Portable ratiometric fluorescent platforms have emerged as promising tools for multifarious detection,yet remain unexplored for point-of-care monitoring doxorubicin(DOX),one of clinically antineoplastic drugs.To this ...Portable ratiometric fluorescent platforms have emerged as promising tools for multifarious detection,yet remain unexplored for point-of-care monitoring doxorubicin(DOX),one of clinically antineoplastic drugs.To this end,we herein develop a portable self-calibrating platform namely carbon dots(C-dots)-embedded hydrogel sensors with a smartphone-assisted high-throughput imaging device,for DOX sensing.The prepared green-emitting(λ_(em)=508 nm)and negatively-charged C-dots(−11.40±1.21 mV),which have sufficient spectral overlap with the absorption band of DOX(∼500 nm),can strongly bind with positively-charged DOX molecules by electrostatic attraction effects.As a result,DOX molecules are selectively and rapid(20 s)determined with a detection limit of 10.26 nmol/L via Förster resonance energy transfer processes,demonstrating a remarkably chromatic shift from green to red.Further integrated with a 3D-printed smartphone-assisted device,the platform enabled high-throughput quantification,achieving recoveries of 96.40%-101.85%in human urine/serum(RSDs<2.94%,n=3).Notably,the dual linear detection ranges of the platform align with the reported clinical DOX concentrations in urine and plasma(0-4 h post-administration),validating their capability for direct quantification of DOX in clinical samples without special pre-treatment processes.By virtue of attractive analytical performances and robust feasibility,this platform bridges laboratory precision and point-of-care testing needs,offering promising potential for personalized chemotherapy and multiplexed analyte screening.展开更多
Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data st...Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data structure to create virtual samples,which can be used to augment the original dataset.The ALVSG process consists of two steps.First,an average-linkage clustering technique is applied to the dataset to create a dendrogram.The dendrogram represents the hierarchical structure of the dataset,with each merging operation regarded as a linkage.Next,the linkages are combined into an average-based dataset,which serves as a new representation of the dataset.The second step in the ALVSG process involves generating virtual samples using the average-based dataset.The research project generates a set of 100 virtual samples by uniformly distributing them within the provided boundary.These virtual samples are then added to the original dataset,creating a more extensive dataset with improved generalization performance.The efficacy of the ALVSG approach is validated through resampling experiments and t-tests conducted on two small real-world datasets.The experiments are conducted on three forecasting models:the support vector machine for regression(SVR),the deep learning model(DL),and XGBoost.The results show that the ALVSG approach outperforms the baseline methods in terms of mean square error(MSE),root mean square error(RMSE),and mean absolute error(MAE).展开更多
As one of the major volatile components in extraterrestrial materials,nitrogen(N_(2))isotopes serve not only as tracers for the formation and evolution of the solar system,but also play a critical role in assessing pl...As one of the major volatile components in extraterrestrial materials,nitrogen(N_(2))isotopes serve not only as tracers for the formation and evolution of the solar system,but also play a critical role in assessing planetary habitability and the search for extraterrestrial life.The integrated measurement of N_(2)and argon(Ar)isotopes by using noble gas mass spectrometry represents a state-of-the-art technique for such investigations.To support the growing demands of planetary science research in China,we have developed a high-efficiency,high-precision method for the integrated analysis of N_(2)and Ar isotopes.This was achieved by enhancing gas extraction and purification systems and integrating them with a static noble gas mass spectrometer.This method enables integrated N_(2)-Ar isotope measurements on submilligram samples,significantly improving sample utilization and reducing the impact of sample heterogeneity on volatile analysis.The system integrates CO_(2)laser heating,a modular two-stage Zr-Al getter pump,and a CuO furnace-based purification process,effectively reducing background levels(N_(2)blank as low as 0.35×10^(−6)cubic centimeters at standard temperature and pressure[ccSTP]).Analytical precision is ensured through calibration with atmospheric air and CO corrections.To validate the reliability of the method,we performed N_(2)-Ar isotope analyses on the Allende carbonaceous chondrite,one of the most extensively studied meteorites internationally.The measured N_(2)concentrations range from 19.2 to 29.8 ppm,withδ15N values between−44.8‰and−33.0‰.Concentrations of 40Ar,36Ar,and 38Ar are(12.5-21.1)×10^(−6)ccSTP/g,(90.9-150.3)×10^(−9)ccSTP/g,and(19.2-30.7)×10^(−9)ccSTP/g,respectively.These values correspond to cosmic-ray exposure ages of 4.5-5.7 Ma,consistent with previous reports.Step-heating experiments further reveal distinct release patterns of N and Ar isotopes,as well as their associations with specific mineral phases in the meteorite.In summary,the combined N_(2)-Ar isotopic system offers significant advantages for tracing volatile sources in extraterrestrial materials and will provide essential analytical support for upcoming Chinese planetary missions,such as Tianwen-2.展开更多
Continuous control protocols are extensively utilized in traditional MASs,in which information needs to be transmitted among agents consecutively,therefore resulting in excessive consumption of limited resources.To de...Continuous control protocols are extensively utilized in traditional MASs,in which information needs to be transmitted among agents consecutively,therefore resulting in excessive consumption of limited resources.To decrease the control cost,based on ISC,several LFC problems are investigated for second-order MASs without and with time delay,respectively.Firstly,an intermittent sampled controller is designed,and a sufficient and necessary condition is derived,under which state errors between the leader and all the followers approach zero asymptotically.Considering that time delay is inevitable,a new protocol is proposed to deal with the time-delay situation.The error system’s stability is analyzed using the Schur stability theorem,and sufficient and necessary conditions for LFC are obtained,which are closely associated with the coupling gain,the system parameters,and the network structure.Furthermore,for the case where the current position and velocity information are not available,a distributed protocol is designed that depends only on the sampled position information.The sufficient and necessary conditions for LFC are also given.The results show that second-order MASs can achieve the LFC if and only if the system parameters satisfy the inequalities proposed in the paper.Finally,the correctness of the obtained results is verified by numerical simulations.展开更多
Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects ...Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects such as cracks and pores.In this study,3DP gypsum samples with different printing directions were subjected to a series of uniaxial compression tests with in situ micro-computed tomography(micro-CT)scanning to quantitatively investigate their mechanical anisotropic properties and damage evolution characteristics.Based on the two-dimensional(2D)CT images obtained at different scanning steps,a novel void ratio variable was derived using the mean value and variance of CT intensity.Additionally,a constitutive model was formulated incorporating the proposed damage variable,utilizing the void ratio variable.The crack evolution and crack morphology of 3DP gypsum samples were obtained and analyzed using the 3D models reconstructed from the CT images.The results indicate that 3DP gypsum samples exhibit mechanical anisotropic characteristics similar to those found in naturally sedimentary rocks.The mechanical anisotropy is attributed to the bedding planes formed between adjacent layers and pillar-like structures along the printing direction formed by CaSO_(4)·2H_(2)O crystals of needle-like morphology.The mean gray intensity of the voids has a positive linear relationship with the threshold value,while the CT variance and void ratio have concave and convex relationships,respectively.The constitutive model can effectively match the stress–strain curves obtained from uniaxial compression experiments.This study provides comprehensive explanations of the failure modes and anisotropic mechanisms of 3DP gypsum samples,which is important for characterizing and understanding the failure mechanism and microstructural evolution of 3DP rocks when modeling natural rock behavior.展开更多
Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining s...Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining samples do not correspond one-to-one correctly.Mismatched datasets caused by missing samples make the industrial data unavailable for further machine learning.In order to align the mismatched samples,this article presents a cooperative iteration matching method(CIMM)based on the modified dynamic time warping(DTW).The proposed method regards the sequentially accumulated industrial data as the time series.Mismatched samples are aligned by the DTW.In addition,dynamic constraints are applied to the warping distance of the DTW process to make the alignment more efficient.Then a series of models are trained with the cumulated samples iteratively.Several groups of numerical experiments on different missing patterns and missing locations are designed and analyzed to prove the effectiveness and the applicability of the proposed method.展开更多
Marine gas hydrates are highly sensitive to temperature and pressure fluctuations,and deviations from in-situ conditions may cause irreversible changes in phase state,microstructure,and mechanical properties.However,c...Marine gas hydrates are highly sensitive to temperature and pressure fluctuations,and deviations from in-situ conditions may cause irreversible changes in phase state,microstructure,and mechanical properties.However,conventional samplers often fail to maintain sealing and thermal stability,resulting in low sampling success rates.To address these challenges,an in-situ temperature-and pressure-preserved sampler for marine applications has been developed.The experimental results indicate that the selfdeveloped magnetically controlled pressure-preserved controller reliably achieves autonomous triggering and self-sealing,provides an initial sealing force of 83 N,and is capable of maintaining pressures up to 40 MPa.Additionally,a custom-designed intelligent temperature control chip and high-precision sensors were integrated into the sampler.Through the design of an optimized heat transfer structure,a temperature-preserved system was developed,achieving no more than a 0.3℃ rise in temperature within 2 h.The performance evaluation and sampling operations of the sampler were conducted at the Haima Cold Seep in the South China Sea,resulting in the successful recovery of hydrate maintained under in-situ pressure of 13.8 MPa and a temperature of 6.5℃.This advancement enables the acquisition of high-fidelity hydrate samples,providing critical support for the safe exploitation and scientific analysis of marine gas hydrate resources.展开更多
It is well known that nonuniform sampling is usually needed in special signals processing. In this paper, a general method to reconstruct Nth-order periodically nonuniform sampled signals is presented which is also de...It is well known that nonuniform sampling is usually needed in special signals processing. In this paper, a general method to reconstruct Nth-order periodically nonuniform sampled signals is presented which is also developed to digital domain, and the designs of the digital filters and the synthesis system are given. This paper extends the studies of Kohlenberg, whose work concentrate on the periodically nonuniform sampling of second order, as well as the studies of A.J.Coulson, J.L.Brown, whose work deal with the problems of two-band signals’ Nth-order sampling and reconstruction.展开更多
As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,qu...As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,quantum-enhanced imaging can achieve ultra-high resolution,ultra-sensitive detection,and anti-interference imaging.Here,we introduce a quantum-enhanced scanning microscope under illumination of an entangled NOON state in polarization.For the phase imager with NOON states,we propose a simple four-basis projection method to replace the four-step phase-shifting method.We have achieved the phase imaging of micrometer-sized birefringent samples and biological cell specimens,with sensitivity close to the Heisenberg limit.The visibility of transmittance-based imaging shows a great enhancement for NOON states.Besides,we also demonstrate that the scanning imaging with NOON states enables the spatial resolution enhancement of√N compared with classical measurement.Our imaging method may provide some reference for the practical application of quantum imaging and is expected to promote the development of microscopic detection.展开更多
In this paper, the consensus problem with position sampled data for second-order multi-agent systems is investigated.The interaction topology among the agents is depicted by a directed graph. The full-order and reduce...In this paper, the consensus problem with position sampled data for second-order multi-agent systems is investigated.The interaction topology among the agents is depicted by a directed graph. The full-order and reduced-order observers with position sampled data are proposed, by which two kinds of sampled data-based consensus protocols are constructed. With the provided sampled protocols, the consensus convergence analysis of a continuous-time multi-agent system is equivalently transformed into that of a discrete-time system. Then, by using matrix theory and a sampled control analysis method, some sufficient and necessary consensus conditions based on the coupling parameters, spectrum of the Laplacian matrix and sampling period are obtained. While the sampling period tends to zero, our established necessary and sufficient conditions are degenerated to the continuous-time protocol case, which are consistent with the existing result for the continuous-time case. Finally, the effectiveness of our established results is illustrated by a simple simulation example.展开更多
An intelligent diagnosis method based on self-adaptiveWasserstein dual generative adversarial networks and feature fusion is proposed due to problems such as insufficient sample size and incomplete fault feature extra...An intelligent diagnosis method based on self-adaptiveWasserstein dual generative adversarial networks and feature fusion is proposed due to problems such as insufficient sample size and incomplete fault feature extraction,which are commonly faced by rolling bearings and lead to low diagnostic accuracy.Initially,dual models of the Wasserstein deep convolutional generative adversarial network incorporating gradient penalty(1D-2DWDCGAN)are constructed to augment the original dataset.A self-adaptive loss threshold control training strategy is introduced,and establishing a self-adaptive balancing mechanism for stable model training.Subsequently,a diagnostic model based on multidimensional feature fusion is designed,wherein complex features from various dimensions are extracted,merging the original signal waveform features,structured features,and time-frequency features into a deep composite feature representation that encompasses multiple dimensions and scales;thus,efficient and accurate small sample fault diagnosis is facilitated.Finally,an experiment between the bearing fault dataset of CaseWestern ReserveUniversity and the fault simulation experimental platformdataset of this research group shows that this method effectively supplements the dataset and remarkably improves the diagnostic accuracy.The diagnostic accuracy after data augmentation reached 99.94%and 99.87%in two different experimental environments,respectively.In addition,robustness analysis is conducted on the diagnostic accuracy of the proposed method under different noise backgrounds,verifying its good generalization performance.展开更多
A ＂green＂ and quick analytical method for complex compounds was developed for simultaneous determination of tyrosine （Tyr） and dopamine （DA） in urine samples in this paper. The three-way responsive data recorded...A ＂green＂ and quick analytical method for complex compounds was developed for simultaneous determination of tyrosine （Tyr） and dopamine （DA） in urine samples in this paper. The three-way responsive data recorded by excitation-emission matrix fluorescence （EEM） spectrometer was analyzed using second-order calibration methods based on both parallel factor analysis （PARAFAC） and self- weighted alternating trilinear decomposition （SWATLD） algorithms. The EEM spectra of the analytes were overlapped with the background in urine samples. However the second-order advantage of both PARAFAC and SWATLD methods was exploited, even in the presence of unknown interferences and the satisfactory results can be obtained. Furthermore, the linear ranges of Tyr and DA were determined to be 0.042-6.42 p.g/mL and 0.18-4.43/ug]mL, respectively, and the accuracies of both methods were validated by the analytical figures of merit （FOM）.展开更多
In the task of Facial Expression Recognition(FER),data uncertainty has been a critical factor affecting performance,typically arising from the ambiguity of facial expressions,low-quality images,and the subjectivity of...In the task of Facial Expression Recognition(FER),data uncertainty has been a critical factor affecting performance,typically arising from the ambiguity of facial expressions,low-quality images,and the subjectivity of annotators.Tracking the training history reveals that misclassified samples often exhibit high confidence and excessive uncertainty in the early stages of training.To address this issue,we propose an uncertainty-based robust sample selection strategy,which combines confidence error with RandAugment to improve image diversity,effectively reducing overfitting caused by uncertain samples during deep learning model training.To validate the effectiveness of the proposed method,extensive experiments were conducted on FER public benchmarks.The accuracy obtained were 89.08%on RAF-DB,63.12%on AffectNet,and 88.73%on FERPlus.展开更多
Medicinal and edible plants(MEPs)have attracted increasing interest worldwide due to their natural origin,reliable efficacy,and minimal side effects in recent years.However,the complex and fluctuating levels of inhere...Medicinal and edible plants(MEPs)have attracted increasing interest worldwide due to their natural origin,reliable efficacy,and minimal side effects in recent years.However,the complex and fluctuating levels of inherent chemical constituents and exogenous hazardous contaminants have triggered widespread concerns about their efficacy and safety.Developing analytical methods for both active components and exogenous contaminants concealed in these samples is central to the quality evaluation,in which sample preparation is crucial.This paper systematically reviewed the evolution of standard sample preparation methods,microextraction techniques based on novel solvents and nanomaterials,and innovative integrated techniques from 2019.Accordingly,their merits and weaknesses were discussed by showing fruitful applications in identifying and quantifying active components in these plants.Further,successful applications for analyzing exogenous contaminants were prominently showcased,highlighting the management of pesticides,heavy metals,mycotoxins,and polycyclic aromatic hydrocarbons(PAHs).Finally,forthcoming trends in sample preparation techniques were delineated to illuminate the development and implementation of more advanced sample preparation technologies.展开更多
Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noi...Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noisy intermediate quantum devices,photonic-based sampling machines solving the Gaussian boson sampling(GBS)problem currently play a central role in the experimental demonstration of quantum computational advantage.A relevant issue is the validation of the sampling process in the presence of experimental noise,such as photon losses,which could undermine the hardness of simulating the experiment.We test the capability of a validation protocol that exploits the connection between GBS and graph perfect match counting to perform such an assessment in a noisy scenario.In particular,we use as a test bench the recently developed machine Borealis,a large-scale sampling machine that has been made available online for external users,and address its operation in the presence of noise.The employed approach to validation is also shown to provide connections with the open question on the effective advantage of using noisy GBS devices for graph similarity and isomorphism problems and thus provides an effective method for certification of quantum hardware.展开更多
In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.T...In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.The resulting structure layer is then used to constrain the material texture synthesis.The field of second-moment matrices is used to represent the structure layer.Many tests with various constraint images are conducted to ensure that the proposed approach accurately reproduces the visual aspects of the input material sample.The results demonstrate that the proposed algorithm is able to accurately synthesize arbitrary-shaped material textures while respecting the local characteristics of the exemplar.This paves the way toward the synthesis of 3D material textures of arbitrary shapes from 2D material samples,which has a wide application range in virtual material design and materials characterization.展开更多
Systems with quenched disorder possess complex energy landscapes that are challenging to explore under conventional Monte Carlo methods.In this work,we implement an efficient entropy sampling scheme for accurate compu...Systems with quenched disorder possess complex energy landscapes that are challenging to explore under conventional Monte Carlo methods.In this work,we implement an efficient entropy sampling scheme for accurate computation of the entropy function in low-energy regions.The method is applied to the two-dimensional±J random-bond Ising model,where frustration is controlled by the fraction p of ferromagnetic bonds.We investigate the low-temperature paramagnetic–ferromagnetic phase boundary below the multicritical point at T_(N)=0.9530(4),P_(N)=0.89078(8),as well as the zerotemperature ferromagnetic–spin-glass transition.Finite-size scaling analysis reveals that the phase boundary for T<T_(N) exhibits reentrant behavior.By analyzing the evolution of the magnetizationresolved density of states g(E,M)and ground-state spin configurations against increasing frustration,we provide strong evidence that the zero-temperature transition is a mixed-order.Finite-size scaling conducted on the spin-glass side supports the validity of β=0,whereβis the magnetization exponent,with a correlation length exponentν=1.50(8).Our results provide new insights into the nature of the ferromagnetic-to-spin-glass phase transition in an extensively degenerate ground state.展开更多
In this paper, we use sample average approximation with adaptive multiple importance sampling to explore moderate deviations for the optimal values. Utilizing the moderate deviation principle for martingale difference...In this paper, we use sample average approximation with adaptive multiple importance sampling to explore moderate deviations for the optimal values. Utilizing the moderate deviation principle for martingale differences and an appropriate Delta method, we establish a moderate deviation principle for the optimal value. Moreover, for a functional form of stochastic programming, we obtain a functional moderate deviation principle for its optimal value.展开更多
基金supported by the National NaturalScience Foundation of China(No.22274001)the Key Project of Natural Science Research of the Education Department of Anhui Province(No.2022AH051032)the Excellent Research and Innovation Team of Universities in Anhui Province(No.2024AH010016).
文摘Portable ratiometric fluorescent platforms have emerged as promising tools for multifarious detection,yet remain unexplored for point-of-care monitoring doxorubicin(DOX),one of clinically antineoplastic drugs.To this end,we herein develop a portable self-calibrating platform namely carbon dots(C-dots)-embedded hydrogel sensors with a smartphone-assisted high-throughput imaging device,for DOX sensing.The prepared green-emitting(λ_(em)=508 nm)and negatively-charged C-dots(−11.40±1.21 mV),which have sufficient spectral overlap with the absorption band of DOX(∼500 nm),can strongly bind with positively-charged DOX molecules by electrostatic attraction effects.As a result,DOX molecules are selectively and rapid(20 s)determined with a detection limit of 10.26 nmol/L via Förster resonance energy transfer processes,demonstrating a remarkably chromatic shift from green to red.Further integrated with a 3D-printed smartphone-assisted device,the platform enabled high-throughput quantification,achieving recoveries of 96.40%-101.85%in human urine/serum(RSDs<2.94%,n=3).Notably,the dual linear detection ranges of the platform align with the reported clinical DOX concentrations in urine and plasma(0-4 h post-administration),validating their capability for direct quantification of DOX in clinical samples without special pre-treatment processes.By virtue of attractive analytical performances and robust feasibility,this platform bridges laboratory precision and point-of-care testing needs,offering promising potential for personalized chemotherapy and multiplexed analyte screening.
基金funding support from the National Science and Technology Council(NSTC),under Grant No.114-2410-H-011-026-MY3.
文摘Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data structure to create virtual samples,which can be used to augment the original dataset.The ALVSG process consists of two steps.First,an average-linkage clustering technique is applied to the dataset to create a dendrogram.The dendrogram represents the hierarchical structure of the dataset,with each merging operation regarded as a linkage.Next,the linkages are combined into an average-based dataset,which serves as a new representation of the dataset.The second step in the ALVSG process involves generating virtual samples using the average-based dataset.The research project generates a set of 100 virtual samples by uniformly distributing them within the provided boundary.These virtual samples are then added to the original dataset,creating a more extensive dataset with improved generalization performance.The efficacy of the ALVSG approach is validated through resampling experiments and t-tests conducted on two small real-world datasets.The experiments are conducted on three forecasting models:the support vector machine for regression(SVR),the deep learning model(DL),and XGBoost.The results show that the ALVSG approach outperforms the baseline methods in terms of mean square error(MSE),root mean square error(RMSE),and mean absolute error(MAE).
基金supported by the Bureau of Frontier Sciences and Basic Research,Chinese Academy of Sciences(Grant No.QYJ-2025-0103)the National Natural Science Foundation of China(Grant Nos.42441834,42241105,42441825,and 42203048)the Key Research Program of the Institute of Geology and Geophysics,Chinese Academy of Sciences(Grant No.IGGCAS-202401).
文摘As one of the major volatile components in extraterrestrial materials,nitrogen(N_(2))isotopes serve not only as tracers for the formation and evolution of the solar system,but also play a critical role in assessing planetary habitability and the search for extraterrestrial life.The integrated measurement of N_(2)and argon(Ar)isotopes by using noble gas mass spectrometry represents a state-of-the-art technique for such investigations.To support the growing demands of planetary science research in China,we have developed a high-efficiency,high-precision method for the integrated analysis of N_(2)and Ar isotopes.This was achieved by enhancing gas extraction and purification systems and integrating them with a static noble gas mass spectrometer.This method enables integrated N_(2)-Ar isotope measurements on submilligram samples,significantly improving sample utilization and reducing the impact of sample heterogeneity on volatile analysis.The system integrates CO_(2)laser heating,a modular two-stage Zr-Al getter pump,and a CuO furnace-based purification process,effectively reducing background levels(N_(2)blank as low as 0.35×10^(−6)cubic centimeters at standard temperature and pressure[ccSTP]).Analytical precision is ensured through calibration with atmospheric air and CO corrections.To validate the reliability of the method,we performed N_(2)-Ar isotope analyses on the Allende carbonaceous chondrite,one of the most extensively studied meteorites internationally.The measured N_(2)concentrations range from 19.2 to 29.8 ppm,withδ15N values between−44.8‰and−33.0‰.Concentrations of 40Ar,36Ar,and 38Ar are(12.5-21.1)×10^(−6)ccSTP/g,(90.9-150.3)×10^(−9)ccSTP/g,and(19.2-30.7)×10^(−9)ccSTP/g,respectively.These values correspond to cosmic-ray exposure ages of 4.5-5.7 Ma,consistent with previous reports.Step-heating experiments further reveal distinct release patterns of N and Ar isotopes,as well as their associations with specific mineral phases in the meteorite.In summary,the combined N_(2)-Ar isotopic system offers significant advantages for tracing volatile sources in extraterrestrial materials and will provide essential analytical support for upcoming Chinese planetary missions,such as Tianwen-2.
基金supported by the National Natural Science Foundation of China under Grants 62476138 and 42375016.
文摘Continuous control protocols are extensively utilized in traditional MASs,in which information needs to be transmitted among agents consecutively,therefore resulting in excessive consumption of limited resources.To decrease the control cost,based on ISC,several LFC problems are investigated for second-order MASs without and with time delay,respectively.Firstly,an intermittent sampled controller is designed,and a sufficient and necessary condition is derived,under which state errors between the leader and all the followers approach zero asymptotically.Considering that time delay is inevitable,a new protocol is proposed to deal with the time-delay situation.The error system’s stability is analyzed using the Schur stability theorem,and sufficient and necessary conditions for LFC are obtained,which are closely associated with the coupling gain,the system parameters,and the network structure.Furthermore,for the case where the current position and velocity information are not available,a distributed protocol is designed that depends only on the sampled position information.The sufficient and necessary conditions for LFC are also given.The results show that second-order MASs can achieve the LFC if and only if the system parameters satisfy the inequalities proposed in the paper.Finally,the correctness of the obtained results is verified by numerical simulations.
基金supported by grants from the Human Resources Development program(Grant No.20204010600250)the Training Program of CCUS for the Green Growth(Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government(MOTIE).
文摘Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects such as cracks and pores.In this study,3DP gypsum samples with different printing directions were subjected to a series of uniaxial compression tests with in situ micro-computed tomography(micro-CT)scanning to quantitatively investigate their mechanical anisotropic properties and damage evolution characteristics.Based on the two-dimensional(2D)CT images obtained at different scanning steps,a novel void ratio variable was derived using the mean value and variance of CT intensity.Additionally,a constitutive model was formulated incorporating the proposed damage variable,utilizing the void ratio variable.The crack evolution and crack morphology of 3DP gypsum samples were obtained and analyzed using the 3D models reconstructed from the CT images.The results indicate that 3DP gypsum samples exhibit mechanical anisotropic characteristics similar to those found in naturally sedimentary rocks.The mechanical anisotropy is attributed to the bedding planes formed between adjacent layers and pillar-like structures along the printing direction formed by CaSO_(4)·2H_(2)O crystals of needle-like morphology.The mean gray intensity of the voids has a positive linear relationship with the threshold value,while the CT variance and void ratio have concave and convex relationships,respectively.The constitutive model can effectively match the stress–strain curves obtained from uniaxial compression experiments.This study provides comprehensive explanations of the failure modes and anisotropic mechanisms of 3DP gypsum samples,which is important for characterizing and understanding the failure mechanism and microstructural evolution of 3DP rocks when modeling natural rock behavior.
基金the Key National Natural Science Foundation of China(No.U1864211)the National Natural Science Foundation of China(No.11772191)the Natural Science Foundation of Shanghai(No.21ZR1431500)。
文摘Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining samples do not correspond one-to-one correctly.Mismatched datasets caused by missing samples make the industrial data unavailable for further machine learning.In order to align the mismatched samples,this article presents a cooperative iteration matching method(CIMM)based on the modified dynamic time warping(DTW).The proposed method regards the sequentially accumulated industrial data as the time series.Mismatched samples are aligned by the DTW.In addition,dynamic constraints are applied to the warping distance of the DTW process to make the alignment more efficient.Then a series of models are trained with the cumulated samples iteratively.Several groups of numerical experiments on different missing patterns and missing locations are designed and analyzed to prove the effectiveness and the applicability of the proposed method.
基金financially supported by Shenzhen Science and Technology Program(Nos.JSGG20220831105002005 and KJZD20231025152759002)Support from the National Natural Science Foundation of China(Nos.52374357 and 523B2101)funded by the Shared Voyages Project for Deep-sea and Abyss Scientific Research and Equipment Sea Trials of Hainan Deep-Sea Technology Innovation Center(No.DSTIC-GXHC-2022002)。
文摘Marine gas hydrates are highly sensitive to temperature and pressure fluctuations,and deviations from in-situ conditions may cause irreversible changes in phase state,microstructure,and mechanical properties.However,conventional samplers often fail to maintain sealing and thermal stability,resulting in low sampling success rates.To address these challenges,an in-situ temperature-and pressure-preserved sampler for marine applications has been developed.The experimental results indicate that the selfdeveloped magnetically controlled pressure-preserved controller reliably achieves autonomous triggering and self-sealing,provides an initial sealing force of 83 N,and is capable of maintaining pressures up to 40 MPa.Additionally,a custom-designed intelligent temperature control chip and high-precision sensors were integrated into the sampler.Through the design of an optimized heat transfer structure,a temperature-preserved system was developed,achieving no more than a 0.3℃ rise in temperature within 2 h.The performance evaluation and sampling operations of the sampler were conducted at the Haima Cold Seep in the South China Sea,resulting in the successful recovery of hydrate maintained under in-situ pressure of 13.8 MPa and a temperature of 6.5℃.This advancement enables the acquisition of high-fidelity hydrate samples,providing critical support for the safe exploitation and scientific analysis of marine gas hydrate resources.
文摘It is well known that nonuniform sampling is usually needed in special signals processing. In this paper, a general method to reconstruct Nth-order periodically nonuniform sampled signals is presented which is also developed to digital domain, and the designs of the digital filters and the synthesis system are given. This paper extends the studies of Kohlenberg, whose work concentrate on the periodically nonuniform sampling of second order, as well as the studies of A.J.Coulson, J.L.Brown, whose work deal with the problems of two-band signals’ Nth-order sampling and reconstruction.
基金supported by he National Natural Science Foundation of China(Grant Nos.12304359,12304398,12404382,12234009,12274215,and 12427808)the China Postdoctoral Science Foundation(Grant No.2023M731611)+4 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent(Grant No.2023ZB717)Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301400)Key R&D Program of Jiangsu Province(Grant No.BE2023002)Natural Science Foundation of Jiangsu Province(Grant Nos.BK20220759 and BK20233001)Program for Innovative Talents and Entrepreneurs in Jiangsu,and Key R&D Program of Guangdong Province(Grant No.2020B0303010001).
文摘As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,quantum-enhanced imaging can achieve ultra-high resolution,ultra-sensitive detection,and anti-interference imaging.Here,we introduce a quantum-enhanced scanning microscope under illumination of an entangled NOON state in polarization.For the phase imager with NOON states,we propose a simple four-basis projection method to replace the four-step phase-shifting method.We have achieved the phase imaging of micrometer-sized birefringent samples and biological cell specimens,with sensitivity close to the Heisenberg limit.The visibility of transmittance-based imaging shows a great enhancement for NOON states.Besides,we also demonstrate that the scanning imaging with NOON states enables the spatial resolution enhancement of√N compared with classical measurement.Our imaging method may provide some reference for the practical application of quantum imaging and is expected to promote the development of microscopic detection.
基金supported by the Natural Science Foundation of Zhejiang Province,China(Grant No.LY13F030005)the National Natural Science Foundation of China(Grant No.61501331)
文摘In this paper, the consensus problem with position sampled data for second-order multi-agent systems is investigated.The interaction topology among the agents is depicted by a directed graph. The full-order and reduced-order observers with position sampled data are proposed, by which two kinds of sampled data-based consensus protocols are constructed. With the provided sampled protocols, the consensus convergence analysis of a continuous-time multi-agent system is equivalently transformed into that of a discrete-time system. Then, by using matrix theory and a sampled control analysis method, some sufficient and necessary consensus conditions based on the coupling parameters, spectrum of the Laplacian matrix and sampling period are obtained. While the sampling period tends to zero, our established necessary and sufficient conditions are degenerated to the continuous-time protocol case, which are consistent with the existing result for the continuous-time case. Finally, the effectiveness of our established results is illustrated by a simple simulation example.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272259 and 52005148).
文摘An intelligent diagnosis method based on self-adaptiveWasserstein dual generative adversarial networks and feature fusion is proposed due to problems such as insufficient sample size and incomplete fault feature extraction,which are commonly faced by rolling bearings and lead to low diagnostic accuracy.Initially,dual models of the Wasserstein deep convolutional generative adversarial network incorporating gradient penalty(1D-2DWDCGAN)are constructed to augment the original dataset.A self-adaptive loss threshold control training strategy is introduced,and establishing a self-adaptive balancing mechanism for stable model training.Subsequently,a diagnostic model based on multidimensional feature fusion is designed,wherein complex features from various dimensions are extracted,merging the original signal waveform features,structured features,and time-frequency features into a deep composite feature representation that encompasses multiple dimensions and scales;thus,efficient and accurate small sample fault diagnosis is facilitated.Finally,an experiment between the bearing fault dataset of CaseWestern ReserveUniversity and the fault simulation experimental platformdataset of this research group shows that this method effectively supplements the dataset and remarkably improves the diagnostic accuracy.The diagnostic accuracy after data augmentation reached 99.94%and 99.87%in two different experimental environments,respectively.In addition,robustness analysis is conducted on the diagnostic accuracy of the proposed method under different noise backgrounds,verifying its good generalization performance.
基金National Natural Science Foundation of China(No.21175041)the National Basic Research Program(No.2012CBg10602)
文摘A ＂green＂ and quick analytical method for complex compounds was developed for simultaneous determination of tyrosine （Tyr） and dopamine （DA） in urine samples in this paper. The three-way responsive data recorded by excitation-emission matrix fluorescence （EEM） spectrometer was analyzed using second-order calibration methods based on both parallel factor analysis （PARAFAC） and self- weighted alternating trilinear decomposition （SWATLD） algorithms. The EEM spectra of the analytes were overlapped with the background in urine samples. However the second-order advantage of both PARAFAC and SWATLD methods was exploited, even in the presence of unknown interferences and the satisfactory results can be obtained. Furthermore, the linear ranges of Tyr and DA were determined to be 0.042-6.42 p.g/mL and 0.18-4.43/ug]mL, respectively, and the accuracies of both methods were validated by the analytical figures of merit （FOM）.
文摘In the task of Facial Expression Recognition(FER),data uncertainty has been a critical factor affecting performance,typically arising from the ambiguity of facial expressions,low-quality images,and the subjectivity of annotators.Tracking the training history reveals that misclassified samples often exhibit high confidence and excessive uncertainty in the early stages of training.To address this issue,we propose an uncertainty-based robust sample selection strategy,which combines confidence error with RandAugment to improve image diversity,effectively reducing overfitting caused by uncertain samples during deep learning model training.To validate the effectiveness of the proposed method,extensive experiments were conducted on FER public benchmarks.The accuracy obtained were 89.08%on RAF-DB,63.12%on AffectNet,and 88.73%on FERPlus.
基金supported by the National Natural Science Foundation of China(Grant No.:81903794)Macao Science and Technology Development Fund(Grant Nos.:0031/2022/AGJ,0014/2022/ITP,005/2023/SKL and 001/2023/ALC)+2 种基金Guangdong Basic and Applied Basic Research Foundation(Grant No.:2024A1515030214)Guangdong-Macao Science and Technology Innovation Joint Research Special Fund(Grant No.:2023A0505020013)the Research Committee of the University of Macao(Grant Nos.:SRG2022-00035-ICMS,MYRG-CRG2022-00016-ICMS,MYRG2023-00205-ICMS,and MYRG2023-00234-ICMS-UMDF)。
文摘Medicinal and edible plants(MEPs)have attracted increasing interest worldwide due to their natural origin,reliable efficacy,and minimal side effects in recent years.However,the complex and fluctuating levels of inherent chemical constituents and exogenous hazardous contaminants have triggered widespread concerns about their efficacy and safety.Developing analytical methods for both active components and exogenous contaminants concealed in these samples is central to the quality evaluation,in which sample preparation is crucial.This paper systematically reviewed the evolution of standard sample preparation methods,microextraction techniques based on novel solvents and nanomaterials,and innovative integrated techniques from 2019.Accordingly,their merits and weaknesses were discussed by showing fruitful applications in identifying and quantifying active components in these plants.Further,successful applications for analyzing exogenous contaminants were prominently showcased,highlighting the management of pesticides,heavy metals,mycotoxins,and polycyclic aromatic hydrocarbons(PAHs).Finally,forthcoming trends in sample preparation techniques were delineated to illuminate the development and implementation of more advanced sample preparation technologies.
基金supported by the ERC Advanced Grant QU-BOSS(QUantum advantage via nonlinear BOSon Sampling,Grant No.884676)by ICSC-Centro Nazionale di Ricerca in High Performance Computing,Big Data,and Quantum Computing,funded by the European Union-NextGenerationEU.D.S.acknowledges Thales Alenia Space Italia for supporting the PhD fellowship.N.S.acknowledges funding from Sapienza Universitàdi Roma via Bando Ricerca 2020:Progetti di Ricerca Piccoli,Project No.RP120172B8A36B37.
文摘Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noisy intermediate quantum devices,photonic-based sampling machines solving the Gaussian boson sampling(GBS)problem currently play a central role in the experimental demonstration of quantum computational advantage.A relevant issue is the validation of the sampling process in the presence of experimental noise,such as photon losses,which could undermine the hardness of simulating the experiment.We test the capability of a validation protocol that exploits the connection between GBS and graph perfect match counting to perform such an assessment in a noisy scenario.In particular,we use as a test bench the recently developed machine Borealis,a large-scale sampling machine that has been made available online for external users,and address its operation in the presence of noise.The employed approach to validation is also shown to provide connections with the open question on the effective advantage of using noisy GBS devices for graph similarity and isomorphism problems and thus provides an effective method for certification of quantum hardware.
文摘In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.The resulting structure layer is then used to constrain the material texture synthesis.The field of second-moment matrices is used to represent the structure layer.Many tests with various constraint images are conducted to ensure that the proposed approach accurately reproduces the visual aspects of the input material sample.The results demonstrate that the proposed algorithm is able to accurately synthesize arbitrary-shaped material textures while respecting the local characteristics of the exemplar.This paves the way toward the synthesis of 3D material textures of arbitrary shapes from 2D material samples,which has a wide application range in virtual material design and materials characterization.
基金supported by NKRDPC-2022YFA1402802,NSFC-92165204the Research Grants Council of the HKSAR under Grant Nos.12304020 and 12301723+2 种基金Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices under Grant No.2022B1212010008Guangdong Fundamental Research Center for Magnetoelectric Physics under Grant No.2024B0303390001Guangdong Provincial Quantum Science Strategic Initiative under Grant No.GDZX2401010。
文摘Systems with quenched disorder possess complex energy landscapes that are challenging to explore under conventional Monte Carlo methods.In this work,we implement an efficient entropy sampling scheme for accurate computation of the entropy function in low-energy regions.The method is applied to the two-dimensional±J random-bond Ising model,where frustration is controlled by the fraction p of ferromagnetic bonds.We investigate the low-temperature paramagnetic–ferromagnetic phase boundary below the multicritical point at T_(N)=0.9530(4),P_(N)=0.89078(8),as well as the zerotemperature ferromagnetic–spin-glass transition.Finite-size scaling analysis reveals that the phase boundary for T<T_(N) exhibits reentrant behavior.By analyzing the evolution of the magnetizationresolved density of states g(E,M)and ground-state spin configurations against increasing frustration,we provide strong evidence that the zero-temperature transition is a mixed-order.Finite-size scaling conducted on the spin-glass side supports the validity of β=0,whereβis the magnetization exponent,with a correlation length exponentν=1.50(8).Our results provide new insights into the nature of the ferromagnetic-to-spin-glass phase transition in an extensively degenerate ground state.
基金Supported by the National Natural Science Foundation of China(Grant No.12071175)。
文摘In this paper, we use sample average approximation with adaptive multiple importance sampling to explore moderate deviations for the optimal values. Utilizing the moderate deviation principle for martingale differences and an appropriate Delta method, we establish a moderate deviation principle for the optimal value. Moreover, for a functional form of stochastic programming, we obtain a functional moderate deviation principle for its optimal value.
