Full-color imaging is essential in digital pathology for accurate tissue analysis.Utilizing advanced optical modulation and phase retrieval algorithms,Fourier ptychographic microscopy(FPM)offers a powerful solution fo...Full-color imaging is essential in digital pathology for accurate tissue analysis.Utilizing advanced optical modulation and phase retrieval algorithms,Fourier ptychographic microscopy(FPM)offers a powerful solution for high-throughput digital pathology,combining high resolution,large field of view,and extended depth of field(DOF).However,the full-color capabilities of FPM are hindered by coherent color artifacts and reduced computational efficiency,which significantly limits its practical applications.Color-transferbased FPM(CFPM)has emerged as a potential solution,theoretically reducing both acquisition and reconstruction threefold time.Yet,existing methods fall short of achieving the desired reconstruction speed and colorization quality.In this study,we report a generalized dual-color-space constrained model for FPM colorization.This model provides a mathematical framework for model-based FPM colorization,enabling a closed-form solution without the need for redundant iterative calculations.Our approach,termed generalized CFPM(gCFPM),achieves colorization within seconds for megapixel-scale images,delivering superior colorization quality in terms of both colorfulness and sharpness,along with an extended DOF.Both simulations and experiments demonstrate that gCFPM surpasses state-of-the-art methods across all evaluated criteria.Our work offers a robust and comprehensive workflow for high-throughput full-color pathological imaging using FPM platforms,laying a solid foundation for future advancements in methodology and engineering.展开更多
Let f be a primitive holomorphic cusp form with even integral weight k≥2 for the full modular groupΓ=SL(2,Z)andλ_(sym^(j)f)(n)be the n-th coefficient of Dirichlet series of j-th symmetric L-function L(s,sym^(j)f)at...Let f be a primitive holomorphic cusp form with even integral weight k≥2 for the full modular groupΓ=SL(2,Z)andλ_(sym^(j)f)(n)be the n-th coefficient of Dirichlet series of j-th symmetric L-function L(s,sym^(j)f)attached to f.In this paper,we study the mean value distribution over a specific sparse sequence of positive integers of the following sum∑(a^(2)+b^(2)+c^(2)+d^(2)≤x(a,b,c,d)∈Z^(4))λ_(sym^(j))^(i)f(a^(2)+b^(2)+c^(2)+d^(2))where j≥2 is a given positive integer,i=2,3,4 andαis sufficiently large.We utilize Python programming to design algorithms for higher power conditions,combining Perron's formula,latest results of representations of natural integers as sums of squares,as well as analytic properties and subconvexity and convexity bounds of automorphic L-functions,to ensure the accuracy and verifiability of asymptotic formulas.The conclusion we obtained improves previous results and extends them to a more general settings.展开更多
Fourier Ptychographic Microscopy(FPM)is a high-throughput computational optical imaging technology reported in 2013.It effectively breaks through the trade-off between high-resolution imaging and wide-field imaging.In...Fourier Ptychographic Microscopy(FPM)is a high-throughput computational optical imaging technology reported in 2013.It effectively breaks through the trade-off between high-resolution imaging and wide-field imaging.In recent years,it has been found that FPM is not only a tool to break through the trade-off between field of view and spatial resolution,but also a paradigm to break through those trade-off problems,thus attracting extensive attention.Compared with previous reviews,this review does not introduce its concept,basic principles,optical system and series of applications once again,but focuses on elaborating the three major difficulties faced by FPM technology in the process from“looking good”in the laboratory to“working well”in practical applications:mismatch between numerical model and physical reality,long reconstruction time and high computing power demand,and lack of multi-modal expansion.It introduces how to achieve key technological innovations in FPM through the dual drive of Artificial Intelligence(AI)and physics,including intelligent reconstruction algorithms introducing machine learning concepts,optical-algorithm co-design,fusion of frequency domain extrapolation methods and generative adversarial networks,multi-modal imaging schemes and data fusion enhancement,etc.,gradually solving the difficulties of FPM technology.Conversely,this review deeply considers the unique value of FPM technology in potentially feeding back to the development of“AI+optics”,such as providing AI benchmark tests under physical constraints,inspirations for the balance of computing power and bandwidth in miniaturized intelligent microscopes,and photoelectric hybrid architectures.Finally,it introduces the industrialization path and frontier directions of FPM technology,pointing out that with the promotion of the dual drive of AI and physics,it will generate a large number of industrial application case,and looks forward to the possibilities of future application scenarios and expansions,for instance,body fluid biopsy and point-of-care testing at the grassroots level represent the expansion of the growth market.展开更多
The response and performance of radiation detectors for accurate measurements and effective use for radiological safety in medical, industrial, and nuclear sectors are based on the optimal use, maintenance, repair and...The response and performance of radiation detectors for accurate measurements and effective use for radiological safety in medical, industrial, and nuclear sectors are based on the optimal use, maintenance, repair and calibration of radiation monitoring instruments in a secondary standard dosimetry laboratory. In Nigeria, the suboptimal performances of these instruments are attributed to inadequate maintenance practices, insufficient calibration, and limited awareness of proper equipment handling for optimal use. This study assesses the current practices related to the optimal use, maintenance, repair, and calibration of radiation detection equipment across Nigeria’s six geopolitical zones. Using a cross-sectional survey approach, data were collected from Ninety (90) radiation monitoring equipment operators, Radiation Safety Officers, and frontline responders to evaluate their knowledge, awareness, and practices concerning equipment usage, operation, storage, handling, and calibration. The findings reveal significant gaps in knowledge of usage (trained is 43.2%, not trained is 56.8%) and inconsistencies in maintenance practices (as indicated by the regression analysis (β = 0.51, p < 0.01), particularly regarding specialized instruments such as the PackEye, Mobile Detection System (MDS), Radionuclide Identifinder (RID), and Personal Radiation Detectors (PRD). While there is high awareness of the need for regular calibration and handling training, the lack of standardized protocols and training alignment poses challenges to the effective use of these instruments. This study underscores the importance of comprehensive training programs, standardized maintenance protocols, and enhanced awareness initiatives to optimize the usage, performance and safety of radiation monitoring instruments in Nigeria.展开更多
Objective:To evaluate the effectiveness of quality nursing in the management of reusable instruments in the Central Sterile Supply Department(CSSD).Methods:Eleven nurses from the CSSD department were selected from Jan...Objective:To evaluate the effectiveness of quality nursing in the management of reusable instruments in the Central Sterile Supply Department(CSSD).Methods:Eleven nurses from the CSSD department were selected from January to October 2024,and quality nursing activities were implemented in the management of reusable instruments.The completion of quality indicators was analyzed.The instrument quality management scores,department satisfaction,and nurses’professional ability scores before and after nursing management were compared.Results:After nursing intervention,the qualified rates of initial cleaning and final cleaning of sterilization instruments were 99.66%and 100%,respectively.The qualified rate of packaging was 99.97%,the wet package rate was 0.1‰,the loading qualified rate was 99.88%,and the qualified rate of distribution was 99.99%.After nursing intervention,the nurses’instrument quality management scores,department satisfaction,and nurses’professional ability scores were all higher than those before nursing intervention(P<0.05).Conclusion:Quality nursing activities can improve the cleaning,packaging,and sterilization qualified rates of reusable instruments in the CSSD,enhance the effect of instrument quality management,obtain higher department satisfaction from nurses,cultivate their professional abilities,and possess significant nursing management advantages.展开更多
This paper introduces the key design aspects of automotive center console instrument systems,including hardware architecture,ergonomics,antenna layout,etc.It elaborates on the application and advantages of various adv...This paper introduces the key design aspects of automotive center console instrument systems,including hardware architecture,ergonomics,antenna layout,etc.It elaborates on the application and advantages of various advanced technologies,such as 3D printing and dual-color injection molding.Additionally,it discusses advancements in structural design,as well as future challenges and the trend of multidisciplinary collaborative innovation.展开更多
We present the Fourier lightfield multiview stereoscope(FiLM-Scope).This imaging device combines concepts from Fourier lightfield microscopy and multiview stereo imaging to capture high-resolution 3D videos over large...We present the Fourier lightfield multiview stereoscope(FiLM-Scope).This imaging device combines concepts from Fourier lightfield microscopy and multiview stereo imaging to capture high-resolution 3D videos over large fields of view.The FiLM-Scope optical hardware consists of a multicamera array,with 48 individual microcameras,placed behind a high-throughput primary lens.This allows the FiLM-Scope to simultaneously capture 48 unique 12.8 megapixel images of a 28×37 mm field-of-view,from unique angular perspectives over a 21 deg×29 deg range,with down to 22μm lateral resolution.We also describe a self-supervised algorithm to reconstruct 3D height maps from these images.Our approach demonstrates height accuracy down to 11μm.To showcase the utility of our system,we perform tool tracking over the surface of an ex vivo rat skull and visualize the 3D deformation in stretching human skin,with videos captured at up to 100 frames per second.The FiLM-Scope has the potential to improve 3D visualization in a range of microsurgical settings.展开更多
In oceanic and atmospheric science,finer resolutions have become a prevailing trend in all aspects of development.For high-resolution fluid flow simulations,the computational costs of widely used numerical models incr...In oceanic and atmospheric science,finer resolutions have become a prevailing trend in all aspects of development.For high-resolution fluid flow simulations,the computational costs of widely used numerical models increase significantly with the resolution.Artificial intelligence methods have attracted increasing attention because of their high precision and fast computing speeds compared with traditional numerical model methods.The resolution-independent Fourier neural operator(FNO)presents a promising solution to the still challenging problem of high-resolution fluid flow simulations based on low-resolution data.Accordingly,we assess the potential of FNO for high-resolution fluid flow simulations using the vorticity equation as an example.We assess and compare the performance of FNO in multiple high-resolution tests varying the amounts of data and the evolution durations.When assessed with finer resolution data(even up to number of grid points with 1280×1280),the FNO model,trained at low resolution(number of grid points with 64×64)and with limited data,exhibits a stable overall error and good accuracy.Additionally,our work demonstrates that the FNO model takes less time than the traditional numerical method for high-resolution simulations.This suggests that FNO has the prospect of becoming a cost-effective and highly precise model for high-resolution simulations in the future.Moreover,FNO can make longer high-resolution predictions while training with less data by superimposing vorticity fields from previous time steps as input.A suitable initial learning rate can be set according to the frequency principle,and the time intervals of the dataset need to be adjusted according to the spatial resolution of the input when training the FNO model.Our findings can help optimize FNO for future fluid flow simulations.展开更多
Quantum information masking(QIM)is a crucial technique for protecting quantum data from being accessed by local subsystems.In this paper,we introduce a novel method for achieving1-uniform QIM in multipartite systems u...Quantum information masking(QIM)is a crucial technique for protecting quantum data from being accessed by local subsystems.In this paper,we introduce a novel method for achieving1-uniform QIM in multipartite systems utilizing a Fourier matrix.We further extend this approach to construct an orthogonal array with the aid of a Hadamard matrix,which is a specific type of Fourier matrix.This allows us to explore the relationship between 2-uniform QIM and orthogonal arrays.Through this framework,we derive two distinct 2-uniform quantum states,enabling the 2-uniform masking of original information within multipartite systems.Furthermore,we prove that the maximum number of quantum bits required for achieving a2-uniformly masked state is 2^(n)-1,and the minimum is 2^(n-1)+3.Moreover,our scheme effectively demonstrates the rich quantum correlations between multipartite systems and has potential application value in quantum secret sharing.展开更多
The aim of this paper is to price power option with its underlying asset price following exponential normal inverse gaussian(NIG)process.We first find the risk neutral equivalent martingale measure Q by Esscher transf...The aim of this paper is to price power option with its underlying asset price following exponential normal inverse gaussian(NIG)process.We first find the risk neutral equivalent martingale measure Q by Esscher transform.Then,using the Fourier transform and its inverse,we derive the analytical pricing formulas of power options which are expressed in the form of Fourier integral.In addition,the fast Fourier transform(FFT)algorithm is applied to calculate these pricing formulas.Finally,Shangzheng 50ETF options are chosen to test our results.Estimating the parameters in NIG process by maximum likelihood method,we show that the NIG prices are much closer to market prices than the Black-Scholes-Merton(BSM)ones.展开更多
The capacity to diagnose faults in rolling bearings is of significant practical importance to ensure the normal operation of the equipment.Frequency-domain features can effectively enhance the identification of fault ...The capacity to diagnose faults in rolling bearings is of significant practical importance to ensure the normal operation of the equipment.Frequency-domain features can effectively enhance the identification of fault modes.However,existing methods often suffer from insufficient frequency-domain representation in practical applications,which greatly affects diagnostic performance.Therefore,this paper proposes a rolling bearing fault diagnosismethod based on aMulti-Scale FusionNetwork(MSFN)using the Time-Division Fourier Transform(TDFT).The method constructs multi-scale channels to extract time-domain and frequency-domain features of the signal in parallel.A multi-level,multi-scale filter-based approach is designed to extract frequency-domain features in a segmented manner.A cross-attention mechanism is introduced to facilitate the fusion of the extracted time-frequency domain features.The performance of the proposed method is validated using the CWRU and Ottawa datasets.The results show that the average accuracy of MSFN under complex noisy signals is 97.75%and 94.41%.The average accuracy under variable load conditions is 98.68%.This demonstrates its significant application potential compared to existing methods.展开更多
Fourier ptychographic microscopy(FPM)is an innovative computational microscopy approach that enables high-throughput imaging with high resolution,wide field of view,and quantitative phase imaging(QPI)by simultaneously...Fourier ptychographic microscopy(FPM)is an innovative computational microscopy approach that enables high-throughput imaging with high resolution,wide field of view,and quantitative phase imaging(QPI)by simultaneously capturing bright-field and dark-field images.However,effectively utilizing dark-field intensity images,including both normally exposed and overexposed data,which contain valuable high-angle illumination information,remains a complex challenge.Successfully extracting and applying this information could significantly enhance phase reconstruction,benefiting processes such as virtual staining and QPI imaging.To address this,we introduce a multi-exposure image fusion(MEIF)framework that optimizes dark-field information by incorporating it into the FPM preprocessing workflow.MEIF increases the data available for reconstruction without requiring changes to the optical setup.We evaluate the framework using both feature-domain and traditional FPM,demonstrating that it achieves substantial improvements in intensity resolution and phase information for biological samples that exceed the performance of conventional high dynamic range(HDR)methods.This image preprocessing-based information-maximization strategy fully leverages existing datasets and offers promising potential to drive advancements in fields such as microscopy,remote sensing,and crystallography.展开更多
With the rapid development of the nuclear power industry on a global scale,the discharge of radioactive e uents from nuclear power plants and their impact on the environment have become important issues in radioactive...With the rapid development of the nuclear power industry on a global scale,the discharge of radioactive e uents from nuclear power plants and their impact on the environment have become important issues in radioactive waste management,radiation protection,and environmental impact assessments.-detection of nuclides requires tedious processes,such as waiting for the radioactive balance of the sample and pretreatment separation,and there is an urgent need for a method specifically designed for mixing rapid energy spectrum measurement method for nuclide samples.The analysis of hybrid-energy spectrum is proposed in this study as a new algorithm,which takes advantage of the spectral analysis of-logarithmic energy spectrum and fitting ability of Fourier series.The logarithmic energy spectrum is obtained by logarithmic conversion of the hybrid linear energy spectrum.The Fourier fitting interpolation method is used to fit the logarithmic energy spectrum numerically.Next,the interpolation points for the‘e ective high-energy window’and‘e ective low-energy window’corresponding to the highest E_(m)nuclide in the hybrid logarithmic fitted energy spectrum are set,and spline interpolation is performed three times to obtain the logarithmic fitted energy spectrum of the highest E_(m)nuclide.Finally,the logarithmic fitted spectrum of the highest E_(m)nuclide is subtracted from the hybrid logarithmic fitted spectrum to obtain a logarithmic fitted spectrum comprised of the remaining lower E_(m)nuclides.The aforementioned process is iterated in a loop to resolve the logarithmic spectra of each nuclide in the original hybrid logarithmic spectra.Then,the radioactivity of E_(m)nuclides to be measured is calculated.In the experimental tests,^(14)C,^(90)Sr,and ^(90)Y spectra,which are obtained using the Fourier fitting interpolation method are compared with the original simulated ^(14)C,^(90)Sr,and ^(90)Y spectra of GEANT4.The measured liquid scintillator data of ^(90)Sr∕^(90)Y sample source and simulated data from GEANT4 are then analyzed.Analysis of the experimental results indicates that the Fourier fitting interpolation method accurately solves ^(14)C,^(90)Sr,and ^(90)Y energy spectra,which is in good agreement with the original GEANT4 simulation.The error in ^(90)Y activity,calculated using the actual detection e ciency,is less than 10%and less than 5%when using the simulated full-spectrum detection e ciency,satisfying the experimental expectations.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12104500 and 82430062)the Key Research and Development Projects of Shaanxi Province(Grant No.2023-YBSF-263),the Shenzhen Engineering Research Centre(Grant No.XMHT20230115004)the Shenzhen Science and Technology Innovation Commission(Grant No.KCXFZ20201221173207022).
文摘Full-color imaging is essential in digital pathology for accurate tissue analysis.Utilizing advanced optical modulation and phase retrieval algorithms,Fourier ptychographic microscopy(FPM)offers a powerful solution for high-throughput digital pathology,combining high resolution,large field of view,and extended depth of field(DOF).However,the full-color capabilities of FPM are hindered by coherent color artifacts and reduced computational efficiency,which significantly limits its practical applications.Color-transferbased FPM(CFPM)has emerged as a potential solution,theoretically reducing both acquisition and reconstruction threefold time.Yet,existing methods fall short of achieving the desired reconstruction speed and colorization quality.In this study,we report a generalized dual-color-space constrained model for FPM colorization.This model provides a mathematical framework for model-based FPM colorization,enabling a closed-form solution without the need for redundant iterative calculations.Our approach,termed generalized CFPM(gCFPM),achieves colorization within seconds for megapixel-scale images,delivering superior colorization quality in terms of both colorfulness and sharpness,along with an extended DOF.Both simulations and experiments demonstrate that gCFPM surpasses state-of-the-art methods across all evaluated criteria.Our work offers a robust and comprehensive workflow for high-throughput full-color pathological imaging using FPM platforms,laying a solid foundation for future advancements in methodology and engineering.
文摘Let f be a primitive holomorphic cusp form with even integral weight k≥2 for the full modular groupΓ=SL(2,Z)andλ_(sym^(j)f)(n)be the n-th coefficient of Dirichlet series of j-th symmetric L-function L(s,sym^(j)f)attached to f.In this paper,we study the mean value distribution over a specific sparse sequence of positive integers of the following sum∑(a^(2)+b^(2)+c^(2)+d^(2)≤x(a,b,c,d)∈Z^(4))λ_(sym^(j))^(i)f(a^(2)+b^(2)+c^(2)+d^(2))where j≥2 is a given positive integer,i=2,3,4 andαis sufficiently large.We utilize Python programming to design algorithms for higher power conditions,combining Perron's formula,latest results of representations of natural integers as sums of squares,as well as analytic properties and subconvexity and convexity bounds of automorphic L-functions,to ensure the accuracy and verifiability of asymptotic formulas.The conclusion we obtained improves previous results and extends them to a more general settings.
基金National Natural Science Foundation of China(No.12574332)the Space Optoelectronic Measurement and Perception Lab.,Beijing Institute of Control Engineering(No.LabSOMP-2023-10)Major Science and Technology Innovation Program of Xianyang City(No.L2024-ZDKJ-ZDCGZH-0021)。
文摘Fourier Ptychographic Microscopy(FPM)is a high-throughput computational optical imaging technology reported in 2013.It effectively breaks through the trade-off between high-resolution imaging and wide-field imaging.In recent years,it has been found that FPM is not only a tool to break through the trade-off between field of view and spatial resolution,but also a paradigm to break through those trade-off problems,thus attracting extensive attention.Compared with previous reviews,this review does not introduce its concept,basic principles,optical system and series of applications once again,but focuses on elaborating the three major difficulties faced by FPM technology in the process from“looking good”in the laboratory to“working well”in practical applications:mismatch between numerical model and physical reality,long reconstruction time and high computing power demand,and lack of multi-modal expansion.It introduces how to achieve key technological innovations in FPM through the dual drive of Artificial Intelligence(AI)and physics,including intelligent reconstruction algorithms introducing machine learning concepts,optical-algorithm co-design,fusion of frequency domain extrapolation methods and generative adversarial networks,multi-modal imaging schemes and data fusion enhancement,etc.,gradually solving the difficulties of FPM technology.Conversely,this review deeply considers the unique value of FPM technology in potentially feeding back to the development of“AI+optics”,such as providing AI benchmark tests under physical constraints,inspirations for the balance of computing power and bandwidth in miniaturized intelligent microscopes,and photoelectric hybrid architectures.Finally,it introduces the industrialization path and frontier directions of FPM technology,pointing out that with the promotion of the dual drive of AI and physics,it will generate a large number of industrial application case,and looks forward to the possibilities of future application scenarios and expansions,for instance,body fluid biopsy and point-of-care testing at the grassroots level represent the expansion of the growth market.
文摘The response and performance of radiation detectors for accurate measurements and effective use for radiological safety in medical, industrial, and nuclear sectors are based on the optimal use, maintenance, repair and calibration of radiation monitoring instruments in a secondary standard dosimetry laboratory. In Nigeria, the suboptimal performances of these instruments are attributed to inadequate maintenance practices, insufficient calibration, and limited awareness of proper equipment handling for optimal use. This study assesses the current practices related to the optimal use, maintenance, repair, and calibration of radiation detection equipment across Nigeria’s six geopolitical zones. Using a cross-sectional survey approach, data were collected from Ninety (90) radiation monitoring equipment operators, Radiation Safety Officers, and frontline responders to evaluate their knowledge, awareness, and practices concerning equipment usage, operation, storage, handling, and calibration. The findings reveal significant gaps in knowledge of usage (trained is 43.2%, not trained is 56.8%) and inconsistencies in maintenance practices (as indicated by the regression analysis (β = 0.51, p < 0.01), particularly regarding specialized instruments such as the PackEye, Mobile Detection System (MDS), Radionuclide Identifinder (RID), and Personal Radiation Detectors (PRD). While there is high awareness of the need for regular calibration and handling training, the lack of standardized protocols and training alignment poses challenges to the effective use of these instruments. This study underscores the importance of comprehensive training programs, standardized maintenance protocols, and enhanced awareness initiatives to optimize the usage, performance and safety of radiation monitoring instruments in Nigeria.
文摘Objective:To evaluate the effectiveness of quality nursing in the management of reusable instruments in the Central Sterile Supply Department(CSSD).Methods:Eleven nurses from the CSSD department were selected from January to October 2024,and quality nursing activities were implemented in the management of reusable instruments.The completion of quality indicators was analyzed.The instrument quality management scores,department satisfaction,and nurses’professional ability scores before and after nursing management were compared.Results:After nursing intervention,the qualified rates of initial cleaning and final cleaning of sterilization instruments were 99.66%and 100%,respectively.The qualified rate of packaging was 99.97%,the wet package rate was 0.1‰,the loading qualified rate was 99.88%,and the qualified rate of distribution was 99.99%.After nursing intervention,the nurses’instrument quality management scores,department satisfaction,and nurses’professional ability scores were all higher than those before nursing intervention(P<0.05).Conclusion:Quality nursing activities can improve the cleaning,packaging,and sterilization qualified rates of reusable instruments in the CSSD,enhance the effect of instrument quality management,obtain higher department satisfaction from nurses,cultivate their professional abilities,and possess significant nursing management advantages.
文摘This paper introduces the key design aspects of automotive center console instrument systems,including hardware architecture,ergonomics,antenna layout,etc.It elaborates on the application and advantages of various advanced technologies,such as 3D printing and dual-color injection molding.Additionally,it discusses advancements in structural design,as well as future challenges and the trend of multidisciplinary collaborative innovation.
基金supported by the National Cancer Institute(NCI)of the National Institutes of Health(Grant No.R44CA250877)the Office of Research Infrastructure Programs(ORIP),Office of the Director,National Institutes of Health,and the National Institute of Environmental Health Sciences(NIEHS)of the National Institutes of Health(Grant No.R44OD024879)+2 种基金the National Institute of Biomedical Imaging and Bioengineering(NIBIB)of the National Institutes of Health(Grant No.R43EB030979)the National Science Foundation(Grant Nos.2036439 and 2238845)the Duke Coulter Translational Part-nership Award,the Fitzpatrick Institute at the Duke University.
文摘We present the Fourier lightfield multiview stereoscope(FiLM-Scope).This imaging device combines concepts from Fourier lightfield microscopy and multiview stereo imaging to capture high-resolution 3D videos over large fields of view.The FiLM-Scope optical hardware consists of a multicamera array,with 48 individual microcameras,placed behind a high-throughput primary lens.This allows the FiLM-Scope to simultaneously capture 48 unique 12.8 megapixel images of a 28×37 mm field-of-view,from unique angular perspectives over a 21 deg×29 deg range,with down to 22μm lateral resolution.We also describe a self-supervised algorithm to reconstruct 3D height maps from these images.Our approach demonstrates height accuracy down to 11μm.To showcase the utility of our system,we perform tool tracking over the surface of an ex vivo rat skull and visualize the 3D deformation in stretching human skin,with videos captured at up to 100 frames per second.The FiLM-Scope has the potential to improve 3D visualization in a range of microsurgical settings.
基金The National Natural Science Foundation of China under contract No.42425606the Basic Scientific Fund for the National Public Research Institute of China(Shu-Xingbei Young Talent Program)under contract No.2023S01+1 种基金the Ocean Decade International Cooperation Center Scientific and Technological Cooperation Project under contract No.GHKJ2024005China-Korea Joint Ocean Research Center Project under contract Nos PI-20240101(China)and 20220407(Korea).
文摘In oceanic and atmospheric science,finer resolutions have become a prevailing trend in all aspects of development.For high-resolution fluid flow simulations,the computational costs of widely used numerical models increase significantly with the resolution.Artificial intelligence methods have attracted increasing attention because of their high precision and fast computing speeds compared with traditional numerical model methods.The resolution-independent Fourier neural operator(FNO)presents a promising solution to the still challenging problem of high-resolution fluid flow simulations based on low-resolution data.Accordingly,we assess the potential of FNO for high-resolution fluid flow simulations using the vorticity equation as an example.We assess and compare the performance of FNO in multiple high-resolution tests varying the amounts of data and the evolution durations.When assessed with finer resolution data(even up to number of grid points with 1280×1280),the FNO model,trained at low resolution(number of grid points with 64×64)and with limited data,exhibits a stable overall error and good accuracy.Additionally,our work demonstrates that the FNO model takes less time than the traditional numerical method for high-resolution simulations.This suggests that FNO has the prospect of becoming a cost-effective and highly precise model for high-resolution simulations in the future.Moreover,FNO can make longer high-resolution predictions while training with less data by superimposing vorticity fields from previous time steps as input.A suitable initial learning rate can be set according to the frequency principle,and the time intervals of the dataset need to be adjusted according to the spatial resolution of the input when training the FNO model.Our findings can help optimize FNO for future fluid flow simulations.
基金supported by the National Natural Science Foundation of China under Grant No.12301590Natural Science Foundation of Hebei Province under Grant No.A2022210002。
文摘Quantum information masking(QIM)is a crucial technique for protecting quantum data from being accessed by local subsystems.In this paper,we introduce a novel method for achieving1-uniform QIM in multipartite systems utilizing a Fourier matrix.We further extend this approach to construct an orthogonal array with the aid of a Hadamard matrix,which is a specific type of Fourier matrix.This allows us to explore the relationship between 2-uniform QIM and orthogonal arrays.Through this framework,we derive two distinct 2-uniform quantum states,enabling the 2-uniform masking of original information within multipartite systems.Furthermore,we prove that the maximum number of quantum bits required for achieving a2-uniformly masked state is 2^(n)-1,and the minimum is 2^(n-1)+3.Moreover,our scheme effectively demonstrates the rich quantum correlations between multipartite systems and has potential application value in quantum secret sharing.
基金Supported by National Natural Science Foundation of China(11571089,11501164)Natural Science Founda-tion of Hebei Province(A2019205299)+1 种基金the Foundation of Hebei Education Department(ZD2018065,ZD2019053)Hebei Normal University(L2019Z01).
文摘The aim of this paper is to price power option with its underlying asset price following exponential normal inverse gaussian(NIG)process.We first find the risk neutral equivalent martingale measure Q by Esscher transform.Then,using the Fourier transform and its inverse,we derive the analytical pricing formulas of power options which are expressed in the form of Fourier integral.In addition,the fast Fourier transform(FFT)algorithm is applied to calculate these pricing formulas.Finally,Shangzheng 50ETF options are chosen to test our results.Estimating the parameters in NIG process by maximum likelihood method,we show that the NIG prices are much closer to market prices than the Black-Scholes-Merton(BSM)ones.
基金fully supported by the Frontier Exploration Projects of Longmen Laboratory(No.LMQYTSKT034)Key Research and Development and Promotion of Special(Science and Technology)Project of Henan Province,China(No.252102210158)。
文摘The capacity to diagnose faults in rolling bearings is of significant practical importance to ensure the normal operation of the equipment.Frequency-domain features can effectively enhance the identification of fault modes.However,existing methods often suffer from insufficient frequency-domain representation in practical applications,which greatly affects diagnostic performance.Therefore,this paper proposes a rolling bearing fault diagnosismethod based on aMulti-Scale FusionNetwork(MSFN)using the Time-Division Fourier Transform(TDFT).The method constructs multi-scale channels to extract time-domain and frequency-domain features of the signal in parallel.A multi-level,multi-scale filter-based approach is designed to extract frequency-domain features in a segmented manner.A cross-attention mechanism is introduced to facilitate the fusion of the extracted time-frequency domain features.The performance of the proposed method is validated using the CWRU and Ottawa datasets.The results show that the average accuracy of MSFN under complex noisy signals is 97.75%and 94.41%.The average accuracy under variable load conditions is 98.68%.This demonstrates its significant application potential compared to existing methods.
基金supported by the National Natural Science Foundation of China(Grant No.12104500)the Key Research and Development Projects of Shaanxi Province of China(Grant No.2023-YBSF-263).
文摘Fourier ptychographic microscopy(FPM)is an innovative computational microscopy approach that enables high-throughput imaging with high resolution,wide field of view,and quantitative phase imaging(QPI)by simultaneously capturing bright-field and dark-field images.However,effectively utilizing dark-field intensity images,including both normally exposed and overexposed data,which contain valuable high-angle illumination information,remains a complex challenge.Successfully extracting and applying this information could significantly enhance phase reconstruction,benefiting processes such as virtual staining and QPI imaging.To address this,we introduce a multi-exposure image fusion(MEIF)framework that optimizes dark-field information by incorporating it into the FPM preprocessing workflow.MEIF increases the data available for reconstruction without requiring changes to the optical setup.We evaluate the framework using both feature-domain and traditional FPM,demonstrating that it achieves substantial improvements in intensity resolution and phase information for biological samples that exceed the performance of conventional high dynamic range(HDR)methods.This image preprocessing-based information-maximization strategy fully leverages existing datasets and offers promising potential to drive advancements in fields such as microscopy,remote sensing,and crystallography.
基金supported by the National Natural Science Foundation of China(No.12005026)。
文摘With the rapid development of the nuclear power industry on a global scale,the discharge of radioactive e uents from nuclear power plants and their impact on the environment have become important issues in radioactive waste management,radiation protection,and environmental impact assessments.-detection of nuclides requires tedious processes,such as waiting for the radioactive balance of the sample and pretreatment separation,and there is an urgent need for a method specifically designed for mixing rapid energy spectrum measurement method for nuclide samples.The analysis of hybrid-energy spectrum is proposed in this study as a new algorithm,which takes advantage of the spectral analysis of-logarithmic energy spectrum and fitting ability of Fourier series.The logarithmic energy spectrum is obtained by logarithmic conversion of the hybrid linear energy spectrum.The Fourier fitting interpolation method is used to fit the logarithmic energy spectrum numerically.Next,the interpolation points for the‘e ective high-energy window’and‘e ective low-energy window’corresponding to the highest E_(m)nuclide in the hybrid logarithmic fitted energy spectrum are set,and spline interpolation is performed three times to obtain the logarithmic fitted energy spectrum of the highest E_(m)nuclide.Finally,the logarithmic fitted spectrum of the highest E_(m)nuclide is subtracted from the hybrid logarithmic fitted spectrum to obtain a logarithmic fitted spectrum comprised of the remaining lower E_(m)nuclides.The aforementioned process is iterated in a loop to resolve the logarithmic spectra of each nuclide in the original hybrid logarithmic spectra.Then,the radioactivity of E_(m)nuclides to be measured is calculated.In the experimental tests,^(14)C,^(90)Sr,and ^(90)Y spectra,which are obtained using the Fourier fitting interpolation method are compared with the original simulated ^(14)C,^(90)Sr,and ^(90)Y spectra of GEANT4.The measured liquid scintillator data of ^(90)Sr∕^(90)Y sample source and simulated data from GEANT4 are then analyzed.Analysis of the experimental results indicates that the Fourier fitting interpolation method accurately solves ^(14)C,^(90)Sr,and ^(90)Y energy spectra,which is in good agreement with the original GEANT4 simulation.The error in ^(90)Y activity,calculated using the actual detection e ciency,is less than 10%and less than 5%when using the simulated full-spectrum detection e ciency,satisfying the experimental expectations.
