Quantum computing has the potential to solve complex problems that are inefficiently handled by classical computation.However,the high sensitivity of qubits to environmental interference and the high error rates in cu...Quantum computing has the potential to solve complex problems that are inefficiently handled by classical computation.However,the high sensitivity of qubits to environmental interference and the high error rates in current quantum devices exceed the error correction thresholds required for effective algorithm execution.Therefore,quantum error correction technology is crucial to achieving reliable quantum computing.In this work,we study a topological surface code with a two-dimensional lattice structure that protects quantum information by introducing redundancy across multiple qubits and using syndrome qubits to detect and correct errors.However,errors can occur not only in data qubits but also in syndrome qubits,and different types of errors may generate the same syndromes,complicating the decoding task and creating a need for more efficient decoding methods.To address this challenge,we used a transformer decoder based on an attention mechanism.By mapping the surface code lattice,the decoder performs a self-attention process on all input syndromes,thereby obtaining a global receptive field.The performance of the decoder was evaluated under a phenomenological error model.Numerical results demonstrate that the decoder achieved a decoding accuracy of 93.8%.Additionally,we obtained decoding thresholds of 5%and 6.05%at maximum code distances of 7 and 9,respectively.These results indicate that the decoder used demonstrates a certain capability in correcting noise errors in surface codes.展开更多
Quantum error correction is essential for realizing fault-tolerant quantum computing,where both the efficiency and accuracy of the decoding algorithms play critical roles.In this work,we introduce the implementation o...Quantum error correction is essential for realizing fault-tolerant quantum computing,where both the efficiency and accuracy of the decoding algorithms play critical roles.In this work,we introduce the implementation of the PLANAR algorithm,a software framework designed for fast and exact decoding of quantum codes with a planar structure.The algorithm first converts the optimal decoding of quantum codes into a partition function computation problem of an Ising spin glass model.Then it utilizes the exact Kac–Ward formula to solve it.In this way,PLANAR offers the exact maximum likelihood decoding in polynomial complexity for quantum codes with a planar structure,including the surface code with independent code-capacity noise and the quantum repetition code with circuit-level noise.Unlike traditional minimumweight decoders such as minimum-weight perfect matching(MWPM),PLANAR achieves theoretically optimal performance while maintaining polynomial-time efficiency.In addition,to demonstrate its capabilities,we exemplify the implementation using the rotated surface code,a commonly used quantum error correction code with a planar structure,and show that PLANAR achieves a threshold of approximately p_(uc)≈0.109 under the depolarizing error model,with a time complexity scaling of O(N^(0.69)),where N is the number of spins in the Ising model.展开更多
The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM pro...The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM probe loading and positioning has yet to be subjected to comprehensive investigation.This paper proposes a novel bending-test method based on sequential loading points,in which a series of evenly distributed loads are applied along the length of the central axis on the upper surface of the cantilever.The preliminary measured values of Young’s modulus for an unknown alloy material were 193,178,and 176 GPa,exhibiting a considerable degree of dispersion.An algorithm for self-correction of the positioning error was developed,and this resulted in a positioning error of 53 nm and a final converged Young’s modulus of 161 GPa.展开更多
Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the int...Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the intensity of summer precipitation is often largely underestimated in many current dynamic models.This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)method.Using the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model predictions.This study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.展开更多
Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronar...Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image classification.Image denoising is done by a U-Net architecture that ensures effective image denoising.Attenuation correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of classification.Finally,a novel multi-scale diluted convolution(MSDC)network is proposed.It merges the features extracted in different scales and makes the model learn the features more efficiently.Three scales of filters with size 3×3 are used to extract features.All three steps are compared with state-of-the-art methods.The proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of 39.7.The proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.展开更多
Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting ...Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.展开更多
The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmosphe...The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.展开更多
BACKGROUND Transcatheter arterial chemoembolization(TACE)is a key treatment approach for advanced invasive liver cancer(infiltrative hepatocellular carcinoma).However,its therapeutic response can be difficult to evalu...BACKGROUND Transcatheter arterial chemoembolization(TACE)is a key treatment approach for advanced invasive liver cancer(infiltrative hepatocellular carcinoma).However,its therapeutic response can be difficult to evaluate accurately using conventional two-dimensional imaging criteria due to the tumor’s diffuse and multifocal growth pattern.Volumetric imaging,especially enhanced tumor volume(ETV),offers a more comprehensive assessment.Nonetheless,bias field inhomogeneity in magnetic resonance imaging(MRI)poses challenges,potentially skewing volumetric measurements and undermining prognostic evaluation.AIM To investigate whether MRI bias field correction enhances the accuracy of volumetric assessment of infiltrative hepatocellular carcinoma treated with TACE,and to analyze how this improved measurement impacts prognostic prediction.METHODS We retrospectively collected data from 105 patients with invasive liver cancer who underwent TACE treatment at the Affiliated Hospital of Xuzhou Medical University from January 2020 to January 2024.The improved N4 bias field correction algorithm was applied to process MRI images,and the ETV before and after treatment was calculated.The ETV measurements before and after correction were compared,and their relationship with patient prognosis was analyzed.A Cox proportional hazards model was used to evaluate prognostic factors,with Martingale residual analysis determining the optimal cutoff value,followed by survival analysis.RESULTS Bias field correction significantly affected ETV measurements,with the corrected baseline ETV mean(505.235 cm^(3))being significantly lower than before correction(825.632 cm^(3),P<0.001).Cox analysis showed that the hazard ratio(HR)for corrected baseline ETV(HR=1.165,95%CI:1.069-1.268)was higher than before correction(HR=1.063,95%CI:1.031-1.095).Using 412 cm^(3) as the cutoff,the group with baseline ETV<415 cm^(3) had a longer median survival time compared to the≥415 cm^(3) group(18.523 months vs 8.926 months,P<0.001).The group with an ETV reduction rate≥41%had better prognosis than the<41%group(17.862 months vs 9.235 months,P=0.006).Multivariate analysis confirmed that ETV reduction rate(HR=0.412,P<0.001),Child-Pugh classification(HR=0.298,P<0.001),and Barcelona Clinic Liver Cancer stage(HR=0.578,P=0.045)were independent prognostic factors.CONCLUSION Volume imaging based on MRI bias field correction can improve the accuracy of evaluating the efficacy of TACE treatment for invasive liver cancer.The corrected ETV and its reduction rate can serve as independent indicators for predicting patient prognosis,providing important reference for developing individualized treatment strategies.展开更多
Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination...Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.展开更多
Following the publication of Zeng et al.(2023),an inadvertent error was recently identified in Figure 1B and Supplementary Figure S3.To ensure the accuracy and integrity of our published work,we formally request a cor...Following the publication of Zeng et al.(2023),an inadvertent error was recently identified in Figure 1B and Supplementary Figure S3.To ensure the accuracy and integrity of our published work,we formally request a correction to address this issue and apologize for any confusion this error may have caused.For details,please refer to the modified Supplementary Materials.展开更多
Systematic bias is a type of model error that can affect the accuracy of data assimilation and forecasting that must be addressed.An online bias correction scheme called the sequential bias correction scheme(SBCS),was...Systematic bias is a type of model error that can affect the accuracy of data assimilation and forecasting that must be addressed.An online bias correction scheme called the sequential bias correction scheme(SBCS),was developed using the6 h average bias to correct the systematic bias during model integration.The primary purpose of this study is to investigate the impact of the SBCS in the high-resolution China Meteorological Administration Meso-scale(CMA-MESO)numerical weather prediction(NWP)model to reduce the systematic bias and to improve the data assimilation and forecast results through this method.The SBCS is improved upon and applied to the CMA-MESO 3-km model in this study.Four-week sequential data assimilation and forecast experiments,driven by rapid update and cycling(RUC),were conducted for the period from 2–29 May 2022.In terms of the characteristics of systematic bias,both the background and analysis show diurnal bias,and these large biases are affected by complex underlying surfaces(e.g.,oceans,coasts,and mountains).After the application of the SBCS,the results of the data assimilation show that the SBCS can reduce the systematic bias of the background and yield a neutral to slightly positive result for the analysis fields.In addition,the SBCS can reduce forecast errors and improve forecast results,especially for surface variables.The above results indicate that this scheme has good prospects for high-resolution regional NWP models.展开更多
For the quantum error correction and noisy intermediate-scale quantum algorithms to function with high efficiency,the raw fidelity of quantum logic gates on physical qubits needs to satisfy strict requirements.The neu...For the quantum error correction and noisy intermediate-scale quantum algorithms to function with high efficiency,the raw fidelity of quantum logic gates on physical qubits needs to satisfy strict requirements.The neutral atom quantum computing equipped with Rydberg blockade gates has made impressive progress recently,which makes it worthwhile to explore its potential in the two-qubit entangling gates,including the controlledphase gate,and in particular,the CZ gate.Provided the quantum coherence is well preserved,improving the fidelity of Rydberg blockade gates calls for special mechanisms to deal with adverse effects caused by realistic experimental conditions.Here,the heralded very-high-fidelity Rydberg blockade controlled-phase gate is designed to address these issues,which contains self-correction and projection as the key steps.This trailblazing method builds upon the previously established buffer-atom-mediated gate framework,with a special form of symmetry under parity–time transformation playing a crucial role in the process.We further analyze the performance with respect to a few typical sources of imperfections.This procedure can also be regarded as quantum hardware error correction or mitigation.While this paper by itself does not cover every single subtle issue and still contains many oversimplifications,we find it reasonable to anticipate a very-high-fidelity two-qubit quantum logic gate operated in the sense of heralded but probabilistic,whose gate error can be reduced to the level of 10^(-4)–10^(-6)or even lower with reasonably high possibilities.展开更多
Correction to:Nano-Micro Letters(2025)17:191 https://doi.org/10.1007/s40820-025-01702-7 Following the publication of the original article[1],the authors reported an error in Fig.3(b),and the figure legend was reversed...Correction to:Nano-Micro Letters(2025)17:191 https://doi.org/10.1007/s40820-025-01702-7 Following the publication of the original article[1],the authors reported an error in Fig.3(b),and the figure legend was reversed.The correct Fig.3 has been provided in this orrection.展开更多
The hot deformation behavior of as-extruded Ti-6554 alloy was investigated through isothermal compression at 700–950°C and 0.001–1 s^(−1).The temperature rise under different deformation conditions was calculat...The hot deformation behavior of as-extruded Ti-6554 alloy was investigated through isothermal compression at 700–950°C and 0.001–1 s^(−1).The temperature rise under different deformation conditions was calculated,and the curve was corrected.The strain compensation constitutive model of as-extruded Ti-6554 alloy based on temperature rise correction was established.The microstructure evolution under different conditions was analyzed,and the dynamic recrystallization(DRX)mechanism was revealed.The results show that the flow stress decreases with the increase in strain rate and the decrease in deformation temperature.The deformation temperature rise gradually increases with the increase in strain rate and the decrease in deformation temperature.At 700°C/1 s^(−1),the temperature rise reaches 100°C.The corrected curve value is higher than the measured value,and the strain compensation constitutive model has high prediction accuracy.The precipitation of theαphase occurs during deformation in the twophase region,which promotes DRX process of theβphase.At low strain rate,the volume fraction of dynamic recrystallization increases with the increase in deformation temperature.DRX mechanism includes continuous DRX and discontinuous DRX.展开更多
The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Cent...The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Center(EC model)from February to December in 2022 were used.Based on the data of the national intelligent grid forecast,the intelligent grid forecast of the regional bureau,EC model,etc.,temperature was predicted.According to the research of the grid point forecast synthesis algorithm with the highest accuracy rate in the recent three days,the temperature grid point correction was conducted in two forms of stations and grids.In order to reduce the deviation caused by the seasonal system temperature difference,a temperature prediction model was established by using the rolling forecast errors of 5,10,15,20,25 and 30 d as the basis data.The verification and evaluation of objective correction results show that the accuracy rate of temperature forecast by the intelligent grid of the regional bureau,the national intelligent grid,and EC model could be increased by 10%,8%,and 12%,respectively.展开更多
Correction to:Rare Met.https://doi.org/10.1007/s12598-021-01815-z In the original publication,Fig.5 was published with few mistakes.The correct version of Fig.5 is given in this correction.
Correction to:Nuclear Science and Techniques(2025)36:66 https://doi.org/10.1007/s41365-025-01662-y.In this article,the author’s name Hui-Ling Wei was incorrectly written as Hui-Ling We.The original article has been c...Correction to:Nuclear Science and Techniques(2025)36:66 https://doi.org/10.1007/s41365-025-01662-y.In this article,the author’s name Hui-Ling Wei was incorrectly written as Hui-Ling We.The original article has been corrected.展开更多
In this work,we apply tunneling formalism to analyze charged particles tunneling across a hairy black hole horizon.Such black hole solutions are essential for frameworks based on Horndeski's gravity theory.Applyin...In this work,we apply tunneling formalism to analyze charged particles tunneling across a hairy black hole horizon.Such black hole solutions are essential for frameworks based on Horndeski's gravity theory.Applying a semi-classical technique,we examine the tunneling of charged particles from a hairy black hole and derive the generic tunneling spectrum of released particles,ignoring self-gravitational and interaction.It is studied to ignore the back-reaction impact of the radiated particle on the hairy black hole.We analyze the properties of the black hole,such as temperature and entropy,under the influence of quantum gravity and also observe that the firstorder correction is present.We study tunneling radiation produced by a charged field equation in the presence of a generalized uncertainty effect.We modify the semi-classical technique by using the generalized uncertainty principle,the WKB approximation,and surface gravity.展开更多
Correction to:Nuclear Science and Techniques(2024)36:8 https://doi.org/10.1007/s41365-024-01570-7 In this article the affiliation details for Author Jian Shan were incorrectly given as‘College of Physics and Electron...Correction to:Nuclear Science and Techniques(2024)36:8 https://doi.org/10.1007/s41365-024-01570-7 In this article the affiliation details for Author Jian Shan were incorrectly given as‘College of Physics and Electronic Engi-neering,Hengyang Normal University,Hengyang 421008,China’but should have been‘School of Nuclear Science and Technology,University of South China,Hengyang 421001,China’.The original article has been corrected.展开更多
Correction to:Nuclear Science and Techniques(2024)35:162 https://doi.org/10.1007/s41365-024-01514-1 In this article,the citation information for Figures 6 and 7 was published incorrectly.The correct citations should r...Correction to:Nuclear Science and Techniques(2024)35:162 https://doi.org/10.1007/s41365-024-01514-1 In this article,the citation information for Figures 6 and 7 was published incorrectly.The correct citations should read as follows:In the sentence beginning‘the curve of Eq.17 is plotted…..’in this article,the text‘as shown in Fig.7a’should have read‘as shown in Fig.6a’.展开更多
基金Project supported by the Natural Science Foundation of Shandong Province,China(Grant No.ZR2021MF049)Joint Fund of Natural Science Foundation of Shandong Province(Grant Nos.ZR2022LLZ012 and ZR2021LLZ001)the Key R&D Program of Shandong Province,China(Grant No.2023CXGC010901)。
文摘Quantum computing has the potential to solve complex problems that are inefficiently handled by classical computation.However,the high sensitivity of qubits to environmental interference and the high error rates in current quantum devices exceed the error correction thresholds required for effective algorithm execution.Therefore,quantum error correction technology is crucial to achieving reliable quantum computing.In this work,we study a topological surface code with a two-dimensional lattice structure that protects quantum information by introducing redundancy across multiple qubits and using syndrome qubits to detect and correct errors.However,errors can occur not only in data qubits but also in syndrome qubits,and different types of errors may generate the same syndromes,complicating the decoding task and creating a need for more efficient decoding methods.To address this challenge,we used a transformer decoder based on an attention mechanism.By mapping the surface code lattice,the decoder performs a self-attention process on all input syndromes,thereby obtaining a global receptive field.The performance of the decoder was evaluated under a phenomenological error model.Numerical results demonstrate that the decoder achieved a decoding accuracy of 93.8%.Additionally,we obtained decoding thresholds of 5%and 6.05%at maximum code distances of 7 and 9,respectively.These results indicate that the decoder used demonstrates a certain capability in correcting noise errors in surface codes.
基金supported by the National Natural Science Foundation of China(Grant Nos.12325501,12047503,and 12247104)the Chinese Academy of Sciences(Grant No.ZDRW-XX-2022-3-02)P.Z.is partially supported by the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301900).
文摘Quantum error correction is essential for realizing fault-tolerant quantum computing,where both the efficiency and accuracy of the decoding algorithms play critical roles.In this work,we introduce the implementation of the PLANAR algorithm,a software framework designed for fast and exact decoding of quantum codes with a planar structure.The algorithm first converts the optimal decoding of quantum codes into a partition function computation problem of an Ising spin glass model.Then it utilizes the exact Kac–Ward formula to solve it.In this way,PLANAR offers the exact maximum likelihood decoding in polynomial complexity for quantum codes with a planar structure,including the surface code with independent code-capacity noise and the quantum repetition code with circuit-level noise.Unlike traditional minimumweight decoders such as minimum-weight perfect matching(MWPM),PLANAR achieves theoretically optimal performance while maintaining polynomial-time efficiency.In addition,to demonstrate its capabilities,we exemplify the implementation using the rotated surface code,a commonly used quantum error correction code with a planar structure,and show that PLANAR achieves a threshold of approximately p_(uc)≈0.109 under the depolarizing error model,with a time complexity scaling of O(N^(0.69)),where N is the number of spins in the Ising model.
文摘The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM probe loading and positioning has yet to be subjected to comprehensive investigation.This paper proposes a novel bending-test method based on sequential loading points,in which a series of evenly distributed loads are applied along the length of the central axis on the upper surface of the cantilever.The preliminary measured values of Young’s modulus for an unknown alloy material were 193,178,and 176 GPa,exhibiting a considerable degree of dispersion.An algorithm for self-correction of the positioning error was developed,and this resulted in a positioning error of 53 nm and a final converged Young’s modulus of 161 GPa.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608000)the National Natural Science Foundation of China(Grant No.42030605)+1 种基金CAAI-MindSpore Academic Fund Research Projects(CAAIXSJLJJ2023MindSpore11)the program of China Scholarships Council(No.CXXM2101180001)。
文摘Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the intensity of summer precipitation is often largely underestimated in many current dynamic models.This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)method.Using the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model predictions.This study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.
基金the Research Grant of Kwangwoon University in 2024.
文摘Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image classification.Image denoising is done by a U-Net architecture that ensures effective image denoising.Attenuation correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of classification.Finally,a novel multi-scale diluted convolution(MSDC)network is proposed.It merges the features extracted in different scales and makes the model learn the features more efficiently.Three scales of filters with size 3×3 are used to extract features.All three steps are compared with state-of-the-art methods.The proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of 39.7.The proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.
基金the Gansu Province Soft Scientific Research Projects(No.2015GS06516)the Funds for Distinguished Young Scientists of Lanzhou University of Technology,China(No.J201304)。
文摘Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.
基金supported by the National Natural Science Foundation of China(42304018)the National Natural Science Foundation of China(42330105,42064002,42074035)+3 种基金the Guangxi Natural Science Foundation of China(Guike AD23026177,2020GXNSFBA297145)the Foundation of Guilin University of Technology(GUTQDJJ6616032)Guangxi Key Laboratory of Spatial Information and Geomatics(21238-21-05)the Innovation Project of Guangxi Graduate Education(YCSW2023341)。
文摘The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.
文摘BACKGROUND Transcatheter arterial chemoembolization(TACE)is a key treatment approach for advanced invasive liver cancer(infiltrative hepatocellular carcinoma).However,its therapeutic response can be difficult to evaluate accurately using conventional two-dimensional imaging criteria due to the tumor’s diffuse and multifocal growth pattern.Volumetric imaging,especially enhanced tumor volume(ETV),offers a more comprehensive assessment.Nonetheless,bias field inhomogeneity in magnetic resonance imaging(MRI)poses challenges,potentially skewing volumetric measurements and undermining prognostic evaluation.AIM To investigate whether MRI bias field correction enhances the accuracy of volumetric assessment of infiltrative hepatocellular carcinoma treated with TACE,and to analyze how this improved measurement impacts prognostic prediction.METHODS We retrospectively collected data from 105 patients with invasive liver cancer who underwent TACE treatment at the Affiliated Hospital of Xuzhou Medical University from January 2020 to January 2024.The improved N4 bias field correction algorithm was applied to process MRI images,and the ETV before and after treatment was calculated.The ETV measurements before and after correction were compared,and their relationship with patient prognosis was analyzed.A Cox proportional hazards model was used to evaluate prognostic factors,with Martingale residual analysis determining the optimal cutoff value,followed by survival analysis.RESULTS Bias field correction significantly affected ETV measurements,with the corrected baseline ETV mean(505.235 cm^(3))being significantly lower than before correction(825.632 cm^(3),P<0.001).Cox analysis showed that the hazard ratio(HR)for corrected baseline ETV(HR=1.165,95%CI:1.069-1.268)was higher than before correction(HR=1.063,95%CI:1.031-1.095).Using 412 cm^(3) as the cutoff,the group with baseline ETV<415 cm^(3) had a longer median survival time compared to the≥415 cm^(3) group(18.523 months vs 8.926 months,P<0.001).The group with an ETV reduction rate≥41%had better prognosis than the<41%group(17.862 months vs 9.235 months,P=0.006).Multivariate analysis confirmed that ETV reduction rate(HR=0.412,P<0.001),Child-Pugh classification(HR=0.298,P<0.001),and Barcelona Clinic Liver Cancer stage(HR=0.578,P=0.045)were independent prognostic factors.CONCLUSION Volume imaging based on MRI bias field correction can improve the accuracy of evaluating the efficacy of TACE treatment for invasive liver cancer.The corrected ETV and its reduction rate can serve as independent indicators for predicting patient prognosis,providing important reference for developing individualized treatment strategies.
基金supports by the National Natural Science Foundation of China(Nos.82201135)"2015"Cultivation Program for Reserve Talents for Academic Leaders of Nanjing Stomatological School,Medical School of Nanjing University(No.0223A204).
文摘Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.
文摘Following the publication of Zeng et al.(2023),an inadvertent error was recently identified in Figure 1B and Supplementary Figure S3.To ensure the accuracy and integrity of our published work,we formally request a correction to address this issue and apologize for any confusion this error may have caused.For details,please refer to the modified Supplementary Materials.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2242213,U2142213,42305167,42175105)。
文摘Systematic bias is a type of model error that can affect the accuracy of data assimilation and forecasting that must be addressed.An online bias correction scheme called the sequential bias correction scheme(SBCS),was developed using the6 h average bias to correct the systematic bias during model integration.The primary purpose of this study is to investigate the impact of the SBCS in the high-resolution China Meteorological Administration Meso-scale(CMA-MESO)numerical weather prediction(NWP)model to reduce the systematic bias and to improve the data assimilation and forecast results through this method.The SBCS is improved upon and applied to the CMA-MESO 3-km model in this study.Four-week sequential data assimilation and forecast experiments,driven by rapid update and cycling(RUC),were conducted for the period from 2–29 May 2022.In terms of the characteristics of systematic bias,both the background and analysis show diurnal bias,and these large biases are affected by complex underlying surfaces(e.g.,oceans,coasts,and mountains).After the application of the SBCS,the results of the data assimilation show that the SBCS can reduce the systematic bias of the background and yield a neutral to slightly positive result for the analysis fields.In addition,the SBCS can reduce forecast errors and improve forecast results,especially for surface variables.The above results indicate that this scheme has good prospects for high-resolution regional NWP models.
基金supported by the Science and Technology Commission of Shanghai Municipality(Grant No.24DP2600202)the National Key R&D Program of China(Grant No.2024YFB4504002)the National Natural Science Foundation of China(Grant No.92165107)。
文摘For the quantum error correction and noisy intermediate-scale quantum algorithms to function with high efficiency,the raw fidelity of quantum logic gates on physical qubits needs to satisfy strict requirements.The neutral atom quantum computing equipped with Rydberg blockade gates has made impressive progress recently,which makes it worthwhile to explore its potential in the two-qubit entangling gates,including the controlledphase gate,and in particular,the CZ gate.Provided the quantum coherence is well preserved,improving the fidelity of Rydberg blockade gates calls for special mechanisms to deal with adverse effects caused by realistic experimental conditions.Here,the heralded very-high-fidelity Rydberg blockade controlled-phase gate is designed to address these issues,which contains self-correction and projection as the key steps.This trailblazing method builds upon the previously established buffer-atom-mediated gate framework,with a special form of symmetry under parity–time transformation playing a crucial role in the process.We further analyze the performance with respect to a few typical sources of imperfections.This procedure can also be regarded as quantum hardware error correction or mitigation.While this paper by itself does not cover every single subtle issue and still contains many oversimplifications,we find it reasonable to anticipate a very-high-fidelity two-qubit quantum logic gate operated in the sense of heralded but probabilistic,whose gate error can be reduced to the level of 10^(-4)–10^(-6)or even lower with reasonably high possibilities.
基金supported in part by STI 2030-Major Projects under Grant 2022ZD0209200in part by Beijing Natural Science Foundation-Xiaomi Innovation Joint Fund (L233009)+4 种基金in part by National Natural Science Foundation of China under Grant No. 62374099in part by the Tsinghua-Toyota Joint Research Fundin part by the Daikin Tsinghua Union Programin part by Independent Research Program of School of Integrated Circuits,Tsinghua Universitysponsored by CIE-Tencent Robotics X Rhino-Bird Focused Research Program
文摘Correction to:Nano-Micro Letters(2025)17:191 https://doi.org/10.1007/s40820-025-01702-7 Following the publication of the original article[1],the authors reported an error in Fig.3(b),and the figure legend was reversed.The correct Fig.3 has been provided in this orrection.
基金National Key R&D Program of China(2022YFB3706901)National Natural Science Foundation of China(52274382)Key Research and Development Program of Hubei Province(2022BAA024)。
文摘The hot deformation behavior of as-extruded Ti-6554 alloy was investigated through isothermal compression at 700–950°C and 0.001–1 s^(−1).The temperature rise under different deformation conditions was calculated,and the curve was corrected.The strain compensation constitutive model of as-extruded Ti-6554 alloy based on temperature rise correction was established.The microstructure evolution under different conditions was analyzed,and the dynamic recrystallization(DRX)mechanism was revealed.The results show that the flow stress decreases with the increase in strain rate and the decrease in deformation temperature.The deformation temperature rise gradually increases with the increase in strain rate and the decrease in deformation temperature.At 700°C/1 s^(−1),the temperature rise reaches 100°C.The corrected curve value is higher than the measured value,and the strain compensation constitutive model has high prediction accuracy.The precipitation of theαphase occurs during deformation in the twophase region,which promotes DRX process of theβphase.At low strain rate,the volume fraction of dynamic recrystallization increases with the increase in deformation temperature.DRX mechanism includes continuous DRX and discontinuous DRX.
文摘The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Center(EC model)from February to December in 2022 were used.Based on the data of the national intelligent grid forecast,the intelligent grid forecast of the regional bureau,EC model,etc.,temperature was predicted.According to the research of the grid point forecast synthesis algorithm with the highest accuracy rate in the recent three days,the temperature grid point correction was conducted in two forms of stations and grids.In order to reduce the deviation caused by the seasonal system temperature difference,a temperature prediction model was established by using the rolling forecast errors of 5,10,15,20,25 and 30 d as the basis data.The verification and evaluation of objective correction results show that the accuracy rate of temperature forecast by the intelligent grid of the regional bureau,the national intelligent grid,and EC model could be increased by 10%,8%,and 12%,respectively.
文摘Correction to:Rare Met.https://doi.org/10.1007/s12598-021-01815-z In the original publication,Fig.5 was published with few mistakes.The correct version of Fig.5 is given in this correction.
文摘Correction to:Nuclear Science and Techniques(2025)36:66 https://doi.org/10.1007/s41365-025-01662-y.In this article,the author’s name Hui-Ling Wei was incorrectly written as Hui-Ling We.The original article has been corrected.
基金funded by the National Natural Science Foundation of China under Grant No.11975145。
文摘In this work,we apply tunneling formalism to analyze charged particles tunneling across a hairy black hole horizon.Such black hole solutions are essential for frameworks based on Horndeski's gravity theory.Applying a semi-classical technique,we examine the tunneling of charged particles from a hairy black hole and derive the generic tunneling spectrum of released particles,ignoring self-gravitational and interaction.It is studied to ignore the back-reaction impact of the radiated particle on the hairy black hole.We analyze the properties of the black hole,such as temperature and entropy,under the influence of quantum gravity and also observe that the firstorder correction is present.We study tunneling radiation produced by a charged field equation in the presence of a generalized uncertainty effect.We modify the semi-classical technique by using the generalized uncertainty principle,the WKB approximation,and surface gravity.
文摘Correction to:Nuclear Science and Techniques(2024)36:8 https://doi.org/10.1007/s41365-024-01570-7 In this article the affiliation details for Author Jian Shan were incorrectly given as‘College of Physics and Electronic Engi-neering,Hengyang Normal University,Hengyang 421008,China’but should have been‘School of Nuclear Science and Technology,University of South China,Hengyang 421001,China’.The original article has been corrected.
文摘Correction to:Nuclear Science and Techniques(2024)35:162 https://doi.org/10.1007/s41365-024-01514-1 In this article,the citation information for Figures 6 and 7 was published incorrectly.The correct citations should read as follows:In the sentence beginning‘the curve of Eq.17 is plotted…..’in this article,the text‘as shown in Fig.7a’should have read‘as shown in Fig.6a’.
