Over recent years, Japanese right-wing conservatist forces have launched a media and diplomatic attack of shifting the blame of "hindering the development of Sino-Japanese relations" on to China. They said t...Over recent years, Japanese right-wing conservatist forces have launched a media and diplomatic attack of shifting the blame of "hindering the development of Sino-Japanese relations" on to China. They said that China was playing the history card, seizing Japan’s historical fault as a handle against Japan. Some public figures in China also advocate sheltering the issue of the perception of history in order to展开更多
People doing business in China should try to know how to address their Chinese counter-parts, especially in formal settings so as to better engage with them. Different cultures mean people are addressed differently.
The paper was published in October 24,2025(D0I:10.11865/zs.2025404).The author wishes to correct her affiliation due to an institutional change during the manuscript preparation process.
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
Marine heatwaves(MHWs)in the South China Sea(SCS)significantly impact marine ecosystems and socioeconomic development,yet accurately forecasting MHWs remains a challenge.This study developed an upper-ocean temperature...Marine heatwaves(MHWs)in the South China Sea(SCS)significantly impact marine ecosystems and socioeconomic development,yet accurately forecasting MHWs remains a challenge.This study developed an upper-ocean temperature forecasting model based on ConvLSTM for the northern SCS and,in conjunction with the ocean forecasting system LICOM Forecast System(LFS),constructed a hybrid Fusion model using Wasserstein-Distance optimization.The ability of these three models to forecast key MHW metrics with a 10-day lead was assessed during the summer of 2022 in the SCS.Overall,the Fusion model takes advantage of LFS and ConvLSTM,providing superior forecasts for both the duration and intensity of MHWs in the southern SCS.LFS(ConvLSTM)overestimates(underestimates)the duration of MHWs and all models exhibit limitations in forecasting the intensity of MHWs in part of the SCS.The Fusion model's superior forecast skill for MHWs may be attributable to its more realistic representation of the upper-ocean thermal structure with shallower mixed-layer depths during MHWs.This study highlights that combining the deep learning technique with a dynamical model can improve MHW forecasting and has certain physical interpretability.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
Despite its significant societal and scientific importance,projected changes in the characteristics of intraseasonal oscillations(ISOs)associated with Indian summer monsoon rainfall under increased greenhouse gas conc...Despite its significant societal and scientific importance,projected changes in the characteristics of intraseasonal oscillations(ISOs)associated with Indian summer monsoon rainfall under increased greenhouse gas concentrations remain largely unexplored.This study utilizes downscaled and bias-corrected historical simulations and projections from 17 CMIP6 models to investigate the future evolution of ISOs.Our findings reveal a twofold increase in ISO variability over India in the far future under the very high emissions scenario,raising critical concerns about its adverse socioeconomic impacts.Our analysis suggests that the increased magnitude of precipitation anomalies associated with northwardpropagating ISOs may intensify active monsoon spells,potentially triggering extreme rainfall events.Additionally,the phase speed of these northward-propagating ISOs over the Bay of Bengal is projected to accelerate owing to weakened air-sea coupling and feedback.This acceleration reduces the northwest-southeast tilt of the precipitation band,altering the spatial structure of the ISOs.Concurrently,the strengthening of circulation-precipitation feedback and warming of the Indian Ocean are projected to enhance the phase speed of monsoon ISOs,leading to more frequent active spells.This study underscores the critical role of regional ocean-atmosphere feedback in shaping future ISO characteristics,highlighting the urgent need for improved understanding and prediction of these changes in the context of a warming climate.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
Rui Chena,b,Tangbing Cui a,b,∗a School of Biology and Biological Engineering,South China University of Technology,Guangzhou 510006,China b Guangdong Key Laboratory of Fermentation and Enzyme Engineering,South China Un...Rui Chena,b,Tangbing Cui a,b,∗a School of Biology and Biological Engineering,South China University of Technology,Guangzhou 510006,China b Guangdong Key Laboratory of Fermentation and Enzyme Engineering,South China University of Technology,Guangzhou 510006,China The authors regret that the published version of this article contained several errors and omissions,which are described and corrected below.1.Figs.3 and 4(figure order and legends).In the published article,Figs.3 and 4 were inadvertently published in reversed order.The figures should be swapped so that the figure content matches its caption.The correct figures and their legends are provided on the following page.2.Title correction.The compound name in the published title was incorrectly typeset as“benzo[a]pyrene”The correct spelling is“benzo[a]pyrene.”3.Text corrections in Section 2.4.Several typographical errors occurred in Section 2.4(“Up-regulation of acetoin,lactate,and kanosamine biosynthesis under sodium gluconate treatment”).展开更多
Accurate precipitation estimation in semiarid,topographically complicated areas is critical for water resource management and climate risk monitoring.This work provides a detailed,multi-scale evaluation of four major ...Accurate precipitation estimation in semiarid,topographically complicated areas is critical for water resource management and climate risk monitoring.This work provides a detailed,multi-scale evaluation of four major satellite precipitation products(CHIRPS,PERSIANN-CDR,IMERG-F v07,and GSMaP)over Isfahan province,Iran,over a 9-year period(2015-2023).The performance of these products was benchmarked against a dense network of 98 rain gauges using a suite of continuous and categorical statistical metrics,following a two-stage quality control protocol to remove outliers and false alarms.The results revealed that the performance of all products improves with temporal aggregation.At the daily level,GSMaP performed marginally better,although all products were linked with considerable uncertainty.At the monthly and annual levels,the GPM-era products(IMERG and GSMaP)clearly beat the other two,establishing themselves as dependable tools for long-term hydro-climatological studies.Error analysis revealed that topography is the dominant regulating factor,creating a systematic elevationdependent bias,largely characterized by underestimation from most products in high-elevation areas,though the PERSIANN-CDR product exhibited a contrasting overestimation tendency.Finally,the findings highlight the importance of implementing local,elevation-dependent calibration before deploying these products in hydrological modeling.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
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
Considering the drastic variations in the surface elevation of the piedmont region in the Bai Cheng West Area,there is no reference point within the Reference Ground Line(RG line)of the starting point of the synthetic...Considering the drastic variations in the surface elevation of the piedmont region in the Bai Cheng West Area,there is no reference point within the Reference Ground Line(RG line)of the starting point of the synthetic seismic records in the process of calibration of the horizon.Through the analysis of the process and properties of the production of the RG line,in the processing of seismic data,it is indicated that the position of the synthetic data of seismic records is not located at the beginning of the RG line.Rather,it must be at the time point of the seismic profile at the elevation of a datum position of the static value of less than the datum plane.Both the RG line and the elevation static correction value line can easily be seen by computerizing the calculated value of the elevation static correction of the datum plane relating to the seismic section and plotting it on the seismic section.To achieve a good calibration with the synthetic seismogram,it is possible to set the starting point of the synthetic seismogram on the elevation static correction value line that is situated at the place of the Common Mid-Point(CMP).In the current paper,a systematic overview of methods and safety procedures for establishing the seismic interpretation work area and horizon calibration in seismic interpretation has been reviewed,which will form an effective guide towards seismic interpretation under the complicated surface conditions in the Bai Cheng west region.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
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
In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along...In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.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
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
文摘Over recent years, Japanese right-wing conservatist forces have launched a media and diplomatic attack of shifting the blame of "hindering the development of Sino-Japanese relations" on to China. They said that China was playing the history card, seizing Japan’s historical fault as a handle against Japan. Some public figures in China also advocate sheltering the issue of the perception of history in order to
文摘People doing business in China should try to know how to address their Chinese counter-parts, especially in formal settings so as to better engage with them. Different cultures mean people are addressed differently.
文摘The paper was published in October 24,2025(D0I:10.11865/zs.2025404).The author wishes to correct her affiliation due to an institutional change during the manuscript preparation process.
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 Natural Science Foundation of China [grant numbers 42375168 and 42205035]a Shanghai Science and Technology Commission Project [grant number 23DZ1204704]。
文摘Marine heatwaves(MHWs)in the South China Sea(SCS)significantly impact marine ecosystems and socioeconomic development,yet accurately forecasting MHWs remains a challenge.This study developed an upper-ocean temperature forecasting model based on ConvLSTM for the northern SCS and,in conjunction with the ocean forecasting system LICOM Forecast System(LFS),constructed a hybrid Fusion model using Wasserstein-Distance optimization.The ability of these three models to forecast key MHW metrics with a 10-day lead was assessed during the summer of 2022 in the SCS.Overall,the Fusion model takes advantage of LFS and ConvLSTM,providing superior forecasts for both the duration and intensity of MHWs in the southern SCS.LFS(ConvLSTM)overestimates(underestimates)the duration of MHWs and all models exhibit limitations in forecasting the intensity of MHWs in part of the SCS.The Fusion model's superior forecast skill for MHWs may be attributable to its more realistic representation of the upper-ocean thermal structure with shallower mixed-layer depths during MHWs.This study highlights that combining the deep learning technique with a dynamical model can improve MHW forecasting and has certain physical interpretability.
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 a National Research Foundation of Korea(NRF) grant funded by the Korean government (MSIT)(Grant No.RS-2024-00416848)SERB-DST Govt. of India for providing financial support under NPDF (Grant No.PDF/2022/001886)
文摘Despite its significant societal and scientific importance,projected changes in the characteristics of intraseasonal oscillations(ISOs)associated with Indian summer monsoon rainfall under increased greenhouse gas concentrations remain largely unexplored.This study utilizes downscaled and bias-corrected historical simulations and projections from 17 CMIP6 models to investigate the future evolution of ISOs.Our findings reveal a twofold increase in ISO variability over India in the far future under the very high emissions scenario,raising critical concerns about its adverse socioeconomic impacts.Our analysis suggests that the increased magnitude of precipitation anomalies associated with northwardpropagating ISOs may intensify active monsoon spells,potentially triggering extreme rainfall events.Additionally,the phase speed of these northward-propagating ISOs over the Bay of Bengal is projected to accelerate owing to weakened air-sea coupling and feedback.This acceleration reduces the northwest-southeast tilt of the precipitation band,altering the spatial structure of the ISOs.Concurrently,the strengthening of circulation-precipitation feedback and warming of the Indian Ocean are projected to enhance the phase speed of monsoon ISOs,leading to more frequent active spells.This study underscores the critical role of regional ocean-atmosphere feedback in shaping future ISO characteristics,highlighting the urgent need for improved understanding and prediction of these changes in the context of a warming climate.
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.
文摘Rui Chena,b,Tangbing Cui a,b,∗a School of Biology and Biological Engineering,South China University of Technology,Guangzhou 510006,China b Guangdong Key Laboratory of Fermentation and Enzyme Engineering,South China University of Technology,Guangzhou 510006,China The authors regret that the published version of this article contained several errors and omissions,which are described and corrected below.1.Figs.3 and 4(figure order and legends).In the published article,Figs.3 and 4 were inadvertently published in reversed order.The figures should be swapped so that the figure content matches its caption.The correct figures and their legends are provided on the following page.2.Title correction.The compound name in the published title was incorrectly typeset as“benzo[a]pyrene”The correct spelling is“benzo[a]pyrene.”3.Text corrections in Section 2.4.Several typographical errors occurred in Section 2.4(“Up-regulation of acetoin,lactate,and kanosamine biosynthesis under sodium gluconate treatment”).
文摘Accurate precipitation estimation in semiarid,topographically complicated areas is critical for water resource management and climate risk monitoring.This work provides a detailed,multi-scale evaluation of four major satellite precipitation products(CHIRPS,PERSIANN-CDR,IMERG-F v07,and GSMaP)over Isfahan province,Iran,over a 9-year period(2015-2023).The performance of these products was benchmarked against a dense network of 98 rain gauges using a suite of continuous and categorical statistical metrics,following a two-stage quality control protocol to remove outliers and false alarms.The results revealed that the performance of all products improves with temporal aggregation.At the daily level,GSMaP performed marginally better,although all products were linked with considerable uncertainty.At the monthly and annual levels,the GPM-era products(IMERG and GSMaP)clearly beat the other two,establishing themselves as dependable tools for long-term hydro-climatological studies.Error analysis revealed that topography is the dominant regulating factor,creating a systematic elevationdependent bias,largely characterized by underestimation from most products in high-elevation areas,though the PERSIANN-CDR product exhibited a contrasting overestimation tendency.Finally,the findings highlight the importance of implementing local,elevation-dependent calibration before deploying these products in hydrological modeling.
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.
文摘Considering the drastic variations in the surface elevation of the piedmont region in the Bai Cheng West Area,there is no reference point within the Reference Ground Line(RG line)of the starting point of the synthetic seismic records in the process of calibration of the horizon.Through the analysis of the process and properties of the production of the RG line,in the processing of seismic data,it is indicated that the position of the synthetic data of seismic records is not located at the beginning of the RG line.Rather,it must be at the time point of the seismic profile at the elevation of a datum position of the static value of less than the datum plane.Both the RG line and the elevation static correction value line can easily be seen by computerizing the calculated value of the elevation static correction of the datum plane relating to the seismic section and plotting it on the seismic section.To achieve a good calibration with the synthetic seismogram,it is possible to set the starting point of the synthetic seismogram on the elevation static correction value line that is situated at the place of the Common Mid-Point(CMP).In the current paper,a systematic overview of methods and safety procedures for establishing the seismic interpretation work area and horizon calibration in seismic interpretation has been reviewed,which will form an effective guide towards seismic interpretation under the complicated surface conditions in the Bai Cheng west region.
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.
文摘In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.
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.
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.
