WITHDRAWAL:Zhang,J.J.,Guo,Y.Q.,Qin,Z.Y.,Wei,C.T.,Hu,Q.H.,Vandeginste,V.,Miao,H.Y.,Yao,P.,and Zhang,P.F.,“Predicting Irreducible Water Saturation of Unconventional Reservoirs by Using NMR T2 Spectra:Methods of Morphol...WITHDRAWAL:Zhang,J.J.,Guo,Y.Q.,Qin,Z.Y.,Wei,C.T.,Hu,Q.H.,Vandeginste,V.,Miao,H.Y.,Yao,P.,and Zhang,P.F.,“Predicting Irreducible Water Saturation of Unconventional Reservoirs by Using NMR T2 Spectra:Methods of Morphological Division and Fractal Models”,Acta Geologica Sinica-English Edition(Accepted Article):https://doi.org/10.1111/1755-6724.15094.展开更多
Recently,information acquired at the canopy top,such as spectral and textural data,has been widely used to estimate plant nitrogen(N)accumulation(PNA).The response of crops to N uptake involves not only changes in hor...Recently,information acquired at the canopy top,such as spectral and textural data,has been widely used to estimate plant nitrogen(N)accumulation(PNA).The response of crops to N uptake involves not only changes in horizontal canopy top information but also an increase in vertical plant height(PH).It remains unclear whether the fusion of spectral indices with PH can improve the estimation performance of PNA models based on spectral remote sensing across different growth stages.展开更多
Five-valued Boolean functions play an important role in the design of symmetric cryptography.While the design and properties of single-output almost optimal five-valued spectra Boolean functions have been extensively ...Five-valued Boolean functions play an important role in the design of symmetric cryptography.While the design and properties of single-output almost optimal five-valued spectra Boolean functions have been extensively studied over the past few decades,there has been limited research on the construction of almost optimal five-valued spectra vectorial Boolean functions.In this paper,we present a construction method for even-variable 2-output almost optimal five-valued spectra balanced Boolean functions,whose Walsh spectra values belong to the set{0,±2^(n/2),±2^(n/2+1)},at the same time,we discuss the existence of sufficient conditions in the construction.Additionally,this paper presents a novel construction method for balanced single-output Boolean functions with even variables featuring a special five-valued spectral structure,whose Walsh spectra values are constrained to the set{0,±2^(n/2),±3·2^(n/2)}.These functions provide new canonical examples for the study of Boolean function spectral theory.展开更多
Deep learning neural network incorporating surface enhancement Raman scattering technique(SERS)is becoming as a powerful tool for the precise classifications and diagnosis of bacterial infections.However,the large amo...Deep learning neural network incorporating surface enhancement Raman scattering technique(SERS)is becoming as a powerful tool for the precise classifications and diagnosis of bacterial infections.However,the large amount of sample requirement and time-consuming sample collection severely hinder its applications.We herein propose a spectral concatenation strategy for residual neural network using nonspecific and specific SERS spectra for the training data augmentation,which is accessible to acquiring larger training dataset with same number of SERS spectra or same size of training dataset with fewer SERS spectra,compared with pure non-specific SERS spectra.With this strategy,the training loss exhibit rapid convergence,and an average accuracy up to 100%in bacteria classifications was achieved with50 SERS spectra for each kind of bacterium;even reduced to 20 SERS spectra per kind of bacterium,classification accuracy is still>95%,demonstrating marked advantage over the results without spectra concatenation.This method can markedly improve the classification accuracy under fewer samples and reduce the data collection workload,and can evidently enhance the performance when used in different machine learning models with high generalization ability.Therefore,this strategy is beneficial for rapid and accurate bacteria classifications with residual neural network.展开更多
Electrochemical impedance spectroscopy(EIS)offers valuable insights into the dynamic behaviors of lithium-ion batteries,making it a powerful and non-invasive tool for evaluating battery health.However,EIS falls short ...Electrochemical impedance spectroscopy(EIS)offers valuable insights into the dynamic behaviors of lithium-ion batteries,making it a powerful and non-invasive tool for evaluating battery health.However,EIS falls short in quantitatively determining the degree of specific degradation modes,which are essential for improving battery lifespan.This study introduces a novel approach employing deep neural networks enhanced by an attention mechanism to identify the degree of degradation modes.The proposed method can automatically determine the most relevant frequency ranges for each degradation mode,which can link impedance characteristics to battery degradation.To overcome the limitation of scarce labeled experimental data,simulation results derived from mechanistic models are incorporated into the model.Validation results demonstrate that the proposed method could achieve root mean square errors below 3%for estimating loss of lithium inventory and loss of active material of the positive electrode,and below 4%for estimating loss of active material of the negative electrode while requiring only 25%of early-stage experimental degradation data.By integrating simulation results,the proposed method achieves a reduction in maximum estimation error ranging from 42.92%to 66.30%across different temperatures and operating conditions compared to the baseline model trained solely on experimental data.展开更多
Prompt fission neutron spectra(PFNS)have a significant role in nuclear science and technology.In this study,the PFNS for^(239)Pu are evaluated using both differential and integral experimental data.A method that lever...Prompt fission neutron spectra(PFNS)have a significant role in nuclear science and technology.In this study,the PFNS for^(239)Pu are evaluated using both differential and integral experimental data.A method that leverages integral criticality benchmark experiments to constrain the PFNS data is introduced.The measured central values of the PFNS are perturbed by constructing a covariance matrix.The PFNS are sampled using two types of covariance matrices,either generated with an assumed correlation matrix and incorporating experimental uncertainties or derived directly from experimental reports.The joint Monte Carlo transport code is employed to perform transport simulations on five criticality benchmark assemblies by utilizing perturbed PFNS data.Extensive simulations result in an optimized PFNS that shows improved agreement with the integral criticality benchmark experiments.This study introduces a novel approach for optimizing differential experimental data through integral experiments,particularly when a covariance matrix is not provided.展开更多
The precise measurement of the antineutrino spectra produced by isotope fission in reactors is of great significance for studying neutrino oscillations,refining nuclear databases,and addressing the reactor antineutrin...The precise measurement of the antineutrino spectra produced by isotope fission in reactors is of great significance for studying neutrino oscillations,refining nuclear databases,and addressing the reactor antineutrino anomaly.In this paper,we report a method that utilizes a feedforward neural network(FNN)model to decompose the prompt energy spectrum observed in a short-baseline reactor neutrino experiment and extract the antineutrino spectra produced by the fission of major isotopes such as^(235)U,^(238)U,^(239)Pu,and^(241)Pu in the nuclear reactor.We present two training strategies for the model and compare them with the traditional X^(2) minimization method by applying them to the same set of pseudo-data corresponding to a total exposure of(2.9×5×1800)GW_(th)·tons·days.The results show that the FNN model not only converges faster and better during the fitting process but also achieves relative errors of less than 1%in the 2−8 MeV range in the extracted spectra,outperforming the X^(2) minimization method.The feasibility and superiority of this method were validated in the study.展开更多
In this study,we analyzed the characteristics of three-dimensional excitation-emission matrix spectra(EEMs)of 150 samples from five industrial wastewater types and domestic sewage to track water pollution sources effe...In this study,we analyzed the characteristics of three-dimensional excitation-emission matrix spectra(EEMs)of 150 samples from five industrial wastewater types and domestic sewage to track water pollution sources effectively.We then developed a recognition model for wastewater EEMs by establishing a feature dataset containing fluorescence peak values and parameters derived from EEMs,integrated with machine learning techniques.This model enables the rapid and precise identification of pollution sources.Our findings suggest that although the EEMs of the sixwastewater categories are distinct,visual differentiation is challenging.This was confirmed by cosine similarity assessments,showing some samples with low within-group(<0.8)and high between-group(>0.95)similarities.Despite significant variations in EEMs features acrosswastewater categories,identifying specific pollutants remains difficult,especially for pulp mills and leather effluents.Among the tested classification algorithms,Support Vector Machine(SVM)achieved the highest performance with91.7%accuracy,94%precision,91%recall,and 92%F_(1)-score,outperforming K-Nearest Neighbors and Partial Least Squares Discriminant Analysis.The SVM significantly improved identification accuracy for pulpmill and leather processing wastewaters compared to other models.To enhance identification accuracy,further exploration of EEMs features and expanding the training dataset are recommended.Combining EEMs features with machine learning presents a promising method for improvingwater pollution supervision and source tracing in environmental management practices.展开更多
The empirical models for wavenumber-frequency spectra of wall pressure are broadly used in the fast prediction of aerodynamic and hydrodynamic noise.However,it needs to fit the parameter using massive data and is only...The empirical models for wavenumber-frequency spectra of wall pressure are broadly used in the fast prediction of aerodynamic and hydrodynamic noise.However,it needs to fit the parameter using massive data and is only used for limited cases.In this letter,we propose Kolmogorov-Arnold networks(KAN)base models for wavenumber-frequency spectra of pressure fluctuations under turbulent boundary layers.The results are compared with DNS results.In turbulent channel flows,it is found that the KAN base model leads to a smooth wavenumber-frequency spectrum with sparse samples.In the turbulent flow over an axisymmetric body of revolution,the KAN base model captures the wavenumber-frequency spectra near the convective peak.展开更多
In the realm of engineering practice,various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra.Thus,accurately predi...In the realm of engineering practice,various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra.Thus,accurately predicting the fatigue life of structures becomes notably arduous.This paper proposed an approach to predict the fatigue life of structure based on the optimized load spectra,which is accurately estimated by an efficient hinging hyperplane neural network(EHH-NN)model.The construction of the EHH-NN model includes initial network generation and parameter optimization.Through the combination of working conditions design,multi-body dynamics analysis and structural static mechanics analysis,the simulated load spectra of the structure are obtained.The simulated load spectra are taken as the input variables for the optimized EHH-NN model,while the measurement load spectra are used as the output variables.The prediction results of case structure indicate that the optimized EHH-NN model can achieve the high-accuracy load spectra,in comparison with support vector machine(SVM),random forest(RF)model and back propagation(BP)neural network.The error rate between the prediction values and the measurement values of the optimized EHH-NN model is 4.61%.In the Cauchy-Lorentz distribution,the absolute error data of 92%with EHH-NN model appear in the intermediate range of±1.65%.Also,the fatigue life analysis is performed for the case structure,based on the accurately predicted load spectra.The fatigue life of the case structure is calculated based on the comparison between the measured and predicted load spectra,with an accuracy of 93.56%.This research proposes the optimized EHH-NN model can more accurately reflect the measurement load spectra,enabling precise calculation of fatigue life.Additionally,the optimized EHH-NN model provides reliability assessment for industrial engineering equipment.展开更多
The seismic damage to ancillary facilities on high-speed railway(HSR)bridges can affect the normal movement of trains.To propose the bridge deck acceleration response spectra of the typical HSR simply-supported girder...The seismic damage to ancillary facilities on high-speed railway(HSR)bridges can affect the normal movement of trains.To propose the bridge deck acceleration response spectra of the typical HSR simply-supported girder bridge for simplifying the seismic responses analysis of the facilities on bridges,the finite element models of the HSR multi-span simply-supported girder bridges with CRTSII track were established,and the numerical model was validated by tests.Besides,the effects of the span number,peak ground acceleration(PGA),pier height on the seismic acceleration and response spectra of the bridge deck were investigated.Afterward,the bridge acceleration amplification factor curves and bridge deck response spectra with different PGAs and pier heights were obtained.The formula for bridge deck acceleration amplification factor,with a 95%guarantee rate,was fitted.Moreover,the finite element models of the overhead contact lines(OCL)mounted on rigid base and bridges were established to validate the fitted formula.The results indicated that the maximum seismic acceleration response is in the midspan of the beam.The proposed formula for the bridge deck acceleration response spectra can be used to analyze the earthquake response of the OCL and other ancillary facilities on HSR simply-supported girder bridges.The bridge deck acceleration response spectra are conservative in terms of structural safety and can significantly improving the analysis efficiency.展开更多
We delve into the phenomenon of high-order harmonic generation within a helium atom under the influence of a plasmon-assisted shaping pulse.Our findings reveal an intriguing manipulation of the frequency peak position...We delve into the phenomenon of high-order harmonic generation within a helium atom under the influence of a plasmon-assisted shaping pulse.Our findings reveal an intriguing manipulation of the frequency peak position in the harmonic emission by adjusting the absolute phase parameter within the frequency domain of the shaping pulse.This phenomenon holds potential significance for experimental setups necessitating precisely tuned single harmonics.Notably,we observe a modulated shift in the created harmonic photon energy,spanning an impressive range of 1.2 eV.This frequency peak shift is rooted in the asymmetry exhibited by the rising and falling edges of the laser pulse,directly influencing the position of the peak frequency emission.Our study quantifies the dependence of this tuning range and the asymmetry of the laser pulse,offering valuable insights into the underlying mechanisms driving this phenomenon.Furthermore,our investigation uncovers the emergence of semi-integer order harmonics as the phase parameter is altered.We attribute this discovery to the intricate interference between harmonics generated by the primary and secondary return cores.This observation introduces an innovative approach for generating semi-integer order harmonics,thus expanding our understanding of high-order harmonic generation.Ultimately,our work contributes to the broader comprehension of complex phenomena in laser-matter interactions and provides a foundation for harnessing these effects in various applications,particularly those involving precise spectral control and the generation of unique harmonic patterns.展开更多
Manganese-based perovskite is popular for research on ferromagnetic materials,and its spectroscopic studies are essential for understanding its electronic structure,dielectric,electrical,and magnetic properties.In thi...Manganese-based perovskite is popular for research on ferromagnetic materials,and its spectroscopic studies are essential for understanding its electronic structure,dielectric,electrical,and magnetic properties.In this paper,the M-edge spectra of La ions and the M-edge,L-edge,and K-edge spectra of Mn ions in LaMnO3 are calculated by considering both the free-ion multiplet calculation and the crystal field effects.We analyze spectral shapes,identify peak origins,and estimate the oxidation states of La and Mn ions in LaMnO3 theoretically.It is concluded that La ions in LaMnO3 predominantly exist in the trivalent state,while Mn ions exist primarily in the trivalent state with a minor presence of tetravalent ions.Furthermore,the calculated spectra are in better conformity with the experimental spectra when the proportion of Mn3+is 90%and Mn4+is 10%.This article enhances our comprehension of the oxidation states of La and Mn within the crystal and also provides a valuable guidance for spectroscopic investigations of other manganates.展开更多
A vacuum ultraviolet(VUV)spectroscopy with a focal length of 1 m has been engineered specifically for observing edge impurity emissions in Experimental Advanced Superconducting Tokamak(EAST).In this study,wavelength c...A vacuum ultraviolet(VUV)spectroscopy with a focal length of 1 m has been engineered specifically for observing edge impurity emissions in Experimental Advanced Superconducting Tokamak(EAST).In this study,wavelength calibration for the VUV spectroscopy is achieved utilizing a zinc lamp.The grating angle and charge-coupled device(CCD)position are carefully calibrated for different wavelength positions.The wavelength calibration of the VUV spectroscopy is crucial for improving the accuracy of impurity spectral data,and is required to identify more impurity spectral lines for impurity transport research.Impurity spectra of EAST plasmas have also been obtained in the wavelength range of 50–300 nm with relatively high spectral resolution.It is found that the impurity emissions in the edge region are still dominated by low-Z impurities,such as carbon,oxygen,and nitrogen,albeit with the application of fulltungsten divertors on the EAST tokamak.展开更多
Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS...Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS)rate.This approach even allowed to obtain,by far,the best resolved ^(1)H spectra of molecular solids[1](https://doi.org/10.1002/anie.202216607).Deep learning based artificial intelligence is developing rapidly,and its application is deepening.Currently,there are many applications of deep learning in the field of magnetic resonance,such as the reconstruction of the under-sampled multidimensional spectra[2-4],the deconvolution of two-dimensional NMR spectra[5]and noise suppression and weak peak retrial[6],etc.展开更多
This study explores the utilization of various chemometric analytical methods for determining the quality of pressed sesame oil with different adulteration levels of refined sesame oil using UV spectral fingerprints.T...This study explores the utilization of various chemometric analytical methods for determining the quality of pressed sesame oil with different adulteration levels of refined sesame oil using UV spectral fingerprints.The goal of this study was to provide a reliable tool for assessing the quality of sesame oil.The UV spectra of 51 samples of pressed sesame oil and 420 adulterated samples with refined sesame oil were measured in the range of 200-330 nm.Various classification and prediction methods,including linear discrimination analysis(LDA),support vector machines(SVM),soft independent modeling of class analogy(SIMCA),partial least squares regression(PLSR),support vector machine regression(SVR),and back-propagation neural network(BPNN),were employed to analyze the UV spectral data of pressed sesame oil and adulterated sesame oil.The results indicated that SVM outperformed the other classification methods in qualitatively identifying adulterated sesame oil,achieving an accuracy of 96.15%,a sensitivity of 97.87%,and a specificity of 80%.For quantitative analysis,BPNN yielded the best prediction results,with an R^(2) value of 0.99,RMSEP of 2.34%,and RPD value of 10.60(LOD of 8.60%and LOQ of 28.67%).Overall,the developed models exhibited significant potential for rapidly identifying and predicting the quality of sesame oil.展开更多
The Raman spectra in the C-H stretching region are of great importance for the study of the structure and dynamics of organic compounds.However,the Fermi resonance between the first overtone mode of C-H bending vibrat...The Raman spectra in the C-H stretching region are of great importance for the study of the structure and dynamics of organic compounds.However,the Fermi resonance between the first overtone mode of C-H bending vibration and C-H stretching vibration typically results in the disturbance of Raman bands in the C-H stretching region.In this context,a specific deuterated molecule with only one C-H bond was proposed,and it was found that the frequency of the first overtone mode of the C-H bending vibration was significantly different from the frequency of the C-H stretching vibration.Due to the significant discrepancy,Fermi resonance in the C-H stretching region was eliminated from the experimental and theoretical Raman spectra of deuterated leucine,deuterated benzoin,deuterated methanol,and deuterated ethanol.Hence then,the Raman spectra of these specific deuterated compounds in the C-H stretching region can be used to study the structure or the dynamics of the organic compounds.展开更多
Wheat ( Triticum aestivum L.) plants were grown under ambient and doubled_CO 2(plus 350 μL/L) concentration in cylindrical open_top chamber to examine their effects on the ultrastructure, supramolecular architect...Wheat ( Triticum aestivum L.) plants were grown under ambient and doubled_CO 2(plus 350 μL/L) concentration in cylindrical open_top chamber to examine their effects on the ultrastructure, supramolecular architecture, absorption spectrum and low temperature (77 K) fluorescence emission spectrum of the chloroplasts from wheat leaves. The results were briefly summarized as follows: (1) The wheat leaves possessed normally developed chloroplasts with intact grana and stroma thylakoid membranes; The grana intertwined with stroma thylakoid membranes and increased slightly in stacking degree and the width of granum, in spite of more accumulated starch grains within the chloroplasts than those in control; (2) The particle density in the stacked region of the endoplasmic fracture face (EFs) and protoplasmic fracture face (PFs) and in the unstacked region the endoplasmic fracture face (EFu) and the protoplasmic fracture face (PFu) was significantly higher than that of control. Furthermore, in some cases many more particles on EFs faces of thylakoid membranes appeared as a paracrystalline particle array; (3) The variations in the structure of chloroplasts were consistent with the absorption spectra and the low temperature (77 K) fluorescence emission spectra of the chloroplasts developed under the doubled_CO 2 concentration. Results indicate that the capability of light energy absorption of chloroplasts and regulative capability of excitation energy distribution between PSⅡ and PSⅠ were raised by doubled_CO 2 concentration. This is very favorable for final productivity of wheat.展开更多
To extract vegetation pigment concentration and physiological status has been studied in two test areas covered with swamp and flourish vegetation using pushbroom hyperspectral imager (PHI) data which flied in Septemb...To extract vegetation pigment concentration and physiological status has been studied in two test areas covered with swamp and flourish vegetation using pushbroom hyperspectral imager (PHI) data which flied in September of 2000 at Daxing'anling district of Heilongjiang Province, China. The ratio analysis of reflectance spectra (RARS) indices, which were put forward by Chappelle et al (1992), are chosen in this paper owing to their effect and simpleness against both comparison with various methods and techniques for exploration of pigment concentration and characteristics of PHI data. The correlation coefficients between RARS indices and pigment concentration of vegetation were up to 0.8. The new RARS indices modes are established in the two test areas using both PHI data and spectra of different vegetations measured in the field. The indices' parameter images of chlorophyll a (Chl a), chlorophyll b (Chl b) and carotenoids (Cars) of the test areas covered with swamp and flourish vegetation are acquired by the new RARS indices modes. Furthermore, the regional concentration of Chl a and Chl b are extracted and quantified using regression equations between RARS indices and pigment concentrations, which were built by Blackburn (1998). The results showed the physiological status and variety clearly, and are in good agreement with the distribution of vegetation in the field.展开更多
文摘WITHDRAWAL:Zhang,J.J.,Guo,Y.Q.,Qin,Z.Y.,Wei,C.T.,Hu,Q.H.,Vandeginste,V.,Miao,H.Y.,Yao,P.,and Zhang,P.F.,“Predicting Irreducible Water Saturation of Unconventional Reservoirs by Using NMR T2 Spectra:Methods of Morphological Division and Fractal Models”,Acta Geologica Sinica-English Edition(Accepted Article):https://doi.org/10.1111/1755-6724.15094.
基金supported by the National Key Research and Development Plan Project Sub-Topic of China(Grant Nos.2022YFD1901500 and 2022YFD1901505-07)the National Natural Science Foundation of China(Grant No.32260531)+1 种基金the Key Laboratory of Molecular Breeding for Grain and Oil Crops in Guizhou Province,China(Grant No.Qiankehezhongyindi[2023]8)the Key Laboratory of Functional Agriculture of Guizhou Provincial Higher Education Institutions,China(Grant No.Qianjiaoji[2023]007).
文摘Recently,information acquired at the canopy top,such as spectral and textural data,has been widely used to estimate plant nitrogen(N)accumulation(PNA).The response of crops to N uptake involves not only changes in horizontal canopy top information but also an increase in vertical plant height(PH).It remains unclear whether the fusion of spectral indices with PH can improve the estimation performance of PNA models based on spectral remote sensing across different growth stages.
基金National Natural Science Foundation of China(62272360)。
文摘Five-valued Boolean functions play an important role in the design of symmetric cryptography.While the design and properties of single-output almost optimal five-valued spectra Boolean functions have been extensively studied over the past few decades,there has been limited research on the construction of almost optimal five-valued spectra vectorial Boolean functions.In this paper,we present a construction method for even-variable 2-output almost optimal five-valued spectra balanced Boolean functions,whose Walsh spectra values belong to the set{0,±2^(n/2),±2^(n/2+1)},at the same time,we discuss the existence of sufficient conditions in the construction.Additionally,this paper presents a novel construction method for balanced single-output Boolean functions with even variables featuring a special five-valued spectral structure,whose Walsh spectra values are constrained to the set{0,±2^(n/2),±3·2^(n/2)}.These functions provide new canonical examples for the study of Boolean function spectral theory.
基金supported by the National Key Research and Development Program of China(No.2023YFC3402900)the National Nature Science of Foundation(No.61875131)+1 种基金Shenzhen Key Laboratory of Photonics and Biophotonics(No.ZDSYS20210623092006020)Shenzhen Science and Technology Innovation Program(No.20231120175730001)。
文摘Deep learning neural network incorporating surface enhancement Raman scattering technique(SERS)is becoming as a powerful tool for the precise classifications and diagnosis of bacterial infections.However,the large amount of sample requirement and time-consuming sample collection severely hinder its applications.We herein propose a spectral concatenation strategy for residual neural network using nonspecific and specific SERS spectra for the training data augmentation,which is accessible to acquiring larger training dataset with same number of SERS spectra or same size of training dataset with fewer SERS spectra,compared with pure non-specific SERS spectra.With this strategy,the training loss exhibit rapid convergence,and an average accuracy up to 100%in bacteria classifications was achieved with50 SERS spectra for each kind of bacterium;even reduced to 20 SERS spectra per kind of bacterium,classification accuracy is still>95%,demonstrating marked advantage over the results without spectra concatenation.This method can markedly improve the classification accuracy under fewer samples and reduce the data collection workload,and can evidently enhance the performance when used in different machine learning models with high generalization ability.Therefore,this strategy is beneficial for rapid and accurate bacteria classifications with residual neural network.
基金supported by the National Key R&D Program of China(2024YFB2505003).
文摘Electrochemical impedance spectroscopy(EIS)offers valuable insights into the dynamic behaviors of lithium-ion batteries,making it a powerful and non-invasive tool for evaluating battery health.However,EIS falls short in quantitatively determining the degree of specific degradation modes,which are essential for improving battery lifespan.This study introduces a novel approach employing deep neural networks enhanced by an attention mechanism to identify the degree of degradation modes.The proposed method can automatically determine the most relevant frequency ranges for each degradation mode,which can link impedance characteristics to battery degradation.To overcome the limitation of scarce labeled experimental data,simulation results derived from mechanistic models are incorporated into the model.Validation results demonstrate that the proposed method could achieve root mean square errors below 3%for estimating loss of lithium inventory and loss of active material of the positive electrode,and below 4%for estimating loss of active material of the negative electrode while requiring only 25%of early-stage experimental degradation data.By integrating simulation results,the proposed method achieves a reduction in maximum estimation error ranging from 42.92%to 66.30%across different temperatures and operating conditions compared to the baseline model trained solely on experimental data.
基金supported by the National Natural Science Foundation of China(No.12347126)。
文摘Prompt fission neutron spectra(PFNS)have a significant role in nuclear science and technology.In this study,the PFNS for^(239)Pu are evaluated using both differential and integral experimental data.A method that leverages integral criticality benchmark experiments to constrain the PFNS data is introduced.The measured central values of the PFNS are perturbed by constructing a covariance matrix.The PFNS are sampled using two types of covariance matrices,either generated with an assumed correlation matrix and incorporating experimental uncertainties or derived directly from experimental reports.The joint Monte Carlo transport code is employed to perform transport simulations on five criticality benchmark assemblies by utilizing perturbed PFNS data.Extensive simulations result in an optimized PFNS that shows improved agreement with the integral criticality benchmark experiments.This study introduces a novel approach for optimizing differential experimental data through integral experiments,particularly when a covariance matrix is not provided.
基金supported by the China Postdoctoral Science Foundation(No.2024M753715)Fundamental Research Funds for the Central Universities,Sun Yat-sen University(Nos.24qnpy125 and 22lglj11)Guangdong Basic and Applied Basic Research Foundation(No.2023B1515120030).
文摘The precise measurement of the antineutrino spectra produced by isotope fission in reactors is of great significance for studying neutrino oscillations,refining nuclear databases,and addressing the reactor antineutrino anomaly.In this paper,we report a method that utilizes a feedforward neural network(FNN)model to decompose the prompt energy spectrum observed in a short-baseline reactor neutrino experiment and extract the antineutrino spectra produced by the fission of major isotopes such as^(235)U,^(238)U,^(239)Pu,and^(241)Pu in the nuclear reactor.We present two training strategies for the model and compare them with the traditional X^(2) minimization method by applying them to the same set of pseudo-data corresponding to a total exposure of(2.9×5×1800)GW_(th)·tons·days.The results show that the FNN model not only converges faster and better during the fitting process but also achieves relative errors of less than 1%in the 2−8 MeV range in the extracted spectra,outperforming the X^(2) minimization method.The feasibility and superiority of this method were validated in the study.
基金supported by the Leading Talent of the Science and Technology Nova Program of Zhejiang(No.2020R52039)the Outstanding Innovative Team Supporting Plan of Jiaxing City(No.2022-LHYJ-02-0503-02)+1 种基金the Key Research Project of Yangtze Delta Region Institute of Tsinghua University(No.2023ZQZ005)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX22-1386).
文摘In this study,we analyzed the characteristics of three-dimensional excitation-emission matrix spectra(EEMs)of 150 samples from five industrial wastewater types and domestic sewage to track water pollution sources effectively.We then developed a recognition model for wastewater EEMs by establishing a feature dataset containing fluorescence peak values and parameters derived from EEMs,integrated with machine learning techniques.This model enables the rapid and precise identification of pollution sources.Our findings suggest that although the EEMs of the sixwastewater categories are distinct,visual differentiation is challenging.This was confirmed by cosine similarity assessments,showing some samples with low within-group(<0.8)and high between-group(>0.95)similarities.Despite significant variations in EEMs features acrosswastewater categories,identifying specific pollutants remains difficult,especially for pulp mills and leather effluents.Among the tested classification algorithms,Support Vector Machine(SVM)achieved the highest performance with91.7%accuracy,94%precision,91%recall,and 92%F_(1)-score,outperforming K-Nearest Neighbors and Partial Least Squares Discriminant Analysis.The SVM significantly improved identification accuracy for pulpmill and leather processing wastewaters compared to other models.To enhance identification accuracy,further exploration of EEMs features and expanding the training dataset are recommended.Combining EEMs features with machine learning presents a promising method for improvingwater pollution supervision and source tracing in environmental management practices.
基金supported by the National Natural Science Foundation of China Basic Science Center Program for“Multiscale Problems in Nonlinear Mechanics”(Grant No.11988102)the National Natural Science Foundation of China(Grant Nos.92252203,12102439,and 12425207)+1 种基金the Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-087)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB0620102).
文摘The empirical models for wavenumber-frequency spectra of wall pressure are broadly used in the fast prediction of aerodynamic and hydrodynamic noise.However,it needs to fit the parameter using massive data and is only used for limited cases.In this letter,we propose Kolmogorov-Arnold networks(KAN)base models for wavenumber-frequency spectra of pressure fluctuations under turbulent boundary layers.The results are compared with DNS results.In turbulent channel flows,it is found that the KAN base model leads to a smooth wavenumber-frequency spectrum with sparse samples.In the turbulent flow over an axisymmetric body of revolution,the KAN base model captures the wavenumber-frequency spectra near the convective peak.
基金Supported by National Natural Science Foundation of China(Grant No.51805447)Natural Science Foundation of Jiangsu Higher Education of China(Grant No.22KJB460010)+2 种基金Jiangsu Provincial Innovation and Promotion Project of Forestry Science and Technology of China(Grant No.LYKJ[2023]06)Yangzhou Science and Technology Plan(City School Cooperation Project)of China(Grant No.YZ2022193)Cyan Blue Project of Yangzhou University of China。
文摘In the realm of engineering practice,various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra.Thus,accurately predicting the fatigue life of structures becomes notably arduous.This paper proposed an approach to predict the fatigue life of structure based on the optimized load spectra,which is accurately estimated by an efficient hinging hyperplane neural network(EHH-NN)model.The construction of the EHH-NN model includes initial network generation and parameter optimization.Through the combination of working conditions design,multi-body dynamics analysis and structural static mechanics analysis,the simulated load spectra of the structure are obtained.The simulated load spectra are taken as the input variables for the optimized EHH-NN model,while the measurement load spectra are used as the output variables.The prediction results of case structure indicate that the optimized EHH-NN model can achieve the high-accuracy load spectra,in comparison with support vector machine(SVM),random forest(RF)model and back propagation(BP)neural network.The error rate between the prediction values and the measurement values of the optimized EHH-NN model is 4.61%.In the Cauchy-Lorentz distribution,the absolute error data of 92%with EHH-NN model appear in the intermediate range of±1.65%.Also,the fatigue life analysis is performed for the case structure,based on the accurately predicted load spectra.The fatigue life of the case structure is calculated based on the comparison between the measured and predicted load spectra,with an accuracy of 93.56%.This research proposes the optimized EHH-NN model can more accurately reflect the measurement load spectra,enabling precise calculation of fatigue life.Additionally,the optimized EHH-NN model provides reliability assessment for industrial engineering equipment.
基金Project(HNTY2022K03)supported by the Hunan Tieyuan Civil Engineering Testing Co.,Ltd.,ChinaProject(52478573)supported by the National Natural Science Foundation of China。
文摘The seismic damage to ancillary facilities on high-speed railway(HSR)bridges can affect the normal movement of trains.To propose the bridge deck acceleration response spectra of the typical HSR simply-supported girder bridge for simplifying the seismic responses analysis of the facilities on bridges,the finite element models of the HSR multi-span simply-supported girder bridges with CRTSII track were established,and the numerical model was validated by tests.Besides,the effects of the span number,peak ground acceleration(PGA),pier height on the seismic acceleration and response spectra of the bridge deck were investigated.Afterward,the bridge acceleration amplification factor curves and bridge deck response spectra with different PGAs and pier heights were obtained.The formula for bridge deck acceleration amplification factor,with a 95%guarantee rate,was fitted.Moreover,the finite element models of the overhead contact lines(OCL)mounted on rigid base and bridges were established to validate the fitted formula.The results indicated that the maximum seismic acceleration response is in the midspan of the beam.The proposed formula for the bridge deck acceleration response spectra can be used to analyze the earthquake response of the OCL and other ancillary facilities on HSR simply-supported girder bridges.The bridge deck acceleration response spectra are conservative in terms of structural safety and can significantly improving the analysis efficiency.
基金This project was supported by the National Key Research and Development Program of China(Grant Nos.2022YFE134200 and 2019YFA0307700)the National Natural Science Foundation of China(Grant Nos.11604119,12104177,11904192,12074145,and 11704147)the Fundamental Research Funds for the Central Universities(Grant Nos.GK202207012 and QCYRCXM-2022-241).
文摘We delve into the phenomenon of high-order harmonic generation within a helium atom under the influence of a plasmon-assisted shaping pulse.Our findings reveal an intriguing manipulation of the frequency peak position in the harmonic emission by adjusting the absolute phase parameter within the frequency domain of the shaping pulse.This phenomenon holds potential significance for experimental setups necessitating precisely tuned single harmonics.Notably,we observe a modulated shift in the created harmonic photon energy,spanning an impressive range of 1.2 eV.This frequency peak shift is rooted in the asymmetry exhibited by the rising and falling edges of the laser pulse,directly influencing the position of the peak frequency emission.Our study quantifies the dependence of this tuning range and the asymmetry of the laser pulse,offering valuable insights into the underlying mechanisms driving this phenomenon.Furthermore,our investigation uncovers the emergence of semi-integer order harmonics as the phase parameter is altered.We attribute this discovery to the intricate interference between harmonics generated by the primary and secondary return cores.This observation introduces an innovative approach for generating semi-integer order harmonics,thus expanding our understanding of high-order harmonic generation.Ultimately,our work contributes to the broader comprehension of complex phenomena in laser-matter interactions and provides a foundation for harnessing these effects in various applications,particularly those involving precise spectral control and the generation of unique harmonic patterns.
基金Project supported by the National Natural Science Foundation of China(Grant No.11974253).
文摘Manganese-based perovskite is popular for research on ferromagnetic materials,and its spectroscopic studies are essential for understanding its electronic structure,dielectric,electrical,and magnetic properties.In this paper,the M-edge spectra of La ions and the M-edge,L-edge,and K-edge spectra of Mn ions in LaMnO3 are calculated by considering both the free-ion multiplet calculation and the crystal field effects.We analyze spectral shapes,identify peak origins,and estimate the oxidation states of La and Mn ions in LaMnO3 theoretically.It is concluded that La ions in LaMnO3 predominantly exist in the trivalent state,while Mn ions exist primarily in the trivalent state with a minor presence of tetravalent ions.Furthermore,the calculated spectra are in better conformity with the experimental spectra when the proportion of Mn3+is 90%and Mn4+is 10%.This article enhances our comprehension of the oxidation states of La and Mn within the crystal and also provides a valuable guidance for spectroscopic investigations of other manganates.
基金partially supported by National Natural Science Foundation of China(Nos.U23A2077,12175278,12205072)the National Magnetic Confinement Fusion Science Program of China(Nos.2019YFE0304002,2018YFE0303103)+2 种基金the Comprehensive Research Facility for Fusion Technology Program of China(No.2018-000052-73-01-001228)Major Science and Technology Infrastructure Maintenance and Reconstruction Projects of the Chinese Academy of Sciences(2021)the University Synergy Innovation Program of Anhui Province(No.GXXT2021-029)。
文摘A vacuum ultraviolet(VUV)spectroscopy with a focal length of 1 m has been engineered specifically for observing edge impurity emissions in Experimental Advanced Superconducting Tokamak(EAST).In this study,wavelength calibration for the VUV spectroscopy is achieved utilizing a zinc lamp.The grating angle and charge-coupled device(CCD)position are carefully calibrated for different wavelength positions.The wavelength calibration of the VUV spectroscopy is crucial for improving the accuracy of impurity spectral data,and is required to identify more impurity spectral lines for impurity transport research.Impurity spectra of EAST plasmas have also been obtained in the wavelength range of 50–300 nm with relatively high spectral resolution.It is found that the impurity emissions in the edge region are still dominated by low-Z impurities,such as carbon,oxygen,and nitrogen,albeit with the application of fulltungsten divertors on the EAST tokamak.
基金This work was partially supported by the National Natural Science Foundation of China(Grants 22174118 and 22374124).
文摘Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS)rate.This approach even allowed to obtain,by far,the best resolved ^(1)H spectra of molecular solids[1](https://doi.org/10.1002/anie.202216607).Deep learning based artificial intelligence is developing rapidly,and its application is deepening.Currently,there are many applications of deep learning in the field of magnetic resonance,such as the reconstruction of the under-sampled multidimensional spectra[2-4],the deconvolution of two-dimensional NMR spectra[5]and noise suppression and weak peak retrial[6],etc.
基金supported by the project number of“China Agricultural Research System funded by the Ministry of Agriculture”CARS-14,the Key Project of Science and Technology of Henan Province (201300110600)the“Double First-Class”Project for Postgraduate Academic Innovation Enhancement Programme of Henan University of Technology (HAUTSYL2023TS16)Education and Teaching Reform Research and Practice Project in School of International Education,Henan University of Technology (GJXY202407).
文摘This study explores the utilization of various chemometric analytical methods for determining the quality of pressed sesame oil with different adulteration levels of refined sesame oil using UV spectral fingerprints.The goal of this study was to provide a reliable tool for assessing the quality of sesame oil.The UV spectra of 51 samples of pressed sesame oil and 420 adulterated samples with refined sesame oil were measured in the range of 200-330 nm.Various classification and prediction methods,including linear discrimination analysis(LDA),support vector machines(SVM),soft independent modeling of class analogy(SIMCA),partial least squares regression(PLSR),support vector machine regression(SVR),and back-propagation neural network(BPNN),were employed to analyze the UV spectral data of pressed sesame oil and adulterated sesame oil.The results indicated that SVM outperformed the other classification methods in qualitatively identifying adulterated sesame oil,achieving an accuracy of 96.15%,a sensitivity of 97.87%,and a specificity of 80%.For quantitative analysis,BPNN yielded the best prediction results,with an R^(2) value of 0.99,RMSEP of 2.34%,and RPD value of 10.60(LOD of 8.60%and LOQ of 28.67%).Overall,the developed models exhibited significant potential for rapidly identifying and predicting the quality of sesame oil.
基金supported by the Key Research Project of Shaanxi Provincial Science and Technology Department(2023-YBNY-158)the Xi'an Science and Technology Project(22NYYF016)+3 种基金the Natural Science Foundation of Shaanxi Province(2022JM-087)the Open Fund of the State Key Laboratory of Molecular Reaction Dynamics in DICP,CAS,(SKLMRDK202413)the Fundamental Research Funds for the Central Universities(QTZX23007)the 111 Project.
文摘The Raman spectra in the C-H stretching region are of great importance for the study of the structure and dynamics of organic compounds.However,the Fermi resonance between the first overtone mode of C-H bending vibration and C-H stretching vibration typically results in the disturbance of Raman bands in the C-H stretching region.In this context,a specific deuterated molecule with only one C-H bond was proposed,and it was found that the frequency of the first overtone mode of the C-H bending vibration was significantly different from the frequency of the C-H stretching vibration.Due to the significant discrepancy,Fermi resonance in the C-H stretching region was eliminated from the experimental and theoretical Raman spectra of deuterated leucine,deuterated benzoin,deuterated methanol,and deuterated ethanol.Hence then,the Raman spectra of these specific deuterated compounds in the C-H stretching region can be used to study the structure or the dynamics of the organic compounds.
文摘Wheat ( Triticum aestivum L.) plants were grown under ambient and doubled_CO 2(plus 350 μL/L) concentration in cylindrical open_top chamber to examine their effects on the ultrastructure, supramolecular architecture, absorption spectrum and low temperature (77 K) fluorescence emission spectrum of the chloroplasts from wheat leaves. The results were briefly summarized as follows: (1) The wheat leaves possessed normally developed chloroplasts with intact grana and stroma thylakoid membranes; The grana intertwined with stroma thylakoid membranes and increased slightly in stacking degree and the width of granum, in spite of more accumulated starch grains within the chloroplasts than those in control; (2) The particle density in the stacked region of the endoplasmic fracture face (EFs) and protoplasmic fracture face (PFs) and in the unstacked region the endoplasmic fracture face (EFu) and the protoplasmic fracture face (PFu) was significantly higher than that of control. Furthermore, in some cases many more particles on EFs faces of thylakoid membranes appeared as a paracrystalline particle array; (3) The variations in the structure of chloroplasts were consistent with the absorption spectra and the low temperature (77 K) fluorescence emission spectra of the chloroplasts developed under the doubled_CO 2 concentration. Results indicate that the capability of light energy absorption of chloroplasts and regulative capability of excitation energy distribution between PSⅡ and PSⅠ were raised by doubled_CO 2 concentration. This is very favorable for final productivity of wheat.
文摘To extract vegetation pigment concentration and physiological status has been studied in two test areas covered with swamp and flourish vegetation using pushbroom hyperspectral imager (PHI) data which flied in September of 2000 at Daxing'anling district of Heilongjiang Province, China. The ratio analysis of reflectance spectra (RARS) indices, which were put forward by Chappelle et al (1992), are chosen in this paper owing to their effect and simpleness against both comparison with various methods and techniques for exploration of pigment concentration and characteristics of PHI data. The correlation coefficients between RARS indices and pigment concentration of vegetation were up to 0.8. The new RARS indices modes are established in the two test areas using both PHI data and spectra of different vegetations measured in the field. The indices' parameter images of chlorophyll a (Chl a), chlorophyll b (Chl b) and carotenoids (Cars) of the test areas covered with swamp and flourish vegetation are acquired by the new RARS indices modes. Furthermore, the regional concentration of Chl a and Chl b are extracted and quantified using regression equations between RARS indices and pigment concentrations, which were built by Blackburn (1998). The results showed the physiological status and variety clearly, and are in good agreement with the distribution of vegetation in the field.
