Precipitation plays a pivotal role in wet deposition,significantly affecting aerosol purification.The efficacy of precipitation in removing aerosols depends on its type and the characteristics of the particulates invo...Precipitation plays a pivotal role in wet deposition,significantly affecting aerosol purification.The efficacy of precipitation in removing aerosols depends on its type and the characteristics of the particulates involved.However,further research is necessary to fully understand how precipitation impacts PM_(2.5)components.This study utilized high-temporalresolution data on PM_(2.5),its components and meteorological factors to examine varying responses influenced by precipitation intensity and duration.The findings indicate that increased rainfall intensity and duration enhance PM_(2.5)and its constituents removal efficiency.Specifically,longer precipitation periods significantly improve PM_(2.5)purification,especially with drizzle and light rain.Moreover,there is a direct correlation between preprecipitation PM_(2.5)levels and its scavenging rates,with drizzle potentially exacerbating PM_(2.5)pollution under cleaner conditions(≤35μg/m^(3)).Seasonally,the efficacy of removing PM_(2.5)components varies notably in response to drizzle and light rain.In spring,higher PM_(2.5)levels after drizzlewere primarily due to increased organic carbon concentrations favored by higher relative humidity and lower pH conditions compared to other seasons,conducive to secondary organic aerosol production.Lower wind speeds and higher temperatures further contribute to water-soluble organic carbon accumulation.Daytime and nighttime precipitation exerted differing influences on PM_(2.5)components,particularly in spring where daytime drizzle and light rain significantly increased PM_(2.5)and its constituents,notably NO_(3)-,potentially associated with phase distribution changes between gas and aerosol phases in low-temperature,high-RH conditions compared to nighttime.These results propose a dualimpact mechanism of precipitation on PM_(2.5)and provide scientific basis for designing effective control strategies.展开更多
BACKGROUND Ulcerative colitis(UC)is a chronic inflammatory condition requiring continuous treatment and monitoring.There is limited pharmacokinetic data on vedolizumab during maintenance therapy and the effect of thio...BACKGROUND Ulcerative colitis(UC)is a chronic inflammatory condition requiring continuous treatment and monitoring.There is limited pharmacokinetic data on vedolizumab during maintenance therapy and the effect of thiopurines on vedolizumab trough concentrations is unknown.AIM To investigate the exposure-response relationship of vedolizumab and the impact of thiopurine withdrawal in UC patients who have achieved sustained clinical and endoscopic remission during maintenance therapy.METHODS This is a post-hoc analysis of prospective randomized clinical trial(VIEWS)involving UC patients across 8 centers in Australia from 2018 to 2022.Patients in clinical and endoscopic remission were randomized to continue or withdraw thiopurine while receiving vedolizumab.We evaluated vedolizumab serum trough concentrations,presence of anti-vedolizumab antibodies,and clinical outcomes over 48 weeks to assess exposure-response asso-ciation and impact of thiopurine withdrawal.RESULTS There were 62 UC participants with mean age of 43.4 years and 42%were females.All participants received vedolizumab as maintenance therapy with 67.7%withdrew thiopurine.Vedolizumab serum trough concentrations remained stable over 48 weeks regardless of thiopurine use,with no anti-vedolizumab antibodies detected.Pa-tients with clinical remission had higher trough concentrations at week 48.In quartile analysis,a threshold of>11.3μg/mL was associated with sustained clinical remission,showing a sensitivity of 82.4%,specificity of 60.0%,and an area of receiver operating characteristic of 0.71(95%CI:0.49-0.93).Patients discontinuing thiopurine required higher vedolizumab concentrations for achieving remission.CONCLUSION A positive exposure-response relationship between vedolizumab trough concentrations and UC outcomes suggests that monitoring drug levels may be beneficial.While thiopurine did not influence vedolizumab levels,its with-drawal may necessitate higher vedolizumab trough concentrations to maintain remission.展开更多
Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous ...Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous fluorimetry-based probes have been developed to measure CMCs[3](Fig.S1).However,CMC measurements using these probes suffer from a time-consuming and laborious procedure and large uncertainties,primarily due to their poor photo-stabilities and highly fluctuating fluorescence backgrounds.展开更多
The COVID-19 lockdown was a typical example of extreme emission reduction,providing an opportunity to study the impact of lockdown measures on air pollution.Particle number concentrations(PNC)originate from direct emi...The COVID-19 lockdown was a typical example of extreme emission reduction,providing an opportunity to study the impact of lockdown measures on air pollution.Particle number concentrations(PNC)originate from direct emissions or through new particle formation events.However,their variations during the lockdown period are under investigation.This study focuses on Luohe,a city on the southern edge of the North China Plain,analyzing the changes in PNC and its sources before,during,and after the COVID-19 lockdown.From March 25^(th)to May 31^(st),2022,real-time PNC measurements were conducted using a Scanning Mobility Particle Sizer for particle size.Results showed an 11.2%decrease in PNC during the lockdown compared to pre-lockdown and a 3.6%decrease compared to post-lockdown,indicating reduced local emissions and weakened regional transportation during the lockdown.Positive Matrix Factorization analysis identified six sources contributing to the total PNC,including photochemical nucleation,aged photochemical nucleation,gasoline vehicle emissions,diesel vehicle emissions,coal and biomass combustion,and secondary aerosols.The significant changes in source emissions indicate a substantially reduced traffic volume after the implementation of lockdown measures(2644.8#/cm^(3),2202.2#/cm^(3),2792.7#/cm^(3)).Concurrently,photochemical nucleation(310.1#/cm^(3),306.3#/cm^(3),393.1#/cm^(3))and photochemical nucleation aging(592.8#/cm^(3),744.1#/cm^(3),810.7#/cm^(3))exhibited increasing trends,while coal/biomass combustion(1656.6#/cm^(3),1586.2#/cm^(3),980.0#/cm^(3))and secondary sources(999.4#/cm^(3),791.1#/cm^(3),804.1#/cm^(3))showed decreasing trends.In summary,the contributions of traffic emissions to PNC highlight the potential for targeted traffic management strategies to improve urban air quality.展开更多
Accurately correlating the sweating rate and the concentration of biomarkers in sweat is essential in many sweat-based diagnostic applications.These two measurements are always done simultaneously in wearable sweat se...Accurately correlating the sweating rate and the concentration of biomarkers in sweat is essential in many sweat-based diagnostic applications.These two measurements are always done simultaneously in wearable sweat sensing platforms.However,concentration measurements of biomarkers are always delayed on the timeline compared with their production,whereas there is no such delay for sweating rate.Thus,a timeline mismatch exists between these two measurements.This means that the concentration vs rate correlation constructed on the basis of such measurements will deviate from the actual correlation.This study demonstrates the existence of this mismatch and explains its cause using sweat Na^(+)measurements.It also proposes an effective approach that applies a point-by-point compensation for the delay between Na+measurements and the real-time sweating rates,such that the data on the repositioned concentration vs time curve correspond to exactly the same point on the timeline as their production.A vison sensor is developed to measure the sweating rate with high accuracy at a frequency of more than 0.1 Hz.Off-body and on-body measurements of sweating rate and Na^(+)concentration are carried out,and concentration–rate correlations are constructed using both measured and repositioned concentration curves.The least squares and random forest methods are employed to fit the constructed correlations and evaluate the reliability of the proposed approach.The use of the repositioned concentration curve gives a constructed correlation that is much closer to the actual one.This study indicates the necessity to rearrange sensor-measured biomarker concentration vs time curves when correlations of concentration with sweating rate need to be constructed and proposes a practical point-by-point data repositioning strategy for doing so.The results presented here will benefit the study of sweat biomarkers with unclear correlations with sweating rate,as well as providing a basis for the development of more reliable sweat-based diagnostic methods.展开更多
PM_(2.5)constitutes a complex and diversemixture that significantly impacts the environment,human health,and climate change.However,existing observation and numerical simulation techniques have limitations,such as a l...PM_(2.5)constitutes a complex and diversemixture that significantly impacts the environment,human health,and climate change.However,existing observation and numerical simulation techniques have limitations,such as a lack of data,high acquisition costs,andmultiple uncertainties.These limitations hinder the acquisition of comprehensive information on PM_(2.5)chemical composition and effectively implement refined air pollution protection and control strategies.In this study,we developed an optimal deep learning model to acquire hourly mass concentrations of key PM_(2.5)chemical components without complex chemical analysis.The model was trained using a randomly partitioned multivariate dataset arranged in chronological order,including atmospheric state indicators,which previous studies did not consider.Our results showed that the correlation coefficients of key chemical components were no less than 0.96,and the root mean square errors ranged from 0.20 to 2.11μg/m^(3)for the entire process(training and testing combined).The model accurately captured the temporal characteristics of key chemical components,outperforming typical machine-learning models,previous studies,and global reanalysis datasets(such asModern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2)and Copernicus Atmosphere Monitoring Service ReAnalysis(CAMSRA)).We also quantified the feature importance using the random forest model,which showed that PM_(2.5),PM_(1),visibility,and temperature were the most influential variables for key chemical components.In conclusion,this study presents a practical approach to accurately obtain chemical composition information that can contribute to filling missing data,improved air pollution monitoring and source identification.This approach has the potential to enhance air pollution control strategies and promote public health and environmental sustainability.展开更多
The accumulation of^(222)Rn and^(220)Rn progeny in poorly ventilated environments poses the risk of natural radiation exposure to the public.A previous study indicated that satisfactory results in determining the^(222...The accumulation of^(222)Rn and^(220)Rn progeny in poorly ventilated environments poses the risk of natural radiation exposure to the public.A previous study indicated that satisfactory results in determining the^(222)Rn and^(220)Rn progeny concentrations by measuring the total alpha counts at five time intervals within 560 min should be expected only in the case of high progeny concentrations in air.To complete the measurement within a relatively short period and adapt it for simultaneous measurements at comparatively lower^(222)Rn and^(220)Rn progeny concentrations,a novel mathematical model was proposed based on the radioactive decay law.This model employs a nonlinear fitting method to distinguish nuclides with overlapping spectra by utilizing the alpha particle counts of non-overlapping spectra within consecutive measurement cycles to obtain the concentrations of^(222)Rn and^(220)Rn progeny in air.Several verification experiments were conducted using an alpha spectrometer.The experimental results demonstrate that the concentrations of^(222)Rn and^(220)Rn progeny calculated by the new method align more closely with the actual circumstances than those calculated by the total count method,and their relative uncertainties are all within±16%.Furthermore,the measurement time was reduced to 90 min,representing an acceleration of 84%.The improved capability of the new method in distinguishing alpha particles with similar energies emitted from ^(218)Po and^(212)Bi,both approximately 6 MeV,contributed to realizing more accurate results.The proposed method has the potential advantage of measuring relatively low concentrations of^(222)Rn and^(220)Rn progeny in air more quickly via air filtration.展开更多
To provide advanced diagnostic techniques for diagnosing the outlet temperature distribution and species concentrations of future advanced combustors,this study focuses on a dual-swirl single-dome rectangular combusto...To provide advanced diagnostic techniques for diagnosing the outlet temperature distribution and species concentrations of future advanced combustors,this study focuses on a dual-swirl single-dome rectangular combustor.Through the integration of multiple diagnostics,simultaneous measurement of outlet temperature distribution and species concentrations was achieved.The study validates the engineering applicability of these simultaneous measurements using tungsten-rhenium(W-Re)thermocouples and Coherent Anti-Stokes Raman Scattering(CARS),CARS and Tunable Diode Laser Absorption Spectroscopy(TDLAS),as well as Gas Analysis(GA)and Mass Spectrometry(MS).The results demonstrate that measurements by thermocouples and CARS exhibit good consistency and repeatability,with a relative deviation of less than 4%,fully meeting the requirements of engineering experiments.The spatial distribution reconstruction results of TDLAS can reflect the temperature distribution characteristics at the combustor outlet.Temperature comparison between TDLAS and CARS at single-point positions shows consistent results,with a relative deviation of less than 11%and 7%under both conditions,respectively.Simultaneous measurements by integrating GA and MS show high engineering applicability for the first time,meeting the requirements for measuring both inorganic species and free radicals at the combustor outlet.Under C_(1)condition,the relative deviations of four key species(Unburned Hydrocarbon(UHC),NO,O_(2),and CO_(2))remain within 2%,while that of NO_(2)is slightly higher at approximately 8%.Under C_(2)condition,the overall deviations increase for most species,with only O_(2)and CO_(2)maintaining relatively low deviations.The primary species of UHCs at the combustor outlet under both conditions are small molecular hydrocarbons(C_(3)-C_(8))and RO_(2)radicals,accounting for over 90%of total UHC.Specifically,RO_(2)species(R is C_(1)-C_(2)alkyl groups)are the predominant species,accounting for 74.3%and 82.1%of total RO_(2)under both conditions,respectively.These integrated diagnostic methods for temperature and species concentrations at the combustor outlet serve as a crucial reference for its engineering applications.展开更多
Four distinct coordination polymers(CPs)were successfully synthesized by altering solvent types and adjusting ligand concentrations,and their crystal structures were investigated.[Co(L)(FDCA)(H_(2)O)_(2)]·0.5H_(2...Four distinct coordination polymers(CPs)were successfully synthesized by altering solvent types and adjusting ligand concentrations,and their crystal structures were investigated.[Co(L)(FDCA)(H_(2)O)_(2)]·0.5H_(2)O(1)was synthesized as a 2D structure using Coas the metal source,methanol‑water(4∶6,V/V)as the solvent,and specific concentrations of 2,5‑furandicarboxylic acid(H_(2)FDCA)and 1,3,5‑triimidazole benzene(L).Adjusting to pure water and lowering the concentration of L yielded the 1D chain structure of[Co(HL)2(H_(2)O)_(2)](FDCA)_(2)·6H_(2)O(2).Using Cu(Ⅱ)as the metal source,methanol/water(9∶1,V/V)as the solvent,and specific concentrations of L and H2FDCA,the 1D chain structure of[Cu(L)(FDCA)(H_(2)O)]·2H_(2)O(3)was synthesized.Upon increasing the concentrations of L and H2FDCA,and switching the solvent to pure water,the 1D chain structure of[Cu(HL)_(2)(H_(2)O)_(2)](FDCA)_(2)·6H_(2)O(4)was obtained.This shows that changing the solvent and ligand concentrations can affect the structural changes of CPs.In addition,the solid‑state photoluminescence of CPs 1‑4 at room temperature was studied,and their morphological changes were observed via scanning electron microscopy.Density functional theory calculations revealed that the negative charge concentrates on the O and N atoms of the ligand,facilitating ligand‑metal ion coordination.CCDC:2403934,1;2403935,2;2403936,3;2403938,4.展开更多
Cemented paste backfill(CPB)is a technology that achieves safe mining by filling the goaf with waste rocks,tailings,and other materials.It is an inevitable choice to deal with the development of deep and highly diffic...Cemented paste backfill(CPB)is a technology that achieves safe mining by filling the goaf with waste rocks,tailings,and other materials.It is an inevitable choice to deal with the development of deep and highly difficult mines and meet the requirements of environmental protection and safety regulations.It promotes the development of a circular economy in mines through the development of lowgrade resources and the resource utilization of waste,and extends the service life of mines.The mass concentration of solid content(abbreviated as“concentration”)is a critical parameter for CPB.However,discrepancies often arise between the on-site measurements and the pre-designed values due to factors such as groundwater inflow and segregation within the goaf,which cannot be evaluated after the solidification of CPB.This paper innovatively provides an in-situ non-destructive approach to identify the real concentration of CPB after curing for certain days using hyperspectral imaging(HSI)technology.Initially,the spectral variation patterns under different concentration conditions were investigated through hyperspectral scanning experiments on CPB samples.The results demonstrate that as the CPB concentration increases from 61wt%to 73wt%,the overall spectral reflectance gradually increases,with two distinct absorption peaks observed at 1407 and 1917 nm.Notably,the reflectance at 1407 nm exhibited a strong linear relationship with the concentration.Subsequently,the K-nearest neighbors(KNN)and support vector machine(SVM)algorithms were employed to classify and identify different concentrations.The study revealed that,with the KNN algorithm,the highest accuracy was achieved when K(number of nearest neighbors)was 1,although this resulted in overfitting.When K=3,the model displayed the optimal balance between accuracy and stability,with an accuracy of 95.03%.In the SVM algorithm,the highest accuracy of 98.24%was attained with parameters C(regularization parameter)=200 and Gamma(kernel coefficient)=10.A comparative analysis of precision,accuracy,and recall further highlighted that the SVM provided superior stability and precision for identifying CPB concentration.Thus,HSI technology offers an effective solution for the in-situ,non-destructive monitoring of CPB concentration,presenting a promising approach for optimizing and controlling CPB characteristic parameters.展开更多
Knowing the precise relationship between fuel loading and reactivity is essential for guiding reactor criticality extrapolation and online refueling in molten salt reactors(MSRs).This study aims to explore and explain...Knowing the precise relationship between fuel loading and reactivity is essential for guiding reactor criticality extrapolation and online refueling in molten salt reactors(MSRs).This study aims to explore and explain the linear relationship between reactivity and the reciprocal of uranium concentration in thermal-spectrum MSRs.By applying neutron balance theory,we analyzed the neutron absorption cross sections of various nuclides in single-lattice models with varying fuel concentrations.Our findings reveal a simple linear correlation between reactivity and the reciprocal of uranium concentration,which can be explained from the perspective of nuclear reaction cross sections that adhere to the 1/v law in the thermal neutron spectrum.Furthermore,we identified that the neutron absorption single-group cross sections of structural materials and carrier salts exhibit an approximately linear relationship with the fission single-group cross section of ^(235) U;similarly,the reciprocal of ^(235)U’s fission cross section exhibits an approximately linear relationship with uranium concentration.This linear relationship deviates as the volume fraction of molten salt increases,due to a greater proportion of neutrons being captured in the resonance energy spectrum.However,it remains valid for molten salt volume fractions up to 25%and demonstrates broad applicability in the physical design and operation of thermal molten salt reactors.展开更多
Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiote...Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.展开更多
Arctic sea ice concentration(SIC)prediction on a subseasonal scale plays an important role in polar navigation.To reduce the high uncertainty of daily forecasts,three time series prediction models are combined with em...Arctic sea ice concentration(SIC)prediction on a subseasonal scale plays an important role in polar navigation.To reduce the high uncertainty of daily forecasts,three time series prediction models are combined with empirical orthogonal function(EOF)decomposition to forecast Arctic pentad-mean SIC,where each month is divided into six pentad-means–the first five each span five days,and the last encompasses the remaining days,which may vary in length.The models were trained on SIC data from 1989 to2018 and tested from 2019 to 2023,with lead times ranging from 1 to 12 pentad-means.Model skill was evaluated based on SIC spatial patterns,sea ice area(SIA),and the sea ice edge in September from 2019 to 2023.The moving-averaged 2-m temperature helps reduce the long short-term memory model's error in the Beaufort and Chukchi Seas.Based on the models'scores for each EOF time series,weighted ensemble prediction results were obtained.These results outperform two benchmark models across all lead times.In addition,the ensemble prediction better reproduces the seasonal cycle of the SIA,with relative errors ranging from 1.04%to 3.85%.The predicted September ice edge closely matches observations,with binary accuracy consistently above 90%.Forecast models show the lowest errors in the central Arctic,while relatively higher errors appear in the Barents and Kara Seas.展开更多
The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navi...The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.展开更多
Although multicrystalline Si photovoltaics have been extensively studied and applied in the collection of solar energy,the same systems suffer significant efficiency losses in indoor settings,where ambient light condi...Although multicrystalline Si photovoltaics have been extensively studied and applied in the collection of solar energy,the same systems suffer significant efficiency losses in indoor settings,where ambient light conditions are considerably smaller in intensity and possess greater components of non-normal incidence.Yet,indoor light-driven,stand-alone devices can offer sustainable advances in next-generation technologies such as the Internet of Things.Here,we present a non-invasive solution to aid in photovoltaic indoor light collection—radially distributed waveguide-encoded lattice(RDWEL)slim films(thickness 1.5 mm).Embedded with a monotonical radial array of cylindrical waveguides(±20°),the RDWEL demonstrates seamless light collection(FoV(fields of view)=74.5°)and imparts enhancements in JSC(short circuit current density)of 44%and 14%for indoor and outdoor lighting conditions,respectively,when coupled to a photovoltaic device and compared to an unstructured but otherwise identical slim film coating.展开更多
The practical application of lithium metal batteries(LMBs)requires electrolytes that simultaneously ensure high safety and interfacial stability.Although locally concentrated ionic liquid electrolytes(LCILEs)exhibit e...The practical application of lithium metal batteries(LMBs)requires electrolytes that simultaneously ensure high safety and interfacial stability.Although locally concentrated ionic liquid electrolytes(LCILEs)exhibit exceptional electrochemical stability and compatibility with electrode electrolyte interfaces(EEIs),two major challenges persist:(i)safety risks caused by excessive low-flash-point diluents,and(ii)insufficient understanding of how diluents modulate solvation structures.Herein,we introduce a low-diluent-content LCILE system composed of lithium bis(fluorosulfonyl)imide(LiFSI)salt,N-methyl-N-propyl-pyrrolidinium bis(fluorosulfonyl)imide(Pyr_(13)FSI)ionic liquid,and trifluoromethanesulfonate(TFS)diluent.The TFS diluent strengthens ion-ion interactions by lowering the dielectric constant of the electrolyte,resulting in the formation of a unique nanometric anion aggregates(N-AGGs)reinforced solvation structure.These large anionic clusters exhibit accelerated redox decomposition kinetics,facilitating the rapid formation of a thin,dense,and low-impedance EEI.Consequently,the Li/LiNi_(0.6)Co_(0.2)Mn_(0.2)O_(2)coin cell achieves 87.8%capacity retention over 300 cycles at 4.3 V,while a practical 1.4 Ah Li/NCM622 pouch cell retains 84.5%capacity after 80 cycles at 4.5 V.Furthermore,the electrolyte demonstrates exceptional safety,and 2 Ah Li metal pouch cells successfully pass rigorous nail penetration tests without any ignition or explosion.This work not only provides a design strategy for intrinsically safe and high-performance electrolytes but also highlights the critical role of anion cluster decomposition kinetics in shaping EEI formation.展开更多
In this paper,we propose and analyze two second-order accurate finite difference schemes for the one-dimensional heat equation with concentrated capacity on a computa-tional domain=[a,b].We first transform the target ...In this paper,we propose and analyze two second-order accurate finite difference schemes for the one-dimensional heat equation with concentrated capacity on a computa-tional domain=[a,b].We first transform the target equation into the standard heat equation on the domain excluding the singular point equipped with an inner interface matching(IIM)condition on the singular point x=ξ∈(a,b),then adopt Taylor’s ex-pansion to approximate the IIM condition at the singular point and apply second-order finite difference method to approximate the standard heat equation at the nonsingular points.This discrete procedure allows us to choose different grid sizes to partition the two sub-domains[a,ξ]and[ξ,b],which ensures that x=ξ is a grid point,and hence the pro-posed schemes can be generalized to the heat equation with more than one concentrated capacities.We prove that the two proposed schemes are uniquely solvable.And through in-depth analysis of the local truncation errors,we rigorously prove that the two schemes are second-order accurate both in temporal and spatial directions in the maximum norm without any constraint on the grid ratio.Numerical experiments are carried out to verify our theoretical conclusions.展开更多
Sweet cherries ( Prunus avium L. cv. Napoleon) were stored in controlled atmospheres (CA) of high O(2) (70% O(2) + 0% CO(2)) or high CO(2) (5% O(2) + 10% CO(2)), in modified atmosphere package (MAP, (13% - 18%) O(2) +...Sweet cherries ( Prunus avium L. cv. Napoleon) were stored in controlled atmospheres (CA) of high O(2) (70% O(2) + 0% CO(2)) or high CO(2) (5% O(2) + 10% CO(2)), in modified atmosphere package (MAP, (13% - 18%) O(2) + (2% -4%) CO(2)) and in air (control) at 1 degreesC to investigate the effects of different O(2) and CO(2) concentrations on physiological properties, quality and storability of the fruits during storage. The results indicated that compared with other treatments, CA with high O(2) concentration decreased fruit decay and ethanol content, but increased the accumulation of malondialdehyde (MDA) and stimulated browning. CA with high CO(2) concentration inhibited polyphenol oxidase (PPO) activity, reduced MDA content, maintained vitamin C content and firmness, decreased fruit decay and browning. Soluble solids contents (SSC) were not significantly affected by different atmosphere treatments. 'Napoleon' fruits stored in 5% O(2) + 10% CO(2) for as long as 80 d were of good quality, but only 40, 20 and 30 d stored in MAP, 70% O(2) + 0% CO(2) and air, re-spectively.展开更多
Shear thickening fluids （STFs） based on additives with different concentrations and molecular chain lengths were investigated. STF samples were prepared with silica and additive dispersed in polyethylene glycol （PE...Shear thickening fluids （STFs） based on additives with different concentrations and molecular chain lengths were investigated. STF samples were prepared with silica and additive dispersed in polyethylene glycol （PEG） 400, where three types of additives with different molecular chain lengths of PEG4000, PEG6000, and PEG10000 were used. For PEG10000, different concentrations, including 0, 1%, 3%, and 5%, were selected to study the influences of additive concentrations. Rheological properties of the samples were measured with a rheometer. The results show that the shear thickening effect was significantly enhanced with the increase of the concentration and the molecular chain length of additives. The mechanism of enhancement was quantitatively explained with the formation of large particles clusters.展开更多
Ceramic oxide coatings were prepared on AZ91D magnesium alloys in alkaline silicate solution using micro-arc oxidation（MAO） technique.The corrosion behavior of MAO coating on AZ91D magnesium alloys in NaCl solutions...Ceramic oxide coatings were prepared on AZ91D magnesium alloys in alkaline silicate solution using micro-arc oxidation（MAO） technique.The corrosion behavior of MAO coating on AZ91D magnesium alloys in NaCl solutions with different concentrations（0.1%,0.5%,1.0%,3.5% and 5.0% in mass fraction） was evaluated by electrochemical measurements and immersion tests.The results showed that the corrosion rate of the MAO coated AZ91D increased with increasing chloride ion concentration.The main form of corrosion failure was localized corrosion for the MAO coated AZ91D immersed in higher concentration NaCl solutions（1.0%,3.5% and 5.0%）,while it was general corrosion in dilute NaCl solutions（0.1% and 0.5%）.Two different stages of the failure process of the MAO coated AZ91D could be identified：1） occurrence of the metastable pits and 2） growth of the pits.Different equivalent circuits were also proposed based on the results of electrochemical impedance spectroscopy（EIS） for the MAO coated AZ91D immersed in different concentrations of NaCl solutions for 120 h.展开更多
基金supported by the National Natural Science Foundation of China(No.42175124)the Science and Technology Department of Sichuan Province(No.23YFS0383)the Fundamental Research Funds for the Central Universities,China(No.2023CDSN-18).
文摘Precipitation plays a pivotal role in wet deposition,significantly affecting aerosol purification.The efficacy of precipitation in removing aerosols depends on its type and the characteristics of the particulates involved.However,further research is necessary to fully understand how precipitation impacts PM_(2.5)components.This study utilized high-temporalresolution data on PM_(2.5),its components and meteorological factors to examine varying responses influenced by precipitation intensity and duration.The findings indicate that increased rainfall intensity and duration enhance PM_(2.5)and its constituents removal efficiency.Specifically,longer precipitation periods significantly improve PM_(2.5)purification,especially with drizzle and light rain.Moreover,there is a direct correlation between preprecipitation PM_(2.5)levels and its scavenging rates,with drizzle potentially exacerbating PM_(2.5)pollution under cleaner conditions(≤35μg/m^(3)).Seasonally,the efficacy of removing PM_(2.5)components varies notably in response to drizzle and light rain.In spring,higher PM_(2.5)levels after drizzlewere primarily due to increased organic carbon concentrations favored by higher relative humidity and lower pH conditions compared to other seasons,conducive to secondary organic aerosol production.Lower wind speeds and higher temperatures further contribute to water-soluble organic carbon accumulation.Daytime and nighttime precipitation exerted differing influences on PM_(2.5)components,particularly in spring where daytime drizzle and light rain significantly increased PM_(2.5)and its constituents,notably NO_(3)-,potentially associated with phase distribution changes between gas and aerosol phases in low-temperature,high-RH conditions compared to nighttime.These results propose a dualimpact mechanism of precipitation on PM_(2.5)and provide scientific basis for designing effective control strategies.
基金Supported by Takeda Australia,No.IISR-2016-101883.
文摘BACKGROUND Ulcerative colitis(UC)is a chronic inflammatory condition requiring continuous treatment and monitoring.There is limited pharmacokinetic data on vedolizumab during maintenance therapy and the effect of thiopurines on vedolizumab trough concentrations is unknown.AIM To investigate the exposure-response relationship of vedolizumab and the impact of thiopurine withdrawal in UC patients who have achieved sustained clinical and endoscopic remission during maintenance therapy.METHODS This is a post-hoc analysis of prospective randomized clinical trial(VIEWS)involving UC patients across 8 centers in Australia from 2018 to 2022.Patients in clinical and endoscopic remission were randomized to continue or withdraw thiopurine while receiving vedolizumab.We evaluated vedolizumab serum trough concentrations,presence of anti-vedolizumab antibodies,and clinical outcomes over 48 weeks to assess exposure-response asso-ciation and impact of thiopurine withdrawal.RESULTS There were 62 UC participants with mean age of 43.4 years and 42%were females.All participants received vedolizumab as maintenance therapy with 67.7%withdrew thiopurine.Vedolizumab serum trough concentrations remained stable over 48 weeks regardless of thiopurine use,with no anti-vedolizumab antibodies detected.Pa-tients with clinical remission had higher trough concentrations at week 48.In quartile analysis,a threshold of>11.3μg/mL was associated with sustained clinical remission,showing a sensitivity of 82.4%,specificity of 60.0%,and an area of receiver operating characteristic of 0.71(95%CI:0.49-0.93).Patients discontinuing thiopurine required higher vedolizumab concentrations for achieving remission.CONCLUSION A positive exposure-response relationship between vedolizumab trough concentrations and UC outcomes suggests that monitoring drug levels may be beneficial.While thiopurine did not influence vedolizumab levels,its with-drawal may necessitate higher vedolizumab trough concentrations to maintain remission.
基金supported by Shanghai Municipal Commission of Science and Technology,China(Grant No.:19XD1400300)the National Natural Science Foundation of China(Grant Nos.:821040821,82273867,and 82030107).
文摘Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous fluorimetry-based probes have been developed to measure CMCs[3](Fig.S1).However,CMC measurements using these probes suffer from a time-consuming and laborious procedure and large uncertainties,primarily due to their poor photo-stabilities and highly fluctuating fluorescence backgrounds.
基金supported by the National Research Program for Key Issues in Air Pollution Control in China(No.DQGG202137)the National Natural Science Foundation of China(No.42277429)。
文摘The COVID-19 lockdown was a typical example of extreme emission reduction,providing an opportunity to study the impact of lockdown measures on air pollution.Particle number concentrations(PNC)originate from direct emissions or through new particle formation events.However,their variations during the lockdown period are under investigation.This study focuses on Luohe,a city on the southern edge of the North China Plain,analyzing the changes in PNC and its sources before,during,and after the COVID-19 lockdown.From March 25^(th)to May 31^(st),2022,real-time PNC measurements were conducted using a Scanning Mobility Particle Sizer for particle size.Results showed an 11.2%decrease in PNC during the lockdown compared to pre-lockdown and a 3.6%decrease compared to post-lockdown,indicating reduced local emissions and weakened regional transportation during the lockdown.Positive Matrix Factorization analysis identified six sources contributing to the total PNC,including photochemical nucleation,aged photochemical nucleation,gasoline vehicle emissions,diesel vehicle emissions,coal and biomass combustion,and secondary aerosols.The significant changes in source emissions indicate a substantially reduced traffic volume after the implementation of lockdown measures(2644.8#/cm^(3),2202.2#/cm^(3),2792.7#/cm^(3)).Concurrently,photochemical nucleation(310.1#/cm^(3),306.3#/cm^(3),393.1#/cm^(3))and photochemical nucleation aging(592.8#/cm^(3),744.1#/cm^(3),810.7#/cm^(3))exhibited increasing trends,while coal/biomass combustion(1656.6#/cm^(3),1586.2#/cm^(3),980.0#/cm^(3))and secondary sources(999.4#/cm^(3),791.1#/cm^(3),804.1#/cm^(3))showed decreasing trends.In summary,the contributions of traffic emissions to PNC highlight the potential for targeted traffic management strategies to improve urban air quality.
基金support from the National Natural Science Foundation of China(Grant No.61901295)the Nanchang Microsystem Institute of Tianjin University.
文摘Accurately correlating the sweating rate and the concentration of biomarkers in sweat is essential in many sweat-based diagnostic applications.These two measurements are always done simultaneously in wearable sweat sensing platforms.However,concentration measurements of biomarkers are always delayed on the timeline compared with their production,whereas there is no such delay for sweating rate.Thus,a timeline mismatch exists between these two measurements.This means that the concentration vs rate correlation constructed on the basis of such measurements will deviate from the actual correlation.This study demonstrates the existence of this mismatch and explains its cause using sweat Na^(+)measurements.It also proposes an effective approach that applies a point-by-point compensation for the delay between Na+measurements and the real-time sweating rates,such that the data on the repositioned concentration vs time curve correspond to exactly the same point on the timeline as their production.A vison sensor is developed to measure the sweating rate with high accuracy at a frequency of more than 0.1 Hz.Off-body and on-body measurements of sweating rate and Na^(+)concentration are carried out,and concentration–rate correlations are constructed using both measured and repositioned concentration curves.The least squares and random forest methods are employed to fit the constructed correlations and evaluate the reliability of the proposed approach.The use of the repositioned concentration curve gives a constructed correlation that is much closer to the actual one.This study indicates the necessity to rearrange sensor-measured biomarker concentration vs time curves when correlations of concentration with sweating rate need to be constructed and proposes a practical point-by-point data repositioning strategy for doing so.The results presented here will benefit the study of sweat biomarkers with unclear correlations with sweating rate,as well as providing a basis for the development of more reliable sweat-based diagnostic methods.
基金supported by the National Key Research and Development Program for Young Scientists of China(No.2022YFC3704000)the National Natural Science Foundation of China(No.42275122)the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(EarthLab).
文摘PM_(2.5)constitutes a complex and diversemixture that significantly impacts the environment,human health,and climate change.However,existing observation and numerical simulation techniques have limitations,such as a lack of data,high acquisition costs,andmultiple uncertainties.These limitations hinder the acquisition of comprehensive information on PM_(2.5)chemical composition and effectively implement refined air pollution protection and control strategies.In this study,we developed an optimal deep learning model to acquire hourly mass concentrations of key PM_(2.5)chemical components without complex chemical analysis.The model was trained using a randomly partitioned multivariate dataset arranged in chronological order,including atmospheric state indicators,which previous studies did not consider.Our results showed that the correlation coefficients of key chemical components were no less than 0.96,and the root mean square errors ranged from 0.20 to 2.11μg/m^(3)for the entire process(training and testing combined).The model accurately captured the temporal characteristics of key chemical components,outperforming typical machine-learning models,previous studies,and global reanalysis datasets(such asModern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2)and Copernicus Atmosphere Monitoring Service ReAnalysis(CAMSRA)).We also quantified the feature importance using the random forest model,which showed that PM_(2.5),PM_(1),visibility,and temperature were the most influential variables for key chemical components.In conclusion,this study presents a practical approach to accurately obtain chemical composition information that can contribute to filling missing data,improved air pollution monitoring and source identification.This approach has the potential to enhance air pollution control strategies and promote public health and environmental sustainability.
基金supported by the National Natural Science Foundation of China(No.12075112)Natural Science Foundation of Hunan(No.2023JJ50121),Natural Science Foundation of Hunan Province(No.2023JJ50091)Key Projects of Hunan Provincial Department of Education(No.23A0516).
文摘The accumulation of^(222)Rn and^(220)Rn progeny in poorly ventilated environments poses the risk of natural radiation exposure to the public.A previous study indicated that satisfactory results in determining the^(222)Rn and^(220)Rn progeny concentrations by measuring the total alpha counts at five time intervals within 560 min should be expected only in the case of high progeny concentrations in air.To complete the measurement within a relatively short period and adapt it for simultaneous measurements at comparatively lower^(222)Rn and^(220)Rn progeny concentrations,a novel mathematical model was proposed based on the radioactive decay law.This model employs a nonlinear fitting method to distinguish nuclides with overlapping spectra by utilizing the alpha particle counts of non-overlapping spectra within consecutive measurement cycles to obtain the concentrations of^(222)Rn and^(220)Rn progeny in air.Several verification experiments were conducted using an alpha spectrometer.The experimental results demonstrate that the concentrations of^(222)Rn and^(220)Rn progeny calculated by the new method align more closely with the actual circumstances than those calculated by the total count method,and their relative uncertainties are all within±16%.Furthermore,the measurement time was reduced to 90 min,representing an acceleration of 84%.The improved capability of the new method in distinguishing alpha particles with similar energies emitted from ^(218)Po and^(212)Bi,both approximately 6 MeV,contributed to realizing more accurate results.The proposed method has the potential advantage of measuring relatively low concentrations of^(222)Rn and^(220)Rn progeny in air more quickly via air filtration.
基金support of the National Major Science and Technology Projects of China(No.J2019-V-0005-0096)the National Key Research and Development Program of China(No.2020YFA0405700).
文摘To provide advanced diagnostic techniques for diagnosing the outlet temperature distribution and species concentrations of future advanced combustors,this study focuses on a dual-swirl single-dome rectangular combustor.Through the integration of multiple diagnostics,simultaneous measurement of outlet temperature distribution and species concentrations was achieved.The study validates the engineering applicability of these simultaneous measurements using tungsten-rhenium(W-Re)thermocouples and Coherent Anti-Stokes Raman Scattering(CARS),CARS and Tunable Diode Laser Absorption Spectroscopy(TDLAS),as well as Gas Analysis(GA)and Mass Spectrometry(MS).The results demonstrate that measurements by thermocouples and CARS exhibit good consistency and repeatability,with a relative deviation of less than 4%,fully meeting the requirements of engineering experiments.The spatial distribution reconstruction results of TDLAS can reflect the temperature distribution characteristics at the combustor outlet.Temperature comparison between TDLAS and CARS at single-point positions shows consistent results,with a relative deviation of less than 11%and 7%under both conditions,respectively.Simultaneous measurements by integrating GA and MS show high engineering applicability for the first time,meeting the requirements for measuring both inorganic species and free radicals at the combustor outlet.Under C_(1)condition,the relative deviations of four key species(Unburned Hydrocarbon(UHC),NO,O_(2),and CO_(2))remain within 2%,while that of NO_(2)is slightly higher at approximately 8%.Under C_(2)condition,the overall deviations increase for most species,with only O_(2)and CO_(2)maintaining relatively low deviations.The primary species of UHCs at the combustor outlet under both conditions are small molecular hydrocarbons(C_(3)-C_(8))and RO_(2)radicals,accounting for over 90%of total UHC.Specifically,RO_(2)species(R is C_(1)-C_(2)alkyl groups)are the predominant species,accounting for 74.3%and 82.1%of total RO_(2)under both conditions,respectively.These integrated diagnostic methods for temperature and species concentrations at the combustor outlet serve as a crucial reference for its engineering applications.
文摘Four distinct coordination polymers(CPs)were successfully synthesized by altering solvent types and adjusting ligand concentrations,and their crystal structures were investigated.[Co(L)(FDCA)(H_(2)O)_(2)]·0.5H_(2)O(1)was synthesized as a 2D structure using Coas the metal source,methanol‑water(4∶6,V/V)as the solvent,and specific concentrations of 2,5‑furandicarboxylic acid(H_(2)FDCA)and 1,3,5‑triimidazole benzene(L).Adjusting to pure water and lowering the concentration of L yielded the 1D chain structure of[Co(HL)2(H_(2)O)_(2)](FDCA)_(2)·6H_(2)O(2).Using Cu(Ⅱ)as the metal source,methanol/water(9∶1,V/V)as the solvent,and specific concentrations of L and H2FDCA,the 1D chain structure of[Cu(L)(FDCA)(H_(2)O)]·2H_(2)O(3)was synthesized.Upon increasing the concentrations of L and H2FDCA,and switching the solvent to pure water,the 1D chain structure of[Cu(HL)_(2)(H_(2)O)_(2)](FDCA)_(2)·6H_(2)O(4)was obtained.This shows that changing the solvent and ligand concentrations can affect the structural changes of CPs.In addition,the solid‑state photoluminescence of CPs 1‑4 at room temperature was studied,and their morphological changes were observed via scanning electron microscopy.Density functional theory calculations revealed that the negative charge concentrates on the O and N atoms of the ligand,facilitating ligand‑metal ion coordination.CCDC:2403934,1;2403935,2;2403936,3;2403938,4.
基金funded by the National Natural Science Foundation of China(Nos.52474165 and 52522404)。
文摘Cemented paste backfill(CPB)is a technology that achieves safe mining by filling the goaf with waste rocks,tailings,and other materials.It is an inevitable choice to deal with the development of deep and highly difficult mines and meet the requirements of environmental protection and safety regulations.It promotes the development of a circular economy in mines through the development of lowgrade resources and the resource utilization of waste,and extends the service life of mines.The mass concentration of solid content(abbreviated as“concentration”)is a critical parameter for CPB.However,discrepancies often arise between the on-site measurements and the pre-designed values due to factors such as groundwater inflow and segregation within the goaf,which cannot be evaluated after the solidification of CPB.This paper innovatively provides an in-situ non-destructive approach to identify the real concentration of CPB after curing for certain days using hyperspectral imaging(HSI)technology.Initially,the spectral variation patterns under different concentration conditions were investigated through hyperspectral scanning experiments on CPB samples.The results demonstrate that as the CPB concentration increases from 61wt%to 73wt%,the overall spectral reflectance gradually increases,with two distinct absorption peaks observed at 1407 and 1917 nm.Notably,the reflectance at 1407 nm exhibited a strong linear relationship with the concentration.Subsequently,the K-nearest neighbors(KNN)and support vector machine(SVM)algorithms were employed to classify and identify different concentrations.The study revealed that,with the KNN algorithm,the highest accuracy was achieved when K(number of nearest neighbors)was 1,although this resulted in overfitting.When K=3,the model displayed the optimal balance between accuracy and stability,with an accuracy of 95.03%.In the SVM algorithm,the highest accuracy of 98.24%was attained with parameters C(regularization parameter)=200 and Gamma(kernel coefficient)=10.A comparative analysis of precision,accuracy,and recall further highlighted that the SVM provided superior stability and precision for identifying CPB concentration.Thus,HSI technology offers an effective solution for the in-situ,non-destructive monitoring of CPB concentration,presenting a promising approach for optimizing and controlling CPB characteristic parameters.
文摘Knowing the precise relationship between fuel loading and reactivity is essential for guiding reactor criticality extrapolation and online refueling in molten salt reactors(MSRs).This study aims to explore and explain the linear relationship between reactivity and the reciprocal of uranium concentration in thermal-spectrum MSRs.By applying neutron balance theory,we analyzed the neutron absorption cross sections of various nuclides in single-lattice models with varying fuel concentrations.Our findings reveal a simple linear correlation between reactivity and the reciprocal of uranium concentration,which can be explained from the perspective of nuclear reaction cross sections that adhere to the 1/v law in the thermal neutron spectrum.Furthermore,we identified that the neutron absorption single-group cross sections of structural materials and carrier salts exhibit an approximately linear relationship with the fission single-group cross section of ^(235) U;similarly,the reciprocal of ^(235)U’s fission cross section exhibits an approximately linear relationship with uranium concentration.This linear relationship deviates as the volume fraction of molten salt increases,due to a greater proportion of neutrons being captured in the resonance energy spectrum.However,it remains valid for molten salt volume fractions up to 25%and demonstrates broad applicability in the physical design and operation of thermal molten salt reactors.
基金supported by the National Key Research and Development Program of China[grant number 2022YFE0106800]an Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 311024001]+3 种基金a project supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number SML2023SP209]a Research Council of Norway funded project(MAPARC)[grant number 328943]a Nansen Center´s basic institutional funding[grant number 342624]the high-performance computing support from the School of Atmospheric Science at Sun Yat-sen University。
文摘Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.
基金supported by the National Key Research and Development Program(No.2023YFC2809101)the Laoshan Laboratory Technology Innovation Project(No.LSKJ202202301)。
文摘Arctic sea ice concentration(SIC)prediction on a subseasonal scale plays an important role in polar navigation.To reduce the high uncertainty of daily forecasts,three time series prediction models are combined with empirical orthogonal function(EOF)decomposition to forecast Arctic pentad-mean SIC,where each month is divided into six pentad-means–the first five each span five days,and the last encompasses the remaining days,which may vary in length.The models were trained on SIC data from 1989 to2018 and tested from 2019 to 2023,with lead times ranging from 1 to 12 pentad-means.Model skill was evaluated based on SIC spatial patterns,sea ice area(SIA),and the sea ice edge in September from 2019 to 2023.The moving-averaged 2-m temperature helps reduce the long short-term memory model's error in the Beaufort and Chukchi Seas.Based on the models'scores for each EOF time series,weighted ensemble prediction results were obtained.These results outperform two benchmark models across all lead times.In addition,the ensemble prediction better reproduces the seasonal cycle of the SIA,with relative errors ranging from 1.04%to 3.85%.The predicted September ice edge closely matches observations,with binary accuracy consistently above 90%.Forecast models show the lowest errors in the central Arctic,while relatively higher errors appear in the Barents and Kara Seas.
基金supported by the National Natural Science Foundation of China(No.41971339)the SDUST Research Fund(No.2019TDJH103)。
文摘The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.
基金supported by the European Research Council(ERC)under the European Union's Horizon 2020 Research and Innovation Programme(Grant Agreement No.818762)the Engineering and Physical Sciences Research Council(Grant No.EP/V048953/1)and the Isaac Newton Trust(grant 22.39(m))。
文摘Although multicrystalline Si photovoltaics have been extensively studied and applied in the collection of solar energy,the same systems suffer significant efficiency losses in indoor settings,where ambient light conditions are considerably smaller in intensity and possess greater components of non-normal incidence.Yet,indoor light-driven,stand-alone devices can offer sustainable advances in next-generation technologies such as the Internet of Things.Here,we present a non-invasive solution to aid in photovoltaic indoor light collection—radially distributed waveguide-encoded lattice(RDWEL)slim films(thickness 1.5 mm).Embedded with a monotonical radial array of cylindrical waveguides(±20°),the RDWEL demonstrates seamless light collection(FoV(fields of view)=74.5°)and imparts enhancements in JSC(short circuit current density)of 44%and 14%for indoor and outdoor lighting conditions,respectively,when coupled to a photovoltaic device and compared to an unstructured but otherwise identical slim film coating.
基金supported by the National Key R&D Program of China(Grant No.2022YFE0207300)the National Natural Science Foundation of China(Grant Nos.22179142 and 22075314)+1 种基金Jiangsu Provincial Science and Technology Program(Grant No.BG 2024020).XPSWAXS and TOF-SIMS characterizations were supported by Nano-X(Vacuum Interconnected Nanotech Workstation,Suzhou Institute of Nano-Tech and Nano-Bionics,Chinese Academy of Sciences(SINANO),Suzhou 215123,China)。
文摘The practical application of lithium metal batteries(LMBs)requires electrolytes that simultaneously ensure high safety and interfacial stability.Although locally concentrated ionic liquid electrolytes(LCILEs)exhibit exceptional electrochemical stability and compatibility with electrode electrolyte interfaces(EEIs),two major challenges persist:(i)safety risks caused by excessive low-flash-point diluents,and(ii)insufficient understanding of how diluents modulate solvation structures.Herein,we introduce a low-diluent-content LCILE system composed of lithium bis(fluorosulfonyl)imide(LiFSI)salt,N-methyl-N-propyl-pyrrolidinium bis(fluorosulfonyl)imide(Pyr_(13)FSI)ionic liquid,and trifluoromethanesulfonate(TFS)diluent.The TFS diluent strengthens ion-ion interactions by lowering the dielectric constant of the electrolyte,resulting in the formation of a unique nanometric anion aggregates(N-AGGs)reinforced solvation structure.These large anionic clusters exhibit accelerated redox decomposition kinetics,facilitating the rapid formation of a thin,dense,and low-impedance EEI.Consequently,the Li/LiNi_(0.6)Co_(0.2)Mn_(0.2)O_(2)coin cell achieves 87.8%capacity retention over 300 cycles at 4.3 V,while a practical 1.4 Ah Li/NCM622 pouch cell retains 84.5%capacity after 80 cycles at 4.5 V.Furthermore,the electrolyte demonstrates exceptional safety,and 2 Ah Li metal pouch cells successfully pass rigorous nail penetration tests without any ignition or explosion.This work not only provides a design strategy for intrinsically safe and high-performance electrolytes but also highlights the critical role of anion cluster decomposition kinetics in shaping EEI formation.
基金supported by the National Natural Science Foundation of China(Grant No.11571181)by the Natural Science Foundation of Jiangsu Province(Grant No.BK20171454).
文摘In this paper,we propose and analyze two second-order accurate finite difference schemes for the one-dimensional heat equation with concentrated capacity on a computa-tional domain=[a,b].We first transform the target equation into the standard heat equation on the domain excluding the singular point equipped with an inner interface matching(IIM)condition on the singular point x=ξ∈(a,b),then adopt Taylor’s ex-pansion to approximate the IIM condition at the singular point and apply second-order finite difference method to approximate the standard heat equation at the nonsingular points.This discrete procedure allows us to choose different grid sizes to partition the two sub-domains[a,ξ]and[ξ,b],which ensures that x=ξ is a grid point,and hence the pro-posed schemes can be generalized to the heat equation with more than one concentrated capacities.We prove that the two proposed schemes are uniquely solvable.And through in-depth analysis of the local truncation errors,we rigorously prove that the two schemes are second-order accurate both in temporal and spatial directions in the maximum norm without any constraint on the grid ratio.Numerical experiments are carried out to verify our theoretical conclusions.
文摘Sweet cherries ( Prunus avium L. cv. Napoleon) were stored in controlled atmospheres (CA) of high O(2) (70% O(2) + 0% CO(2)) or high CO(2) (5% O(2) + 10% CO(2)), in modified atmosphere package (MAP, (13% - 18%) O(2) + (2% -4%) CO(2)) and in air (control) at 1 degreesC to investigate the effects of different O(2) and CO(2) concentrations on physiological properties, quality and storability of the fruits during storage. The results indicated that compared with other treatments, CA with high O(2) concentration decreased fruit decay and ethanol content, but increased the accumulation of malondialdehyde (MDA) and stimulated browning. CA with high CO(2) concentration inhibited polyphenol oxidase (PPO) activity, reduced MDA content, maintained vitamin C content and firmness, decreased fruit decay and browning. Soluble solids contents (SSC) were not significantly affected by different atmosphere treatments. 'Napoleon' fruits stored in 5% O(2) + 10% CO(2) for as long as 80 d were of good quality, but only 40, 20 and 30 d stored in MAP, 70% O(2) + 0% CO(2) and air, re-spectively.
文摘Shear thickening fluids （STFs） based on additives with different concentrations and molecular chain lengths were investigated. STF samples were prepared with silica and additive dispersed in polyethylene glycol （PEG） 400, where three types of additives with different molecular chain lengths of PEG4000, PEG6000, and PEG10000 were used. For PEG10000, different concentrations, including 0, 1%, 3%, and 5%, were selected to study the influences of additive concentrations. Rheological properties of the samples were measured with a rheometer. The results show that the shear thickening effect was significantly enhanced with the increase of the concentration and the molecular chain length of additives. The mechanism of enhancement was quantitatively explained with the formation of large particles clusters.
基金Project (2007CB613700) supported by the National Basic Research Program of ChinaProject supported by Research Program of Excellent Scholars Studying Abroad of Ministry of Human Resources and Social Security,China
文摘Ceramic oxide coatings were prepared on AZ91D magnesium alloys in alkaline silicate solution using micro-arc oxidation（MAO） technique.The corrosion behavior of MAO coating on AZ91D magnesium alloys in NaCl solutions with different concentrations（0.1%,0.5%,1.0%,3.5% and 5.0% in mass fraction） was evaluated by electrochemical measurements and immersion tests.The results showed that the corrosion rate of the MAO coated AZ91D increased with increasing chloride ion concentration.The main form of corrosion failure was localized corrosion for the MAO coated AZ91D immersed in higher concentration NaCl solutions（1.0%,3.5% and 5.0%）,while it was general corrosion in dilute NaCl solutions（0.1% and 0.5%）.Two different stages of the failure process of the MAO coated AZ91D could be identified：1） occurrence of the metastable pits and 2） growth of the pits.Different equivalent circuits were also proposed based on the results of electrochemical impedance spectroscopy（EIS） for the MAO coated AZ91D immersed in different concentrations of NaCl solutions for 120 h.
