In recent years,the global installed capacity of wind power has grown rapidly,making the enhancement of wind power prediction accuracy crucial for facilitating the integration and consumption of renewable energy.Curre...In recent years,the global installed capacity of wind power has grown rapidly,making the enhancement of wind power prediction accuracy crucial for facilitating the integration and consumption of renewable energy.Current research on ultra-short-term wind power prediction often overlooks load characteristics,resulting in an inability to adequately address grid connection requirements and load dispatching demands across different time periods.To address this limitation,this study proposes a novel approach to ultra-short-term wind power prediction error correction that incorporates load peak-valley characteristics.The methodology involves three key steps:first,deriving interannual prediction error characteristics from ultra-short-term prediction results of wind farm clusters;second,establishing error correction intervals for load peak and valley periods,calculating corresponding correction coefficients,and analyzing the impact of varying correction radii on the final results;third,validating the proposed method through empirical analysis of wind farm clusters in three northeastern provinces.The results demonstrate that this approach not only improves wind power prediction accuracy but also significantly reduces the occurrence of harmful error days,thereby better meeting the operational requirements of power system dispatch.展开更多
Aerodynamic performances of axial compressors are significantly affected by variation of Reynolds number in aero-engines.In the design and analysis of compressors,previous correction methods for cascades and stages ha...Aerodynamic performances of axial compressors are significantly affected by variation of Reynolds number in aero-engines.In the design and analysis of compressors,previous correction methods for cascades and stages have difficulties in predicting comprehensively Reynolds number effects on airfoils,matching and characteristics curves.This study proposes Re-correction models for loss,deviation angle and endwall blockage based on classical theories and cascade tests,and loss and deviation models show good agreement in test data of NACA65 and C4 cascades.Throughflow method considering Reynolds number effects is developed by integrating the correction models into a verified Streamline Curvature(SLC)tool.A three-stage axial compressor is investigated through SLC and CFD methods from design Reynolds number(Red=2106)to low Re=4104,and the numerical methods are validated with test data of characteristic curves and spanwise distributions at Red.With Re reduction,SLC method with correction models well predicts variation in overall performances compared with CFD calculations and Wassell's model.Streamwise and spanwise matching such as total pressure and loss distributions in SLC predictions are basically consistent with those in CFD results at near-stall points under design and low Reynolds numbers.SLC and CFD methods share similar detections of stall risks in the third stage(Stg3),and their analyses of diffusion processes deviate to some extent due to different predictions in separated endwall flow.The correction models can be adopted to consider Reynolds number effects in through-flow design and analysis of axial compressors.展开更多
The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These...The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.展开更多
The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navi...The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.展开更多
Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,i...Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,its TC forecasts still require enhancement.Prediction errors persist due to biases in the training data and smoothing effects in data-driven methods.To address this,we introduce CycloneBCNet,a deep-learning model designed to correct TianXing’s TC forecast biases by leveraging spatial and temporal data.CycloneBCNet utilizes the SimVP(simpler yet better video prediction)framework with spatial attention to highlight cyclone core regions in forecast fields.It also incorporates TC trend information(center position,maximum wind speed,and minimum sea level pressure)via an LSTM(long short-term memory)module.These TC vectors are derived from post-processed TianXing forecasts.By fusing features from forecast fields and TC vectors,CycloneBCNet corrects biases across multiple lead times.At a 96-h lead time,the track error reduces from 162.4 to 86.4 km,the wind speed error from 17.2 to 6.69 m s^(-1),and the pressure error from 22.2 to 9.36 hPa.Interpretability analysis shows that CycloneBCNet adjusts its attention across forecast lead times.Intensity corrections prioritize inner-core dynamics,particularly the eye and eyewall,while track corrections shift from lower-level variables and the cyclone’s core to broader environmental factors and mid-to upper-level features as the forecast duration increases.These findings demonstrate that CycloneBCNet effectively captures key TC dynamics consistent with meteorological principles,including the dominance of near-surface conditions for intensity and the increasing influence of steering currents on track prediction.展开更多
The infrared channels of the FY-4B advanced geosynchronous radiation imagers(AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the ini...The infrared channels of the FY-4B advanced geosynchronous radiation imagers(AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the initial field quality and the forecasting accuracy of the model. This study assimilated FY-4B AGRI data into the CMA-MESO model and analyzed the bias characteristics and correction methods. Analysis of the AGRI data revealed a clear diurnal variation in the bias, which was positively correlated with the solar elevation angle. However, the diurnal variation in the bias lagged behind the solar elevation angle, likely owing to temperature changes and delayed instrument responses resulting from solar radiation. To address this issue, we propose a correction method that utilizes the solar elevation angle after an optimal time shift. Using the time-shifted solar elevation angle as a predictor effectively reduces the diurnal variation in bias and significantly improves the correction effect. This approach provides theoretical support for the assimilation of FY-4B AGRI data into mesoscale numerical weather predictions, thereby enhancing the reliability of the assimilation results.展开更多
Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial fe...Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial features.To address the limitations,the paper proposes a TimeXer-based numerical forecast correction model optimized by an exogenous-variable attention mechanism.The model treats target forecast values as internal variables,and incorporates historical temporal-spatial data and seven-day numerical forecast results from traditional models as external variables based on the embedding strategy of TimeXer.Using a self-attention structure,the model captures correlations between exogenous variables and target sequences,explores intrinsic multi-dimensional relationships,and subsequently corrects endogenous variables with the mined exogenous features.The model’s performance is evaluated using metrics including MSE(Mean Squared Error),MAE(Mean Absolute Error),RMSE(Root Mean Square Error),MAPE(Mean Absolute Percentage Error),MSPE(Mean Square Percentage Error),and computational time,with TimeXer and PatchTST models serving as benchmarks.Experiment results show that the proposed model achieves lower errors and higher correction accuracy for both one-day and seven-day forecasts.展开更多
Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altit...Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altitude correction during the survey process.Commonly used terrain correction methods are based on the concept of finite elementization of ground surface radioactive sources,using GPS coordinates,radar altitude,and ground elevation distribution information from aerial surveys,combined with the sourceless efficiency calibration method to construct a response matrix,which is then inverted for surface nuclide content.However,most of the sourceless efficiency calibration methods used are numerical calculations that consider the body detector as a point detector and do not consider the changes in intrinsic detection efficiency under different incident directions of gamma rays.Therefore,when the altitude of the measurement area varies significantly or the flight altitude of the aerial survey is relatively low,such sourceless efficiency calibration method calculations tend to have a large bias,which affects the accuracy of the terrain correction.To address the above problems,this study employs a novel sourceless efficiency calibration method based on the Boolean operation of the ray deposition process and simplifies the traditional body source measurement model to a surface source measurement model to achieve fast and accurate efficiency calibration.Then,through the discretization of the measurement process,the static measurement process is superposed as equivalent to the dynamic measurement process,and the dynamic measurement response matrix is built and optimized based on the calibration method.Finally,the PSO-MLEM algorithm was used to solve the dynamic measurement response matrix to achieve dynamic terrain correction of aerial survey data.Analysis of the Baiyun'ebo test area revealed that,after applying dynamic terrain correction,the inverted anomalies in uranium(eU),thorium(eTh),and potassium(K)concentrations were closer to ground measurements(within 5.72%-30.79%)and exhibited clearer anomaly boundaries compared to traditional height-based corrections.However,owing to the inherent statistical fluctuations and characteristics of matrix inversion,higher measurement values tend to absorb lower ones,potentially enlarging the anomalous regions.Nevertheless,the highanomaly regions after inversion largely coincided with the ground truth validation,demonstrating that the proposed method can effectively correct airborne gamma spectrometry data.展开更多
Sensor noise is a critical factor that degrades the performance of image processing systems.In traditional computing systems,noise correction is implemented in the digital domain,resulting in redundant latency and pow...Sensor noise is a critical factor that degrades the performance of image processing systems.In traditional computing systems,noise correction is implemented in the digital domain,resulting in redundant latency and power consumption overhead in the analog-to-digital conversion.In this work,we propose an analog-domain image correction architecture based on a proposed small-scale UNet,which implements a compact noise correction network within a one-transistor-one-memristor(1T1R)array.The statistical non-idealities of the fabricated 1T1R array(e.g.,device variability)are rigorously incorporated into the network's training and inference simulations.This correction network architecture leverages memristors for conducting multiply-accumulate operations aimed at rectifying non-uniform noise,defective pixels(stuck-at-bright/dark),and exposure mismatch.Compared to systems without correction,the proposed architecture achieves up to 50.13%improvement in recognition accuracy while demonstrating robust tolerance to memristor device-level errors.The proposed system achieves a 2.13-fold latency reduction and three orders of magnitude higher energy efficiency compared to conventional architecture.This work establishes a new paradigm for advancing the development of low-power,low-latency,and high-precision image processing systems.展开更多
Correction to“Liu QQ,Li YD,Chen JX,Zhang LL,Guan RC,Zhao W,Meng LY.Prognostic value of preoperative fibrinogen,neutrophil-to-lymphocyte ratio,serum alpha-fetoprotein,and prealbumin for patients with primary liver can...Correction to“Liu QQ,Li YD,Chen JX,Zhang LL,Guan RC,Zhao W,Meng LY.Prognostic value of preoperative fibrinogen,neutrophil-to-lymphocyte ratio,serum alpha-fetoprotein,and prealbumin for patients with primary liver cancer undergoing transarterial chemoembolization.World J Gastrointest Oncol 2025;17(6):103198 PMID:40547171 DOI:10.4251/wjgo.v17.i6.103198”.The funding number listed in the"Supported by"section of this article needs to be corrected.展开更多
Although substantial research shows the effectiveness of written corrective feedback(WCF)in treating simple grammar structures,more research is still needed to refute Truscott’s claim that WCF may not work on complex...Although substantial research shows the effectiveness of written corrective feedback(WCF)in treating simple grammar structures,more research is still needed to refute Truscott’s claim that WCF may not work on complex grammar structures.Similarly,a previous body of research has shown that the degree of explicitness of feedback moderates the efficacy of WCF.However,most WCF studies have systematically manipulated only direct corrective feedback.The current study was therefore conducted to fill these gaps in the literature.To this end,five intact classes of Functional English were recruited and later randomly assigned to four treatment groups:DCF,DCF+ME,ICF,and ICF+ME,and one control group that received no feedback.All the groups took part in three WCF treatment sessions,during which they wrote two different pieces:a news report and a picture description.Later,only the treatment groups received the WCF.The WCF’s effectiveness was measured by writing tests and grammaticality judgment tasks(GJT).The results demonstrated that WCF helped L2 learners improve their grammatical accuracy of passive voice tenses.The study further showed that the group that received the most explicit type of WCF fared better than the ones that received the least explicit type of WCF.Important pedagogical implications for ESL/EFL teachers are discussed.展开更多
This letter compares the clinical efficacy and economic feasibility of the scoliocorrector fatma-UI(SCFUI)with direct vertebral rotation(DVR)in treating adolescent idiopathic scoliosis(AIS).SCFUI has shown promising r...This letter compares the clinical efficacy and economic feasibility of the scoliocorrector fatma-UI(SCFUI)with direct vertebral rotation(DVR)in treating adolescent idiopathic scoliosis(AIS).SCFUI has shown promising results in threedimensional spinal correction,providing superior rotational alignment compared to DVR and achieving significant improvements in coronal and sagittal planes.Additionally,SCFUI’s advanced design reduces risks associated with AIS surgeries and enhances overall patient outcomes.Economic analysis reveals SCFUI as a cost-effective option,potentially lowering long-term healthcare costs by minimizing complications and revisions.Our findings suggest that SCFUI is a viable,innovative approach in AIS treatment,meeting clinical and economic demands in orthopedic care.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
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
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
Aberration-corrected focus scanning is crucial for high-precision optics,but the conventional optical systems rely on bulky and complicated dynamic correctors.Recently,Shiyi Xiao's group proposed a method using tw...Aberration-corrected focus scanning is crucial for high-precision optics,but the conventional optical systems rely on bulky and complicated dynamic correctors.Recently,Shiyi Xiao's group proposed a method using two rotating cascaded transmissive metasurfaces for adaptive aberration correction in focus scanning.The optimized phase profiles enable precise control of the focal position for scanning custom-curved surfaces.This concept was experimentally validated by two allsilicon meta-devices in the terahertz regime,paving the way for high-precision and compact optical devices in various applications.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
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
基金supported by the National Key R&D Program of China(Technology and application of wind power/photovoltaic power prediction for promoting renewable energy consumption(2018YFB0904200).
文摘In recent years,the global installed capacity of wind power has grown rapidly,making the enhancement of wind power prediction accuracy crucial for facilitating the integration and consumption of renewable energy.Current research on ultra-short-term wind power prediction often overlooks load characteristics,resulting in an inability to adequately address grid connection requirements and load dispatching demands across different time periods.To address this limitation,this study proposes a novel approach to ultra-short-term wind power prediction error correction that incorporates load peak-valley characteristics.The methodology involves three key steps:first,deriving interannual prediction error characteristics from ultra-short-term prediction results of wind farm clusters;second,establishing error correction intervals for load peak and valley periods,calculating corresponding correction coefficients,and analyzing the impact of varying correction radii on the final results;third,validating the proposed method through empirical analysis of wind farm clusters in three northeastern provinces.The results demonstrate that this approach not only improves wind power prediction accuracy but also significantly reduces the occurrence of harmful error days,thereby better meeting the operational requirements of power system dispatch.
基金supported by the National Science and Tech-nology Major Project of China(Nos.2017-II-0007-0021 and J2019-II-0017-0038)。
文摘Aerodynamic performances of axial compressors are significantly affected by variation of Reynolds number in aero-engines.In the design and analysis of compressors,previous correction methods for cascades and stages have difficulties in predicting comprehensively Reynolds number effects on airfoils,matching and characteristics curves.This study proposes Re-correction models for loss,deviation angle and endwall blockage based on classical theories and cascade tests,and loss and deviation models show good agreement in test data of NACA65 and C4 cascades.Throughflow method considering Reynolds number effects is developed by integrating the correction models into a verified Streamline Curvature(SLC)tool.A three-stage axial compressor is investigated through SLC and CFD methods from design Reynolds number(Red=2106)to low Re=4104,and the numerical methods are validated with test data of characteristic curves and spanwise distributions at Red.With Re reduction,SLC method with correction models well predicts variation in overall performances compared with CFD calculations and Wassell's model.Streamwise and spanwise matching such as total pressure and loss distributions in SLC predictions are basically consistent with those in CFD results at near-stall points under design and low Reynolds numbers.SLC and CFD methods share similar detections of stall risks in the third stage(Stg3),and their analyses of diffusion processes deviate to some extent due to different predictions in separated endwall flow.The correction models can be adopted to consider Reynolds number effects in through-flow design and analysis of axial compressors.
基金supported by the grants to Min Qiu and Ming Wang from the National Natural Science Foundation of China(32100160 and 32100044)the grants to Ming Wang from the Jiangsu“Innovative and Entrepreneurial Talent”Program,China(JSSCRC2021510)the grants to Yuanchao Wang from the Chinese Modern Agricultural Industry Technology System(CARS-004-PS14)。
文摘The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.
基金supported by the National Natural Science Foundation of China(No.41971339)the SDUST Research Fund(No.2019TDJH103)。
文摘The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.
基金supported by the Meteorological Joint Funds of the National Natural Science Foundation of China(Grant No.U2142211)the National Natural Science Foundation of China(Grant Nos.42075141,42341202 and 62088101)+1 种基金the National Key Research and Development Program of China(Grant No.2020YFA0608000)the Shanghai Municipal Science and Technology Major Project(Grant No.2021SHZDZX0100).
文摘Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,its TC forecasts still require enhancement.Prediction errors persist due to biases in the training data and smoothing effects in data-driven methods.To address this,we introduce CycloneBCNet,a deep-learning model designed to correct TianXing’s TC forecast biases by leveraging spatial and temporal data.CycloneBCNet utilizes the SimVP(simpler yet better video prediction)framework with spatial attention to highlight cyclone core regions in forecast fields.It also incorporates TC trend information(center position,maximum wind speed,and minimum sea level pressure)via an LSTM(long short-term memory)module.These TC vectors are derived from post-processed TianXing forecasts.By fusing features from forecast fields and TC vectors,CycloneBCNet corrects biases across multiple lead times.At a 96-h lead time,the track error reduces from 162.4 to 86.4 km,the wind speed error from 17.2 to 6.69 m s^(-1),and the pressure error from 22.2 to 9.36 hPa.Interpretability analysis shows that CycloneBCNet adjusts its attention across forecast lead times.Intensity corrections prioritize inner-core dynamics,particularly the eye and eyewall,while track corrections shift from lower-level variables and the cyclone’s core to broader environmental factors and mid-to upper-level features as the forecast duration increases.These findings demonstrate that CycloneBCNet effectively captures key TC dynamics consistent with meteorological principles,including the dominance of near-surface conditions for intensity and the increasing influence of steering currents on track prediction.
基金National Key Research and Development Program of China (2022YFC3004004)National Natural Science Foundation of China (42075155,12241104)National Natural Science Foundation of China Joint Fund (U2342213)。
文摘The infrared channels of the FY-4B advanced geosynchronous radiation imagers(AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the initial field quality and the forecasting accuracy of the model. This study assimilated FY-4B AGRI data into the CMA-MESO model and analyzed the bias characteristics and correction methods. Analysis of the AGRI data revealed a clear diurnal variation in the bias, which was positively correlated with the solar elevation angle. However, the diurnal variation in the bias lagged behind the solar elevation angle, likely owing to temperature changes and delayed instrument responses resulting from solar radiation. To address this issue, we propose a correction method that utilizes the solar elevation angle after an optimal time shift. Using the time-shifted solar elevation angle as a predictor effectively reduces the diurnal variation in bias and significantly improves the correction effect. This approach provides theoretical support for the assimilation of FY-4B AGRI data into mesoscale numerical weather predictions, thereby enhancing the reliability of the assimilation results.
基金supported by the National Key Research and Development Program Project(2023YFC3107804)Planning Fund Project of Humanities and Social Sciences Research of the Ministry of Education(24YJA880097)the Graduate Education Reform Project in North China University of Technology(217051360025XN095-17)。
文摘Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial features.To address the limitations,the paper proposes a TimeXer-based numerical forecast correction model optimized by an exogenous-variable attention mechanism.The model treats target forecast values as internal variables,and incorporates historical temporal-spatial data and seven-day numerical forecast results from traditional models as external variables based on the embedding strategy of TimeXer.Using a self-attention structure,the model captures correlations between exogenous variables and target sequences,explores intrinsic multi-dimensional relationships,and subsequently corrects endogenous variables with the mined exogenous features.The model’s performance is evaluated using metrics including MSE(Mean Squared Error),MAE(Mean Absolute Error),RMSE(Root Mean Square Error),MAPE(Mean Absolute Percentage Error),MSPE(Mean Square Percentage Error),and computational time,with TimeXer and PatchTST models serving as benchmarks.Experiment results show that the proposed model achieves lower errors and higher correction accuracy for both one-day and seven-day forecasts.
基金supported by the National Key Research and Development Program(No.2022YFC2807400)the National Natural Science Foundation of China(Nos.12265003 and 12205044)。
文摘Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altitude correction during the survey process.Commonly used terrain correction methods are based on the concept of finite elementization of ground surface radioactive sources,using GPS coordinates,radar altitude,and ground elevation distribution information from aerial surveys,combined with the sourceless efficiency calibration method to construct a response matrix,which is then inverted for surface nuclide content.However,most of the sourceless efficiency calibration methods used are numerical calculations that consider the body detector as a point detector and do not consider the changes in intrinsic detection efficiency under different incident directions of gamma rays.Therefore,when the altitude of the measurement area varies significantly or the flight altitude of the aerial survey is relatively low,such sourceless efficiency calibration method calculations tend to have a large bias,which affects the accuracy of the terrain correction.To address the above problems,this study employs a novel sourceless efficiency calibration method based on the Boolean operation of the ray deposition process and simplifies the traditional body source measurement model to a surface source measurement model to achieve fast and accurate efficiency calibration.Then,through the discretization of the measurement process,the static measurement process is superposed as equivalent to the dynamic measurement process,and the dynamic measurement response matrix is built and optimized based on the calibration method.Finally,the PSO-MLEM algorithm was used to solve the dynamic measurement response matrix to achieve dynamic terrain correction of aerial survey data.Analysis of the Baiyun'ebo test area revealed that,after applying dynamic terrain correction,the inverted anomalies in uranium(eU),thorium(eTh),and potassium(K)concentrations were closer to ground measurements(within 5.72%-30.79%)and exhibited clearer anomaly boundaries compared to traditional height-based corrections.However,owing to the inherent statistical fluctuations and characteristics of matrix inversion,higher measurement values tend to absorb lower ones,potentially enlarging the anomalous regions.Nevertheless,the highanomaly regions after inversion largely coincided with the ground truth validation,demonstrating that the proposed method can effectively correct airborne gamma spectrometry data.
基金Project supported by the National Key Research and Development Program of China(Grant No.2024YFA1208800)the National Natural Science Foundation of China(Grant Nos.62404253,62304254,U23A20322)。
文摘Sensor noise is a critical factor that degrades the performance of image processing systems.In traditional computing systems,noise correction is implemented in the digital domain,resulting in redundant latency and power consumption overhead in the analog-to-digital conversion.In this work,we propose an analog-domain image correction architecture based on a proposed small-scale UNet,which implements a compact noise correction network within a one-transistor-one-memristor(1T1R)array.The statistical non-idealities of the fabricated 1T1R array(e.g.,device variability)are rigorously incorporated into the network's training and inference simulations.This correction network architecture leverages memristors for conducting multiply-accumulate operations aimed at rectifying non-uniform noise,defective pixels(stuck-at-bright/dark),and exposure mismatch.Compared to systems without correction,the proposed architecture achieves up to 50.13%improvement in recognition accuracy while demonstrating robust tolerance to memristor device-level errors.The proposed system achieves a 2.13-fold latency reduction and three orders of magnitude higher energy efficiency compared to conventional architecture.This work establishes a new paradigm for advancing the development of low-power,low-latency,and high-precision image processing systems.
基金Supported by Health Commission of Heilongjiang Province,No.20230404080031.
文摘Correction to“Liu QQ,Li YD,Chen JX,Zhang LL,Guan RC,Zhao W,Meng LY.Prognostic value of preoperative fibrinogen,neutrophil-to-lymphocyte ratio,serum alpha-fetoprotein,and prealbumin for patients with primary liver cancer undergoing transarterial chemoembolization.World J Gastrointest Oncol 2025;17(6):103198 PMID:40547171 DOI:10.4251/wjgo.v17.i6.103198”.The funding number listed in the"Supported by"section of this article needs to be corrected.
文摘Although substantial research shows the effectiveness of written corrective feedback(WCF)in treating simple grammar structures,more research is still needed to refute Truscott’s claim that WCF may not work on complex grammar structures.Similarly,a previous body of research has shown that the degree of explicitness of feedback moderates the efficacy of WCF.However,most WCF studies have systematically manipulated only direct corrective feedback.The current study was therefore conducted to fill these gaps in the literature.To this end,five intact classes of Functional English were recruited and later randomly assigned to four treatment groups:DCF,DCF+ME,ICF,and ICF+ME,and one control group that received no feedback.All the groups took part in three WCF treatment sessions,during which they wrote two different pieces:a news report and a picture description.Later,only the treatment groups received the WCF.The WCF’s effectiveness was measured by writing tests and grammaticality judgment tasks(GJT).The results demonstrated that WCF helped L2 learners improve their grammatical accuracy of passive voice tenses.The study further showed that the group that received the most explicit type of WCF fared better than the ones that received the least explicit type of WCF.Important pedagogical implications for ESL/EFL teachers are discussed.
文摘This letter compares the clinical efficacy and economic feasibility of the scoliocorrector fatma-UI(SCFUI)with direct vertebral rotation(DVR)in treating adolescent idiopathic scoliosis(AIS).SCFUI has shown promising results in threedimensional spinal correction,providing superior rotational alignment compared to DVR and achieving significant improvements in coronal and sagittal planes.Additionally,SCFUI’s advanced design reduces risks associated with AIS surgeries and enhances overall patient outcomes.Economic analysis reveals SCFUI as a cost-effective option,potentially lowering long-term healthcare costs by minimizing complications and revisions.Our findings suggest that SCFUI is a viable,innovative approach in AIS treatment,meeting clinical and economic demands in orthopedic care.
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.
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.
文摘Aberration-corrected focus scanning is crucial for high-precision optics,but the conventional optical systems rely on bulky and complicated dynamic correctors.Recently,Shiyi Xiao's group proposed a method using two rotating cascaded transmissive metasurfaces for adaptive aberration correction in focus scanning.The optimized phase profiles enable precise control of the focal position for scanning custom-curved surfaces.This concept was experimentally validated by two allsilicon meta-devices in the terahertz regime,paving the way for high-precision and compact optical devices in various applications.
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.
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.
