A Machine Learning-Based Observational Constraint Correction Method for Seasonal Precipitation Prediction

Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image classification.Image denoising is done by a U-Net architecture that ensures effective image denoising.Attenuation correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of classification.Finally,a novel multi-scale diluted convolution(MSDC)network is proposed.It merges the features extracted in different scales and makes the model learn the features more efficiently.Three scales of filters with size 3×3 are used to extract features.All three steps are compared with state-of-the-art methods.The proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of 39.7.The proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

Advances in 3D correction of adolescent scoliosis:The superiority of scoliocorrector fatma-UI in rotational realignment

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.

AI-based Correction of Wave Forecasts Using the Transformer-enhanced UNet Model

Grid forecasting can be used to effectively enhance the spatial and temporal density of forecast products,thereby improving the capability of short-term marine disaster forecasting and warnings in terms of proximity.The traditional method that relies on forecasters'subjective correction of station observation data for forecasting has been unable to meet the practical needs of refined forecasting.To address this problem,this paper proposes a Transformer-enhanced UNet(TransUNet)model for wave forecast AI correction,which fuses wind and wave information.The Transformer structure is integrated into the encoder of the UNet model,and instead of using the traditional upsampling method,the dual-sampling module is employed in the decoder to enhance the feature extraction capability.This paper compares the TransUNet model with the traditional UNet model using wind speed forecast data,wave height forecast data,and significant wave height reanalysis data provided by ECMWF.The experimental results indicate that the TransUNet model yields smaller root-meansquare errors,mean errors,and standard deviations of the corrected results for the next 24-h forecasts than does the UNet model.Specifically,the root-mean-square error decreased by more than 21.55%compared to its precorrection value.According to the statistical analysis,87.81%of the corrected wave height errors for the next 24-h forecast were within±0.2m,with only 4.56%falling beyond±0.3 m.This model effectively limits the error range and enhances the ability to forecast wave heights.

Correction to:METTL5 promotes cell proliferation,invasion,and migration by up-regulating Toll-like receptor 8 expression in colorectal cancer

Correction to“METTL5 promotes cell proliferation,invasion,and migration by up-regulating Toll-like receptor 8 expression in colorectal cancer”in World J Gastrointest Oncol 2024;16(5):2006-2017,published by Kong LS,Tao R,Li YF,Wang WB,and Zhao X.In this article,we added the correct images.

Improving the Seasonal Forecast of Summer Precipitation in Southeastern China Using a CycleGAN-based Deep Learning Bias Correction Method

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.

Correction to:Assessing recent recurrence after hepatectomy for hepatitis B-related hepatocellular carcinoma by a predictive model based on sarcopenia

Correction to“Assessing recent recurrence after hepatectomy for hepatitis Brelated hepatocellular carcinoma by a predictive model based on sarcopenia.World J Gastroenterol 2024;30(12):1727-1738[PMID:38617742 DOI:10.3748/wjg.v30.i12.1727]”.In this article,figure 1 needs to be corrected.

Correction to:High expression of autophagy-related gene EIF4EBP1 could promote tamoxifen resistance and predict poor prognosis in breast cancer

This is an erratum to the published paper titled,“High expression of autophagyrelated gene EIF4EBP1 could promote tamoxifen resistance and predict poor prognosis in breast cancer.”We have removed the citations to certain articles in subsequent revisions of the manuscript.However,owing to our oversight,the citation marker in the upper right corner was not removed.We apologize for any confusion this may have caused.

Inflammatory Bowel Disease and Dementia:Evidence Triangulation from a Meta-Analysis of Observational Studies and Mendelian Randomization Study

Objective Observational studies have found associations between inflammatory bowel disease(IBD)and the risk of dementia,including Alzheimer’s dementia(AD)and vascular dementia(VD);however,these findings are inconsistent.It remains unclear whether these associations are causal.Methods We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia.Mendelian randomization(MR)analysis based on summary genome-wide association studies(GWASs)was performed.Genetic correlation and Bayesian colocalization analyses were used to provide robust genetic evidence.Results Ten observational studies involving 80,565,688 participants were included in this metaanalysis.IBD was significantly associated with dementia(risk ratio[RR]=1.36,95%CI=1.04-1.78;I2=84.8%)and VD(RR=2.60,95%CI=1.18-5.70;only one study),but not with AD(RR=2.00,95%CI=0.96-4.13;I^(2)=99.8%).MR analyses did not supported significant causal associations of IBD with dementia(dementia:odds ratio[OR]=1.01,95%CI=0.98-1.03;AD:OR=0.98,95%CI=0.95-1.01;VD:OR=1.02,95%CI=0.97-1.07).In addition,genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia.Conclusion Our study did not provide genetic evidence for a causal association between IBD and dementia risk.The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.

Long-term observation on safety and visual quality of implantable collamer lens V4c implantation for myopia correction:a 5-year follow-up

AIM:To elucidate the safety and visual quality of implantable collamer lens with central hole(ICL V4c)implantation for correcting moderate and high myopia for at least 5y.METHODS:This retrospective study was conducted on 58 patients(114 eyes)who were followed up for at least 5y after ICL V4c implantation.The observation was done before and on 1d,1mo,1 and 5y or more after the surgical procedure.The visual acuity,subjective refraction,intraocular pressure,vault,axial length,central hole position,pupil diameter,visual quality,and adverse events were analyzed.The visual quality includes aberration,the modulation transfer function cutoff frequency(MTF cutoff),objective scattering index(OSI),Stroller's ratio(SR),and visual quality questionnaire.RESULTS:The average follow-up period was 69.25±3.80mo(range 60–82mo)and the preoperative spherical equivalent(SE)was-8.66±1.97 D.At 5y after operation,the safety index was 1.01±0.02 and the efficacy index was 0.99±0.42 and SE was-0.65±0.63 D.The 59.6%of the eyes achieved an uncorrected distance visual acuity of 20/20,76.3%of the eyes had SE within±1.0 D at the last visit.The axial length increased by 0.29±0.71 mm 5y after the surgery(t=-3.843,P<0.001).The mean vault at the last follow-up was 510.59±245.61μm.The central hole was on the temporal side in 80 eyes(84.2%).The visual quality questionnaire showed that 98.2%patients were satisfied with the surgical procedure.Adverse events occurred in 4 eyes(3.5%),including the posttraumatic toric ICL rotation(2 eyes),iris incarceration(1 eye),and posttraumatic ICL displacement(1 eye)at the last follow-up.CONCLUSION:Long-term ICL V4c implantation is safe,effective,and stable for correcting moderate and to high myopia,and the visual quality with patients is excellent and satisfactory,but the progression of axial length still needs attention after surgery.

Evaluation and Correction of Ground-Based Microwave Radiometer Observations Based on NCEP-FNL Data

Consistency between the brightness temperatures observed with a ground-based microwave radiometer and the brightness temperatures computed by forward modeling is important in many different data applications. Using the National Centers for Environmental Prediction-Final Operational Global Analysis (NCEP-FNL) dataset as a reference, the brightness temperature was obtained through the radiation transfer model for forward calculation. The problem of segmented features in long time of observational data from ground-based microwave radiometers (the so-called “jumping problem”) was identified. By analyzing the deviation and correlation between the observational bright temperature data and the forward calculated data under clear sky conditions, a revised scheme is proposed for the bright temperature observational data. Data obtained with a ground-based microwave radiometer in Beijing from January 1, 2010 to December 31, 2011 around the date of liquid nitrogen calibration show that the correlation between the observed brightness temperatures and the forward computed brightness temperatures is better after correction, especially at 28 and 30 GHz. The “jumping” problem in the observational data for the brightness temperature is eliminated after correction and the time continuity of the observational data and its consistency with the forward calculated data based on the NCEP-FNL dataset are improved. The proposed correction scheme can be used both for real-time data quality control and to improve the accuracy of historical datasets obtained with poorly calibrated microwave radiometers or radiometers working in polluted environments.

Roughness correction method for salinity remote sensing using combined active/passive observations

Roughness-induced emission from ocean surfaces is one of the main issues that affects the retrieval accuracy of sea surface salinity remote sensing.In previous studies,the correction of roughness effect mainly depended on wind speeds retrieved from scatterometers or those provided by other means,which necessitates a high requirement for accuracy and synchronicity of wind-speed measurements.The aim of this study is to develop a novel roughness correction model of ocean emissivity for the salinity retrieval application.The combined active/passive observations of normalized radar cross-sections(NRCSs)and emissivities from ocean surfaces given by the L-band Aquarius/SAC-D mission,and the auxiliary wind directions collocated from the National Centers for Environmental Prediction(NCEP)dataset are used for model development.The model is validated against the observations and the Aquarius standard algorithms of roughness-induced emissivity correction.Comparisons between model computations and measurements indicate that the model has better accuracy in computing wind-induced brightness temperature in the upwind/downwind directions or for the surfaces with smaller NRCSs,which can be better than 0.3 K.However,for crosswind directions and larger NRCSs,the model accuracy is relatively low.A model using HH-polarized NRCSs yields better accuracy than that using VV-polarized ones.For a fair comparison to the Aquarius standard algorithms using wind speeds retrieved from multi-source data,the maximum likelihood estimation is employed to produce results combining our model calculations and those using other sources.Numerical simulations show that combined results basically have higher accuracy than the standard algorithms.

Successful Applications of Generic Atmospheric Correction Online Service for InSAR (GACOS) to the Reduction of Atmospheric Effects on InSAR Observations

The tremendous development of Synthetic Aperture Radar(SAR)missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series.However,this poses greater challenges for correcting atmospheric effects due to the wider coverage of SAR imagery than ever.Previous attempts have used observations from Global Positioning System(GPS)and Numerical Weather Models(NWMs)to separate atmospheric delays,but they are limited by(1)The availability(and distribution)of GPS stations;(2)The low spatial resolution of NWM;And(3)The difficulties in quantifying their performance.To overcome these limitations,we have developed the Generic Atmospheric Correction Online Service for InSAR(GACOS)which utilizes the high-resolution European Centre for Medium-Range Weather Forecasts(ECMWF)products using an Iterative Tropospheric Decomposition(ITD)model.This enables the reduction of the coupling effects of the troposphere turbulence and stratification and hence achieves equivalent performances over flat and mountainous terrains.GACOS comprises a range of notable features:(1)Global coverage;(2)All-weather,all-time usability;(3)Available with a maximum of two-day latency;And(4)Indicators available to assess the model’s performance and feasibility.In this paper,we demonstrate some successful applications of the GACOS online service to a variety of geophysical studies.

Curative effect observation on deformed auricle treated with EarWell Infant Ear Correction System with modular parents'nursing education

Objective:To investigate the efficacy and patient satisfaction of the EarWell Infant Ear Correction System combined with modular parents'nursing education's curative effect on deformed auricle.Methods:A total of 42 patients(29 boys and 13 girls;73 ears;age≤3 months)with auricle deformities who had received EarWell Infant Ear Correction System's treatment and modular parents'nursing education in Guangzhou Children and Women's Medical Center between April and October 2018.The modular parents'education program is standardized by EarWell system.Physician and patients'parents compared the severity of auricle deformity separately before and after the treatment by using the auricle deformities visual analogue scales(VAS)rating system.Patient satisfaction was evaluated by using global aesthetic improvement scale(GAIS).The data collected of auricle deformities VAS and GAIS satisfaction score were applied to measure the treatment's effectiveness.Results:All the 42 patients(73 external ears)completed the treatment with EarWell Infant Ear Correction System and modular parents'nursing education.The mean age at initiation of treatment was 37.87±19.44 days and the therapeutic time span was 47.21±17.36 days.At the end of treatment,the physician's and patients'guardians rating of the severity of auricle deformity were significantly improved separately compared to the initial rating(8.33±1.27 vs.6.51±0.84;P<0.005)(5.77±1.59 vs.8.19±2.38 P<0.05).During the treatment and parents'home nursing care period,the side effect and complications were minor like skin eczema and irrigation;there were no severe complications such as necrosis of the skin and cartilage.The patient tolerance for the treatment was acceptable with the adequate parents'nursing care.Most patients'guardians were satisfied with the treatment outcomes of EarWell Infant Ear Correction System with more engagement of nursing care,the GAIS's rating were increased from pretreatment stage's 26.19%to treatment completed stage's 90.48%,and the difference was statistically significant(P<0.05).Conclusions:In this study,we proved that EarWell Infant Ear Correction System with its unique parents'modular nursing care education,as a noninvasive treatment,reasonably improved auricle morphological malformation,and patients'guardians satisfaction with few complications,which is worthy of a wildly clinical promotion.

Correction of Observation Interference on Z component of Geomagnetic Field From DC Power Lines

为减小直流输电线路对地磁场观测的干扰,采用数学计算的方法精确求解了线路对地磁Z分量的干扰水平。以观测点为原点建立了地磁仪器观测点坐标系,推导了观测点坐标系各坐标轴在地心坐标系中的单位矢量表达式。根据空间矢量点积的定义,得到了空间电流磁场矢量投影到地磁Z分量方向的求解公式。利用推导的公式和直流线路电流磁场三维计算模型,最终求得直流线路对地磁Z分量观测的干扰水平。由此,开发了＂直流线路对地磁观测干扰校正系统＂,并开展了地磁台站和野外联合地磁观测干扰实验。结果表明,直流线路和地磁观测台站距离不超过10km时,提出的数学模型和计算方法误差不超过5%。

Correction:Nanomaterial-Based Repurposing of Macrophage Metabolism and Its Applications

Following publication of the original article[1],the authors reported an error in the last author’s name,it was mistakenly written as“Jun Den”.The correct author’s name“Jun Deng”has been updated in this Correction.

The application of the strip-shaped cymba conchae orthosis in the nonsurgical correction of complex auricular deformity

Objective: This study aims to evaluate the efficacy and safety of using a strip-shaped cymba conchae orthosis for the nonsurgical correction of complex auricular deformities. Methods: Clinical data were collected from 2020 to 2021 for 6 patients who underwent correction using a stripshaped cymba conchae orthosis. The indications, corrective effects, and complications associated with use of the orthosis were analyzed. Results: There were four indications for treatment: cryptotia with helix adhesion;cryptotia with grade I microtia;cryptotia with excessive helix thickness;and auricular deformity beyond the treatment time window(≥6 months). Excellent corrective effects were observed in all 6 patients. Complications occurred in one patient, who recovered after symptomatic treatment. Conclusion: The use of a strip-shaped cymba conchae orthosis alone or combined with a U-shaped helix orthosis presents a feasible approach for correcting complex auricular deformities or deformities beyond the treatment time window in pediatric patients.

Magnetopause properties at the dusk magnetospheric flank from global magnetohydrodynamic simulations,the kinetic Vlasov equilibrium,and in situ observations--Potential implications for SMILE

We derived the properties of the terrestrial magnetopause(MP)from two modeling approaches,one global–fluid,the other local–kinetic,and compared the results with data collected in situ by the Magnetospheric Multiscale 2(MMS2)spacecraft.We used global magnetohydrodynamic(MHD)simulations of the Earth’s magnetosphere(publicly available from the NASA-CCMC[National Aeronautics and Space Administration–Community Coordinated Modeling Center])and local Vlasov equilibrium models(based on kinetic models for tangential discontinuities)to extract spatial profiles of the plasma and field variables at the Earth’s MP.The global MHD simulations used initial solar wind conditions extracted from the OMNI database at the time epoch when the MMS2 observes the MP.The kinetic Vlasov model used asymptotic boundary conditions derived from the same in situ MMS measurements upstream or downstream of the MP.The global MHD simulations provide a three-dimensional image of the magnetosphere at the time when the MMS2 crosses the MP.The Vlasov model provides a one-dimensional local view of the MP derived from first principles of kinetic theory.The MMS2 experimental data also serve as a reference for comparing and validating the numerical simulations and modeling.We found that the MP transition layer formed in global MHD simulations was generally localized closer to the Earth(roughly by one Earth radius)from the position of the real MP observed by the MMS.We also found that the global MHD simulations overestimated the thickness of the MP transition by one order of magnitude for three analyzed variables:magnetic field,density,and tangential speed.The MP thickness derived from the local Vlasov equilibrium was consistent with observations for all three of these variables.The overestimation of density in the Vlasov equilibrium was reduced compared with the global MHD solutions.We discuss our results in the context of future SMILE(Solar wind Magnetosphere Ionosphere Link Explorer)campaigns for observing the Earth’s MP.

Dynamical Dark Energy in Light of Cosmic Distance Measurements.Ⅱ.A Study Using Current Observations

We extract key information on dark energy from current observations of BAO,OHD and H_(0),and find hints of dynamical behavior of dark energy.In particular,a dynamical dark energy model whose equation of state crosses-1 is favored by observations.We also find that the Universe has started accelerating at a lower redshift than expected.

Correction to“Gut microbiota dysbiosis in Chinese children with type 1 diabetes mellitus:An observational study”

Liu X,Cheng YW,Shao L,Sun SH,Wu J,Song QH,Zou HS,Ling ZX.Gut microbiota dysbiosis in Chinese children with type 1 diabetes mellitus:An observational study.World J Gastroenterol 2021;27(19):2394-2414[PMID:34040330 DOI:10.3748/wjg.v27.i19.2394].In this article,the affiliation of the first author was wrong.Xia Liu,the first author,belonged to Department of Intensive Care Unit,The First Affiliated Hospital,School of Medicine,Zhejiang University,Hangzhou,310003,China.