The concentration of Radon in mines varies tremendously according to the country rock, type of mineralization and area. Ventilation is also an important factor. The absence of ventilation in mines tends to allow a hig...The concentration of Radon in mines varies tremendously according to the country rock, type of mineralization and area. Ventilation is also an important factor. The absence of ventilation in mines tends to allow a higher concentration of Radon to build up. This is very dangerous for the miners work inside. In this present work, the radon gas concentration is practically measured in closed uranium prospect mine located at Gabal (G.) Gattar. CR-39 solid state nuclear track detector technique is used. It is found that the radon concentration is around 80 kBq m-3 and an effective ventilation rates should be applied if there will be further works in the future.展开更多
OSAHS(Obstructive Sleep Apnea Hypopnea Syndrome)is a respiratory disease mainly characterized by limited and repeated pauses of breathing in sleep.Currently,the optimal treatment is to apply CPAP(Continuous Positive A...OSAHS(Obstructive Sleep Apnea Hypopnea Syndrome)is a respiratory disease mainly characterized by limited and repeated pauses of breathing in sleep.Currently,the optimal treatment is to apply CPAP(Continuous Positive Airway Pressure)ventilation on the upper airway of the patient through a household respiratory machine.However,if the ventilator mask is designed improperly,it might cause the residue and repeated inhalation of CO2,which will exert an adverse impact on the therapeutic effect.Present research numerically analyzed the CO2 transportation inside a commercial ventilator mask(Mirage SoftGel,ResMed,Australia)based on the reconstructed 3D numerical model of a volunteer's face and performed the improved design of the ventilator mask in terms of the CO2 residual concentration below the nostrils.The fluid dynamic analyses showed that at the end time of expiratory,the CO2 residual concentration below the nostrils is close to 4%.To improve the therapeutic effect,we changed the position of the exhaust holes and found that by moving the exhaust holes to the bottom of the ventilator mask,the CO2 residual concentration below the nostrils would be reduced to no more than 1%.This study established a near physiological computational model and provided a new method for the individualized design of the commercial ventilator mask.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
Environmental magnetic research on beaches and shoreline processes is limited.Therefore,we carried out environmental magnetic studies on the heavy mineral-enriched,dark-reddish sands on Cedar Beach of western Lake Eri...Environmental magnetic research on beaches and shoreline processes is limited.Therefore,we carried out environmental magnetic studies on the heavy mineral-enriched,dark-reddish sands on Cedar Beach of western Lake Erie(41.68°N,82.40°W).Magnetite has been identified as the dominant magnetic mineral of these sands.This study reveals a spatial variation in concentration of magnetite particles,distribution of展开更多
A method of retrieving PM10 particles concentrations at the ground level from AOT (Aerosol Optical Thickness) measurements is presented. It uses data obtained among five years during 2003 to 2007 summers in the Lille ...A method of retrieving PM10 particles concentrations at the ground level from AOT (Aerosol Optical Thickness) measurements is presented. It uses data obtained among five years during 2003 to 2007 summers in the Lille region (northern France). As PM10 concentration strongly depends on meteorological variables, we clustered the meteorological situations provided by the MM5 meteorological model forced at the lateral boundaries by the operational NCEP model in eight classes (local weather types) for which a robust statistical relationship between AOT and PM10 was found. The meteorological situations were defined by the hourly vertical profiles of temperature and (zonal and meridian) wind components. The clustering of the weather types were obtained by a self-organizing map (SOM) followed by a hierarchical ascending classification (HAC). We were then able to retrieve the PM10 at the surface from the AERONET AOT measurements for each weather type by doing non linear regressions with dedicated SOMs. The method is general and could be extended to other regions. We analyzed the strong pollution event that occurred during August 2003 heat wave. Comparison of the results from our method with the output of the CHIMERE chemical-transport model showed the interest to tentatively combine these two pieces of information to improve particle pollution alert.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 cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and ...Arctic sea ice cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest(smallest) rate of decline found in September(March) is-0.48%/a(-0.10%/a).The summer(-0.42%/a) and autumn(-0.31%/a) seasons show faster decrease rates than those of winter(-0.12%/a) and spring(-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara(-0.60%/a) and Barents Seas(-0.54%/a), followed by the Chukchi Sea(-0.48%/a), East Siberian Sea(-0.43%/a), Laptev Sea(-0.38%/a), and Beaufort Sea(-0.36%/a). The annual SIC trend for the whole Arctic Ocean is-0.26%/a over the same period. Furthermore, the in?uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Dipole anomaly(DA), sea surface temperature(SST), surface air temperature(SAT), and surface wind(SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices(AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice(i.e., loss of the insulating layer) likely contributes to a colder sea surface(i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged in?uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas(typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land(S-FJL),and the passage between Franz Josef Land and Severnaya Zemlya(FJL-SZ).展开更多
Soil alkali-hydrolyzable nitrogen, which is sensitive to N fertilization rate, is one of the indicators of soil nitrogen supplying capacity. Two field experiments were conducted in Dongtai(120°19″ E, 32°52...Soil alkali-hydrolyzable nitrogen, which is sensitive to N fertilization rate, is one of the indicators of soil nitrogen supplying capacity. Two field experiments were conducted in Dongtai(120°19″ E, 32°52″ N), Jiangsu, China in 2009 and Dafeng(120°28″ E, 33°12″ N), Jiangsu province, China in 2010. Six nitrogen rates(0, 150, 300, 375, 450, and 600 kg ha^(-1)) were used to study the effect of N fertilization rate on soil alkali-hydrolyzable nitrogen content(SAHNC), subtending leaf nitrogen concentration(SLNC), yield, and fiber quality. In both Dongtai and Dafeng experiment station, the highest yield(1709 kg ha^(-1)), best quality(fiber length 30.6 mm, fiber strength 31.6 c N tex^(-1), micronaire 4.82), and highest N agronomic efficiency(2.03 kg kg^(-1)) were achieved at the nitrogen fertilization rate of 375 kg ha^(-1). The dynamics of SAHNC and SLNC could be simulated with a cubic and an exponential function,respectively. The changes in SAHNC were consistent with the changes in SLNC. Optimal average rate(0.276 mg day^(-1)) and duration(51.8 days) of SAHNC rapid decline were similar to the values obtained at the nitrogen rate of 375 kg ha^(-1)at which cotton showed highest fiber yield, quality, and N agronomic efficiency. Thus, the levels and strategies of nitrogen fertilization can affect SAHNC dynamics. The N fertilization rate that optimizes soil alkali-hydrolyzable nitrogen content would optimize the subtending leaf nitrogen concentration and thereby increase the yield and quality of the cotton fiber.展开更多
According to the second law of thermodynamics,spontaneous chemical processes will ultimately reach the equilibrium state with the lowest energy.However,in biological systems,there are numerous highenergy states far fr...According to the second law of thermodynamics,spontaneous chemical processes will ultimately reach the equilibrium state with the lowest energy.However,in biological systems,there are numerous highenergy states far from equilibrium.One typical example is the transmembrane ion-concentration gradient,which plays crucial roles in maintaining homeostasis,regulating cell volume,and enabling cell signaling.Transmembrane ion-concentration gradient is achieved by an active transport process that requires the input of energy and the action of pump proteins.Replicating this process with synthetic supramolecular systems is particularly challenging,requiring both the input of energy and very specific,spatiotemporal control over ion uptake and release.In nature,pump proteins,such as protein-based ion channels,have evolved highly intricate architectures to perform this function.In contrast,Aprahamian and coworkers recently developed a much simpler smallmolecule system that functions as a molecular ion pump,utilizing light energy to pump chloride ions across a hydrophobic barrier against the concentration gradient[1].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 present pagination reports both Brownian diffusion and thermophoresis aspects subject to magneto hydrodynamic Williamson fluid model.Assuming the flow is unsteady and blood is treated as Williamson fluid over a we...The present pagination reports both Brownian diffusion and thermophoresis aspects subject to magneto hydrodynamic Williamson fluid model.Assuming the flow is unsteady and blood is treated as Williamson fluid over a wedge with radiation.The governing equations are transformed into ordinary differential equations by using similarity variables.The analytical solutions of the transformed governing equations are obtained by using the RK 4th order method along with shooting technique solver.The effects of various physical parameters such as Hartmann number,local Weissenberg number,radiation parameter,unsteadiness parameter,Prandtl number,Lewis number,Brownian diffusion,thermophoresis,wedge angle parameter,moving wedge parameter,on velocity,temperature,concentration,skin friction,heat transfer rate and mass transfer rate have been discussed in detail.The velocity and temperature profile deprives for larger We and an opposite trend is observed for concentration.The radiation parameter is propositional to temperature and a counter behaviour is observed for Pr.展开更多
This study used the synthetic running correlation coefficient calculation method to calculate the running correlation coefficients between the daily sea ice concentration(SIC) and sea surface air temperature(SSAT) in ...This study used the synthetic running correlation coefficient calculation method to calculate the running correlation coefficients between the daily sea ice concentration(SIC) and sea surface air temperature(SSAT) in the Beaufort-Chukchi-East Siberian-Laptev Sea(BCEL Sea), Kara Sea and southern Chukchi Sea, with an aim to understand and measure the seasonally occurring changes in the Arctic climate system. The similarities and differences among these three regions were also discussed. There are periods in spring and autumn when the changes in SIC and SSAT are not synchronized, which is a result of the seasonally occurring variation in the climate system. These periods are referred to as transition periods. Spring transition periods can be found in all three regions, and the start and end dates of these periods have advancing trends. The multiyear average duration of the spring transition periods in the BCEL Sea, Kara Sea and southern Chukchi Sea is 74 days, 57 days and 34 days, respectively. In autumn, transition periods exist in only the southern Chukchi Sea, with a multiyear average duration of only 16 days. Moreover, in the Kara Sea, positive correlation events can be found in some years, which are caused by weather time scale processes.展开更多
The effect of varying the temperature and the concentration of ammonium nitrate solution on the stress corrosion cracking (SCC) susceptibility of mild steel is studied. An increase in the temperature causes a decrease...The effect of varying the temperature and the concentration of ammonium nitrate solution on the stress corrosion cracking (SCC) susceptibility of mild steel is studied. An increase in the temperature causes a decrease in the stress corrosion life. It appears that the susceptibility in the range 368 K to 380 K was greater than at other temperatures. Near the boiling point corrosion and stress corrosion occurs, at the boiling point, the cracking was associated with a high rate of general corrosion. Microscopic examination after stress corrosion testing in 10Wt%, 20Wt%, and 52Wt% NH4NO3 solution revealed that in all cases there was severe intergranular attack, especially at the high concentration.展开更多
To explore the impact of lateral stress concentration in interlayer rock stratum on the exploitation of protected coal seam, a field experiment was carried out in a multi-seam mining structure. Lateral stress redistri...To explore the impact of lateral stress concentration in interlayer rock stratum on the exploitation of protected coal seam, a field experiment was carried out in a multi-seam mining structure. Lateral stress redistribution and interlayer rock failure behavior were surveyed. Then an assistant numerical investigation was implemented to evolve the effect of liberated seam mining and its influence on stress reconstruction in surrounding rock mass. The cause of lateral stress concentration and its impact were discussed finally. Key findings turn out that a certain lateral stress increases in interlayer rock stratum and concentrates on its lower region. Lateral stress concentration and interlayer rock failure are interactional. The former is an inducing factor of the latter;the latter promotes the increase of concentration degree. Extent of lateral stress concentration increases to the maximum as seam distance is about 50 m. But the efficacy of liberated seam mining decreases as the seam spacing gets larger. Protected seam mining is then classified based upon the impact of lateral stress concentration, which helps to prevent the rock burst hazard and then to achieve a reliable mining in deep mines.展开更多
Peroxyacyl nitrates(PANs) are important secondary pollutants in ground-level atmosphere.Accurate prediction of atmospheric pollutant concentrations is crucial to guide effective precautions for before and during speci...Peroxyacyl nitrates(PANs) are important secondary pollutants in ground-level atmosphere.Accurate prediction of atmospheric pollutant concentrations is crucial to guide effective precautions for before and during specific pollution events. In this study, four models based on the back-propagation(BP) artificial neural network(ANN) and multiple linear regression(MLR) methods were used to predict the hourly average PAN concentrations at Peking University, Beijing, in 2014. The model inputs were atmospheric pollutant data and meteorological parameters. Model 3 using a BP-ANN based on the original variables achieved the best prediction results among the four models, with a correlation coefficient(R) of 0.7089, mean bias error of -0.0043 ppb, mean absolute error of 0.4836?ppb, root mean squared error of 0.5320?ppb, and Willmott's index of agreement of 0.8214. Based on a comparison of the performance indices of the MLR and BP-ANN models, we concluded that the BP-ANN model was able to capture the highly non-linear relationships between PAN concentration and the conventional atmospheric pollutant and meteorological parameters,providing more accurate results than the traditional MLR models did, with a markedly higher goodness of R. The selected meteorological and atmospheric pollutant parameters described a sufficient amount of PAN variation, and thus provided satisfactory prediction results. More specifically, the BP-ANN model performed very well for capturing the variation pattern when PAN concentrations were low. The findings of this study address some of the existing knowledge gaps in this research field and provide a theoretical basis for future regional air pollution control.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
Epoxy resins are widely employed in wind turbine blades,drone rotors,and automotive interiors due to their excel-lent mechani-cal proper-ties and long service life.However,their insoluble and infusible cross-linked ne...Epoxy resins are widely employed in wind turbine blades,drone rotors,and automotive interiors due to their excel-lent mechani-cal proper-ties and long service life.However,their insoluble and infusible cross-linked networks pose a significant re-cycling challenge,particularly with the impending retirement of the first generation of wind turbine blades.In this work,we reported a fully bio-based epoxy Vitrimer(FEP)incorporat-ing a dual-dynamic covalent network design and systematically investigated the influence of the 1,5,7-triazabicyclo[4.4.0]dec-5-ene(TBD)catalyst on its curing kinetics,thermal/mechan-ical properties,dynamic exchange behavior,and degradation performance in a mild alkaline solution.Compared to conventional epoxy resins,FEP exhibited superior tensile strength and elongation at break at an optimal TBD concentration(2 wt%),achieving an excellent strength-toughness balance.The presence of TBD accelerated the exchange rates of both disulfide and ester bonds,endowing FEP with notable stress relaxation at elevated tempera-tures.Moreover,FEP demonstrated complete dissolution in 1 mol/L NaOH within 6 h at 25℃.These results underscored the exceptional strength,toughness,and recyclability of FEP,positioning it as a promising,environmentally friendly matrix resin for next-generation appli-cations in the new energy sector.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
文摘The concentration of Radon in mines varies tremendously according to the country rock, type of mineralization and area. Ventilation is also an important factor. The absence of ventilation in mines tends to allow a higher concentration of Radon to build up. This is very dangerous for the miners work inside. In this present work, the radon gas concentration is practically measured in closed uranium prospect mine located at Gabal (G.) Gattar. CR-39 solid state nuclear track detector technique is used. It is found that the radon concentration is around 80 kBq m-3 and an effective ventilation rates should be applied if there will be further works in the future.
基金We acknowledge the National Natural Science Foundation of China for supporting the project via the grant number 11472062 and 11002034.
文摘OSAHS(Obstructive Sleep Apnea Hypopnea Syndrome)is a respiratory disease mainly characterized by limited and repeated pauses of breathing in sleep.Currently,the optimal treatment is to apply CPAP(Continuous Positive Airway Pressure)ventilation on the upper airway of the patient through a household respiratory machine.However,if the ventilator mask is designed improperly,it might cause the residue and repeated inhalation of CO2,which will exert an adverse impact on the therapeutic effect.Present research numerically analyzed the CO2 transportation inside a commercial ventilator mask(Mirage SoftGel,ResMed,Australia)based on the reconstructed 3D numerical model of a volunteer's face and performed the improved design of the ventilator mask in terms of the CO2 residual concentration below the nostrils.The fluid dynamic analyses showed that at the end time of expiratory,the CO2 residual concentration below the nostrils is close to 4%.To improve the therapeutic effect,we changed the position of the exhaust holes and found that by moving the exhaust holes to the bottom of the ventilator mask,the CO2 residual concentration below the nostrils would be reduced to no more than 1%.This study established a near physiological computational model and provided a new method for the individualized design of the commercial ventilator mask.
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.
文摘Environmental magnetic research on beaches and shoreline processes is limited.Therefore,we carried out environmental magnetic studies on the heavy mineral-enriched,dark-reddish sands on Cedar Beach of western Lake Erie(41.68°N,82.40°W).Magnetite has been identified as the dominant magnetic mineral of these sands.This study reveals a spatial variation in concentration of magnetite particles,distribution of
文摘A method of retrieving PM10 particles concentrations at the ground level from AOT (Aerosol Optical Thickness) measurements is presented. It uses data obtained among five years during 2003 to 2007 summers in the Lille region (northern France). As PM10 concentration strongly depends on meteorological variables, we clustered the meteorological situations provided by the MM5 meteorological model forced at the lateral boundaries by the operational NCEP model in eight classes (local weather types) for which a robust statistical relationship between AOT and PM10 was found. The meteorological situations were defined by the hourly vertical profiles of temperature and (zonal and meridian) wind components. The clustering of the weather types were obtained by a self-organizing map (SOM) followed by a hierarchical ascending classification (HAC). We were then able to retrieve the PM10 at the surface from the AERONET AOT measurements for each weather type by doing non linear regressions with dedicated SOMs. The method is general and could be extended to other regions. We analyzed the strong pollution event that occurred during August 2003 heat wave. Comparison of the results from our method with the output of the CHIMERE chemical-transport model showed the interest to tentatively combine these two pieces of information to improve particle pollution alert.
基金supported by the Youth Innovation Promotion Association of the Chinese Academy of Sciences(No.2020261)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA02010000)the Young Potential Program of the Shanghai Institute of Applied Physics,Chinese Academy of Sciences(No.SINAP-YXJH-202412)。
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 Natural Science Foundation of China(No.41406215)the NSFC-Shandong Joint Fund for Marine Science Research Centers(No.U1606401)+2 种基金the Qingdao National Laboratory for Marine Science and Technology,the Postdoctoral Science Foundation of China(No.2014M561971)the Open Funds for the Key Laboratory of Marine Geology and Environment,Institute of Oceanology,Chinese Academy of Sciences(No.MGE2013KG07)the Natural Science Foundation of Jiangsu Province of China(No.BK20140186)
文摘Arctic sea ice cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest(smallest) rate of decline found in September(March) is-0.48%/a(-0.10%/a).The summer(-0.42%/a) and autumn(-0.31%/a) seasons show faster decrease rates than those of winter(-0.12%/a) and spring(-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara(-0.60%/a) and Barents Seas(-0.54%/a), followed by the Chukchi Sea(-0.48%/a), East Siberian Sea(-0.43%/a), Laptev Sea(-0.38%/a), and Beaufort Sea(-0.36%/a). The annual SIC trend for the whole Arctic Ocean is-0.26%/a over the same period. Furthermore, the in?uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Dipole anomaly(DA), sea surface temperature(SST), surface air temperature(SAT), and surface wind(SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices(AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice(i.e., loss of the insulating layer) likely contributes to a colder sea surface(i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged in?uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas(typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land(S-FJL),and the passage between Franz Josef Land and Severnaya Zemlya(FJL-SZ).
基金funded by the National Key Technology R&D Program of China (No. 2014BAD11B02)the Special Fund for Agro-scientific Research in the Public Interest (No. 201203096)+1 种基金the National Natural Science Foundation of China (Nos. 31401327, 30971735)the China Agriculture Research System (No. CARS-18-20)
文摘Soil alkali-hydrolyzable nitrogen, which is sensitive to N fertilization rate, is one of the indicators of soil nitrogen supplying capacity. Two field experiments were conducted in Dongtai(120°19″ E, 32°52″ N), Jiangsu, China in 2009 and Dafeng(120°28″ E, 33°12″ N), Jiangsu province, China in 2010. Six nitrogen rates(0, 150, 300, 375, 450, and 600 kg ha^(-1)) were used to study the effect of N fertilization rate on soil alkali-hydrolyzable nitrogen content(SAHNC), subtending leaf nitrogen concentration(SLNC), yield, and fiber quality. In both Dongtai and Dafeng experiment station, the highest yield(1709 kg ha^(-1)), best quality(fiber length 30.6 mm, fiber strength 31.6 c N tex^(-1), micronaire 4.82), and highest N agronomic efficiency(2.03 kg kg^(-1)) were achieved at the nitrogen fertilization rate of 375 kg ha^(-1). The dynamics of SAHNC and SLNC could be simulated with a cubic and an exponential function,respectively. The changes in SAHNC were consistent with the changes in SLNC. Optimal average rate(0.276 mg day^(-1)) and duration(51.8 days) of SAHNC rapid decline were similar to the values obtained at the nitrogen rate of 375 kg ha^(-1)at which cotton showed highest fiber yield, quality, and N agronomic efficiency. Thus, the levels and strategies of nitrogen fertilization can affect SAHNC dynamics. The N fertilization rate that optimizes soil alkali-hydrolyzable nitrogen content would optimize the subtending leaf nitrogen concentration and thereby increase the yield and quality of the cotton fiber.
基金financial supports of National Natural Science Foundation of China(22171226)Natural Science Basic Research Program of Shaanxi(2022JC-06).
文摘According to the second law of thermodynamics,spontaneous chemical processes will ultimately reach the equilibrium state with the lowest energy.However,in biological systems,there are numerous highenergy states far from equilibrium.One typical example is the transmembrane ion-concentration gradient,which plays crucial roles in maintaining homeostasis,regulating cell volume,and enabling cell signaling.Transmembrane ion-concentration gradient is achieved by an active transport process that requires the input of energy and the action of pump proteins.Replicating this process with synthetic supramolecular systems is particularly challenging,requiring both the input of energy and very specific,spatiotemporal control over ion uptake and release.In nature,pump proteins,such as protein-based ion channels,have evolved highly intricate architectures to perform this function.In contrast,Aprahamian and coworkers recently developed a much simpler smallmolecule system that functions as a molecular ion pump,utilizing light energy to pump chloride ions across a hydrophobic barrier against the concentration gradient[1].
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.
文摘The present pagination reports both Brownian diffusion and thermophoresis aspects subject to magneto hydrodynamic Williamson fluid model.Assuming the flow is unsteady and blood is treated as Williamson fluid over a wedge with radiation.The governing equations are transformed into ordinary differential equations by using similarity variables.The analytical solutions of the transformed governing equations are obtained by using the RK 4th order method along with shooting technique solver.The effects of various physical parameters such as Hartmann number,local Weissenberg number,radiation parameter,unsteadiness parameter,Prandtl number,Lewis number,Brownian diffusion,thermophoresis,wedge angle parameter,moving wedge parameter,on velocity,temperature,concentration,skin friction,heat transfer rate and mass transfer rate have been discussed in detail.The velocity and temperature profile deprives for larger We and an opposite trend is observed for concentration.The radiation parameter is propositional to temperature and a counter behaviour is observed for Pr.
基金supported by the National Major Science Project of China for Global Change Research (No. 2015CB953900)the National Natural Science Foundation of China (No. 41330960)
文摘This study used the synthetic running correlation coefficient calculation method to calculate the running correlation coefficients between the daily sea ice concentration(SIC) and sea surface air temperature(SSAT) in the Beaufort-Chukchi-East Siberian-Laptev Sea(BCEL Sea), Kara Sea and southern Chukchi Sea, with an aim to understand and measure the seasonally occurring changes in the Arctic climate system. The similarities and differences among these three regions were also discussed. There are periods in spring and autumn when the changes in SIC and SSAT are not synchronized, which is a result of the seasonally occurring variation in the climate system. These periods are referred to as transition periods. Spring transition periods can be found in all three regions, and the start and end dates of these periods have advancing trends. The multiyear average duration of the spring transition periods in the BCEL Sea, Kara Sea and southern Chukchi Sea is 74 days, 57 days and 34 days, respectively. In autumn, transition periods exist in only the southern Chukchi Sea, with a multiyear average duration of only 16 days. Moreover, in the Kara Sea, positive correlation events can be found in some years, which are caused by weather time scale processes.
文摘The effect of varying the temperature and the concentration of ammonium nitrate solution on the stress corrosion cracking (SCC) susceptibility of mild steel is studied. An increase in the temperature causes a decrease in the stress corrosion life. It appears that the susceptibility in the range 368 K to 380 K was greater than at other temperatures. Near the boiling point corrosion and stress corrosion occurs, at the boiling point, the cracking was associated with a high rate of general corrosion. Microscopic examination after stress corrosion testing in 10Wt%, 20Wt%, and 52Wt% NH4NO3 solution revealed that in all cases there was severe intergranular attack, especially at the high concentration.
文摘To explore the impact of lateral stress concentration in interlayer rock stratum on the exploitation of protected coal seam, a field experiment was carried out in a multi-seam mining structure. Lateral stress redistribution and interlayer rock failure behavior were surveyed. Then an assistant numerical investigation was implemented to evolve the effect of liberated seam mining and its influence on stress reconstruction in surrounding rock mass. The cause of lateral stress concentration and its impact were discussed finally. Key findings turn out that a certain lateral stress increases in interlayer rock stratum and concentrates on its lower region. Lateral stress concentration and interlayer rock failure are interactional. The former is an inducing factor of the latter;the latter promotes the increase of concentration degree. Extent of lateral stress concentration increases to the maximum as seam distance is about 50 m. But the efficacy of liberated seam mining decreases as the seam spacing gets larger. Protected seam mining is then classified based upon the impact of lateral stress concentration, which helps to prevent the rock burst hazard and then to achieve a reliable mining in deep mines.
基金supported by the "State Key R&D Program" of China.(Nos.2017YFC0212400,2016YFC0202200)
文摘Peroxyacyl nitrates(PANs) are important secondary pollutants in ground-level atmosphere.Accurate prediction of atmospheric pollutant concentrations is crucial to guide effective precautions for before and during specific pollution events. In this study, four models based on the back-propagation(BP) artificial neural network(ANN) and multiple linear regression(MLR) methods were used to predict the hourly average PAN concentrations at Peking University, Beijing, in 2014. The model inputs were atmospheric pollutant data and meteorological parameters. Model 3 using a BP-ANN based on the original variables achieved the best prediction results among the four models, with a correlation coefficient(R) of 0.7089, mean bias error of -0.0043 ppb, mean absolute error of 0.4836?ppb, root mean squared error of 0.5320?ppb, and Willmott's index of agreement of 0.8214. Based on a comparison of the performance indices of the MLR and BP-ANN models, we concluded that the BP-ANN model was able to capture the highly non-linear relationships between PAN concentration and the conventional atmospheric pollutant and meteorological parameters,providing more accurate results than the traditional MLR models did, with a markedly higher goodness of R. The selected meteorological and atmospheric pollutant parameters described a sufficient amount of PAN variation, and thus provided satisfactory prediction results. More specifically, the BP-ANN model performed very well for capturing the variation pattern when PAN concentrations were low. The findings of this study address some of the existing knowledge gaps in this research field and provide a theoretical basis for future regional air pollution control.
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.
基金support from the National Natural Science Foundation of China(Nos.22293011,T2341001)the Major Science and Technology Project of Anhui Province(202203a06020010).
文摘Epoxy resins are widely employed in wind turbine blades,drone rotors,and automotive interiors due to their excel-lent mechani-cal proper-ties and long service life.However,their insoluble and infusible cross-linked networks pose a significant re-cycling challenge,particularly with the impending retirement of the first generation of wind turbine blades.In this work,we reported a fully bio-based epoxy Vitrimer(FEP)incorporat-ing a dual-dynamic covalent network design and systematically investigated the influence of the 1,5,7-triazabicyclo[4.4.0]dec-5-ene(TBD)catalyst on its curing kinetics,thermal/mechan-ical properties,dynamic exchange behavior,and degradation performance in a mild alkaline solution.Compared to conventional epoxy resins,FEP exhibited superior tensile strength and elongation at break at an optimal TBD concentration(2 wt%),achieving an excellent strength-toughness balance.The presence of TBD accelerated the exchange rates of both disulfide and ester bonds,endowing FEP with notable stress relaxation at elevated tempera-tures.Moreover,FEP demonstrated complete dissolution in 1 mol/L NaOH within 6 h at 25℃.These results underscored the exceptional strength,toughness,and recyclability of FEP,positioning it as a promising,environmentally friendly matrix resin for next-generation appli-cations in the new energy sector.
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.
