the latest CHAOS-8(CHAMP,Φrsted,and SAC-C 8) model and MGFM(Multisource Geomagnetic Field Model) to remove nonlithospheric sources,including the core field,magnetospheric field,ocean tidal field,and ocean circulation field.Subsequently,orbit-by-orbit processing was applied to both scalar and vector data,such as spherical harmonic high-pass filtering,singular spectrum analysis,and line leveling,to suppress noise and residual signals along the satellite tracks.With an orbital inclination of only 41°,MSS-1 effectively captures fine-scale lithospheric magnetic field signals in mid-to low-latitude regions.Its data exhibit a root mean square error of only 0.77 nT relative to the final model,confirming the high quality and utility of lithospheric field modeling.The resulting model exhibits excellent consistency with the MF7(Magnetic Field Model 7),maintaining a high correlation up to N = 90 and still exceeding 0.65 at N = 100.These results demonstrate the reliability and value of MSS-1 data in global lithospheric magnetic field modeling.
基金supported by Beijing Natural Science Foundation(Grant No.Z210014)National Natural Science Foundation of China(Grant No.32070543)+1 种基金National Key Research and Development Project of China(Grant No.2022YFC2303404)CAMS Innovation Fund for Medical Sciences(CIFMS)(Grant No.2022-12M-CoV19-002)
文摘Background:SARS-CoV-2,first identified in late 2019,has given rise to numerous variants of concern(VOCs),posing a significant threat to human health.The emer-gence of Omicron BA.1.1 towards the end of 2021 led to a pandemic in early 2022.At present,the lethal mouse model for the study of SARS-CoV-2 needs supplementation,and the alterations in neutrophils and monocytes caused by different strains remain to be elucidated.Methods:Human ACE2 transgenic mice were inoculated with the SARS-CoV-2 proto-type and Omicron BA.1,respectively.The pathogenicity of the two strains was evalu-ated by observing clinical symptoms,viral load and pathology.Complete blood count,immunohistochemistry and flow cytometry were performed to detect the alterations of neutrophils and monocytes caused by the two strains.Results:Our findings revealed that Omicron BA.1 exhibited significantly lower vir-ulence compared to the SARS-CoV-2 prototype in the mouse model.Additionally,we observed a significant increase in the proportion of neutrophils late in infection with the SARS-CoV-2 prototype and Omicron BA.1.We found that the proportion of monocytes increased at first and then decreased.The trends in the changes in the proportions of neutrophils and monocytes induced by the two strains were similar.Conclusion:Our study provides valuable insights into the utility of mouse models for simulating the severe disease of SARS-CoV-2 prototype infection and the milder manifestation associated with Omicron BA.1.SARS-CoV-2 prototype and Omicron BA.1 resulted in similar trends in the changes in neutrophils and monocytes.
基金the funding support of National Natural Science Foundation of China(21978204)。
文摘Porous liquid-conducting micro-heat exchangers have garnered considerable attention for their role in efficient heat dissipation in small electronic devices.This demand highlights the need for advanced mathematical models to optimize the selection of mixed heat exchange media and equipment design.A capillary bundle evaporation model for porous liquid-conducting media was developed based on the conjugate mass transfer evaporation rate prediction model of a single capillary tube,supplemented by mercury injection experimental data.Theoretical and experimental comparisons were conducted using 1,2-propanediol-glycerol(PG-VG)mixtures at molar ratios of 1:9,3:7,5:5,and 7:3 at 120,150,and 180℃.The Jouyban-Acree model was implemented to enhance the evaporation rate predictions.For the 7:3 PG-VG mixture at 180℃under the experimental conditions of the thermal medium,the model's error reduced from 16.75%to 10.84%post-correction.Overall,the mean relative error decreased from 11.76%to 5.98%after correction.
基金supported by the National Natural Science Foundation of China“Variable exponential function spaces on variable anisotropic Euclidean spaces and their applications”(12261083),“Harmonic analysis on affine symmetric spaces”(12161083).
文摘We propose the Dantzig selector based on the l_(1-q)(1<q≤2)minimization model for the sparse signal recovery.First,we discuss some properties of l_(1-q)minimization model and give some useful inequalities.Then,we give a sufficient condition based on the restricted isometry property for the stable recovery of signals.The l_(1-2)minimization model of Yin-Lou-He is extended to the l_(1-q)minimization model.
