The Study of Helium Variations in Star Clusters Using China Space Station Telescope

The China Space Station Telescope(CSST)is a 2 m space-based optical-UV telescope.Its primary goal is to carry out a high-resolution photometric imaging survey of a 17,500 square degree sky area using the on board Survey Camera.With its wide field of view(1.1 square degrees)and a mosaic imager containing 640 million pixels,studying the different populations of stars within star clusters is highly feasible.The aim of this study is to assess the CSST's ability to distinguish between stellar populations with varying helium abundance levels,with the help of Modules for Experiments in Stellar Astrophysics.The results of the CSST's photometry for these different populations are presented by transferring the models into the CSST Survey Camera photometric system.The findings confirm that helium-enriched stellar populations will have unique patterns in the color-magnitude diagrams under the CSST photometric system,compared to normal stellar populations.The CSST,with its filters and wide field of view of the Survey Camera,provides a new avenue for the study of multiple populations in star clusters.

Development of advanced anion exchange membrane from the view of the performance of water electrolysis cell

Green hydrogen produced by water electrolysis combined with renewable energy is a promising alternative to fossil fuels due to its high energy density with zero-carbon emissions.Among water electrolysis technologies,the anion exchange membrane(AEM) water electrolysis has gained intensive attention and is considered as the next-generation emerging technology due to its potential advantages,such as the use of low-cost non-noble metal catalysts,the relatively mature stack assembly process,etc.However,the AEM water electrolyzer is still in the early development stage of the kW-level stack,which is mainly attributed to severe performance decay caused by the core component,i.e.,AEM.Here,the review comprehensively presents the recent progress of advanced AEM from the view of the performance of water electrolysis cells.Herein,fundamental principles and critical components of AEM water electrolyzers are introduced,and work conditions of AEM water electrolyzers and AEM performance improvement strategies are discussed.The challenges and perspectives are also analyzed.

The Impact of Bias Row Noise to Photometric Accuracy:Case Study Based on a Scientific CMOS Detector

We tested a new model of CMOS detector manufactured by the Gpixel Inc,for potential space astronomical application.In laboratory,we obtain some bias images under the typical application environment.In these bias images,clear random row noise pattern is observed.The row noise also contains some characteristic spatial frequencies.We quantitatively estimated the impact of this feature to photometric measurements,by making simulated images.We compared different bias noise types under strict parameter control.The result shows the row noise will significantly deteriorate the photometric accuracy.It effectively increases the readout noise by a factor of2-10.However,if it is properly removed,the image quality and photometric accuracy will be significantly improved.

原发性获得性鼻泪管阻塞对泪膜及眼表的影响

目的:利用LipiView眼表面干涉仪和Keratograph 5M眼前节分析仪观察原发性获得性鼻泪管阻塞(PANDO)对泪膜及眼表的影响。方法:自身对照临床试验研究。将2021-09/2022-03我科收治的单侧PANDO且病程在6mo以上的患者40例纳入研究,以健眼作为对照。采用LipiView眼表面干涉仪和Keratograph 5M眼前节分析仪测量并分析双眼泪膜及眼表相关参数的差异。结果:纳入患者患眼非侵入性泪河高度(NITMH)、刺激后NITMH、上睑板腺缺失率、鼻颞侧睫状眼红指数、颞侧结膜眼红指数均高于健眼(P<0.05),但双眼非侵入性泪膜破裂时间(NIBUT)、下睑板腺缺失率、鼻侧结膜眼红指数、干眼分级、眨眼次数、不完全眨眼率、泪膜脂质层厚度(LLT)均无差异(P>0.05)。结论:PANDO可能导致眼表炎症加重及上睑板腺缺失,损害患者眼表健康,应重视早期PANDO的治疗。

基于LSTM-BO和SPRT的风电机组故障演化过程分析

有效挖掘故障演化的过程有利于分析和总结故障传播规律。本文提出了基于LSTM-BO模型和SPRT算法,利用SCADA历史数据研究风电机组早期故障演化过程的分析方法。首先使用Pearson相关系数法挖掘SCADA数据各监测变量之间的映射关系,获得LSTM-BO网络所需的输入—输出关系对;其次是依赖LSTM网络强大的时序特征提取能力,将预处理后的SCADA数据送入LSTM网络进行训练,从而得到相应的正常行为模型;最后,依赖SPRT在序贯测试方面的优势,将各监测变量模型预测值与实际监测值之间的偏差看作序贯测试的对象,并对其测试结果进行滑动窗口观测,以异常点数目占观测窗口宽度的比值为度量指标,得到SCADA数据部分重要监测变量在故障发生前的演化过程。实例分析结果表明,所提方法能够有效提取故障演化的过程,为后续演化规律的分析提供指导。

Perioperative Risk Factors for Post-operative Pneumonia after Type A Acute Aortic Dissection Surgery

Objective Type A acute aortic dissection(TAAAD)is a dangerous and complicated condition with a high death rate before hospital treatment.Patients who are fortunate to receive prompt surgical treatment still face high in-hospital mortality.A series of post-operative complications further affects the prognosis.Post-operative pneumonia(POP)also leads to great morbidity and mortality.This study aimed to identify the prevalence as well as the risk factors for POP in TAAAD patients and offer references for clinical decisions to further improve the prognosis of patients who survived the surgical procedure.Methods The study enrolled 89 TAAAD patients who underwent surgical treatment in Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan,Hubei province,China from December 2020 to July 2021 and analyzed the perioperative data and outcomes of these patients.Logistic regression analyses were used to identify the risk factors for POP.Results In the study,31.5%of patients developed POP.Patients with POP had higher proportions of severe oxygenation damage,pneumothorax,reintubation,tracheotomy,renal replacement therapy,arrhythmia,gastrointestinal bleeding,and longer duration of mechanical ventilation,fever,ICU stay,and length of stay(all with P<0.05).The in-hospital mortality was 2.3%.Smoking,preoperative white blood cells,and intraoperative transfusion were the independent risk factors for POP in TAAAD.Conclusion Patients who underwent TAAAD surgery suffered poorer outcomes when they developed POP.Furthermore,patients with risk factors should be treated with caution.

Physical Activity,Sedentary Behavior,and the Risk of Cardiovascular Disease in Type 2 Diabetes Mellitus Patients:The MIDiab Study

The aim of this study was to explore the associations of moderate-to-vigorous-intensity physical activity(MVPA)time and sedentary(SED)time with a history of cardiovascular disease(CVD)and multifactorial(i.e.,blood pressure(BP),body mass index(BMI),low-density lipoprotein cholesterol(LDL-C),and glycated hemoglobin A1c(HbA1c))control status among type 2 diabetes mellitus(T2DM)patients in China.A cross-sectional analysis of 9152 people with type 2 diabetes from the Multifactorial Intervention on Type 2 Diabetes(MIDiab)study was performed.Patients were grouped according to their self-reported MVPA time(low,<150 min·week−1;moderate,150 to<450 min·week−1;high,≥450 min·week−1)and SED time(low,<4 h·d–1;moderate,4 to<8 h·d–1;high,≥8 h·d–1).Participants who self-reported a history of CVD were identified as having a CVD risk.Odds ratios(ORs)and 95%confidence intervals(CIs)of CVD risk and multifactorial control status associated with MVPA time and SED time were estimated using mixed-effect logistic regression models,adjusting for China’s geographical region characteristics.The participants had a mean±standard deviation(SD)age of(60.87±8.44)years,44.5%were women,and 25.1%had CVD.After adjustment for potential confounding factors,an inverse association between high MVPA time and CVD risk that was independent of SED time was found,whereas this association was not observed in the moderate-MVPA group.A higher MVPA time was more likely to have a positive effect on the control of BMI.Compared with the reference group(i.e.,those with MVPA time≥450 min·week−1 and SED time<4 h·d–1),CVD risk was higher in the low-MVPA group:The OR associated with an SED time<4 h·d–1 was 1.270(95%CI,1.040–1.553)and that associated with an SED time≥8 h·d–1 was 1.499(95%CI,1.149–1.955).We found that a high MVPA time(i.e.,≥450 min·week−1)was associated with lower odds of CVD risk regardless of SED time among patients with T2DM.

A study of the influence of different grid structures on plasma characteristics in the discharge chamber of an ion thruster

The grid structure has significant effects on the discharge characteristics of an ion thruster.The discharge performances of a 30 cm diameter ion thruster with flat,convex and concave grids are studied.The analysis results show that the discharge chamber with a convex grid has a larger’magnetic-field free area’than the others,and the parallelism of the magnetic-field isopotential lines and anode is generally the same in the three models.Plasma densities of the three structures at the grid outlet are in the range of 3.1×1016-6.9×1017m-3.Along the thruster axis direction,the electron temperature in the chamber with the convex and concave grids is in the range of 3.3-3.5 eV,while that with a flat grid is lower,in the range of 3.1-3.5 eV.In addition,the convex and the concave grids have better uniform distribution of electron temperature.Moreover,the collision frequency ratios show that the axial degree of ionization of the three models is the highest,and the flat grid has the highest discharge efficiency,followed by the convex grid and the concave grid is the least efficient.The test and simulation results of the 30 cm diameter ion thruster with the convex grid show that the measurement and calculation results are 3.67 A and 3.44 A,respectively,and the error above mainly comes from the ignorance of the doubly charged ions and parameter settings in the model.The comparison error between the simulation and measurement of beam current density is mainly caused by the actual thermal deformation of the grids during the discharge process,which leads to the change in electric potential distribution and variation of the focusing characteristics of the grids.Upon consideration of discharge performance and the thermal grid gap variation,it can be concluded that the flat and concave grids are more suitable for small-diameter ion thrusters,while the convex grid is a more reasonable choice for the higher-power and larger-diameter thrusters.

Characterization of oral and gut microbiome and plasma metabolomics in COVID-19 patients after 1-year follow-up

Background:Due to the outbreak and rapid spread of coronavirus disease 2019(COVID-19),more than 160 million patients have become convalescents worldwide to date.Significant alterations have occurred in the gut and oral microbiome and metabonomics of patients with COVID-19.However,it is unknown whether their characteristics return to normal after the 1-year recovery.Methods:We recruited 35 confirmed patients to provide specimens at discharge and 1 year later,as well as 160healthy controls.A total of 497 samples were prospectively collected,including 219 tongue-coating,129 stool and 149 plasma samples.Tongue-coating and stool samples were subjected to 16S rRNA sequencing,and plasma samples were subjected to untargeted metabolomics testing.Results:The oral and gut microbiome and metabolomics characteristics of the 1-year convalescents were restored to a large extent but did not completely return to normal.In the recovery process,the microbial diversity gradually increased.Butyric acid-producing microbes and Bifidobacterium gradually increased,whereas lipopolysaccharideproducing microbes gradually decreased.In addition,sphingosine-1-phosphate,which is closely related to the inflammatory factor storm of COVID-19,increased significantly during the recovery process.Moreover,the predictive models established based on the microbiome and metabolites of patients at the time of discharge reached high efficacy in predicting their neutralizing antibody levels one year later.Conclusions:This study is the first to characterize the oral and gut microbiome and metabonomics in 1-year convalescents of COVID-19.The key microbiome and metabolites in the process of recovery were identified,and provided new treatment ideas for accelerating recovery.And the predictive models based on the microbiome and metabolomics afford new insights for predicting the recovery situation which benefited affected individuals and healthcare.

Deep learning for predictive mechanical properties of hot-rolled strip in complex manufacturing systems

Higher requirements for the accuracy of relevant models are put throughout the transformation and upgrade of the iron and steel sector to intelligent production.It has been difficult to meet the needs of the field with the usual prediction model of mechanical properties of hotrolled strip.Insufficient data and difficult parameter adjustment limit deep learning models based on multi-layer networks in practical applications;besides,the limited discrete process parameters used make it impossible to effectively depict the actual strip processing process.In order to solve these problems,this research proposed a new sampling approach for mechanical characteristics input data of hot-rolled strip based on the multi-grained cascade forest(gcForest)framework.According to the characteristics of complex process flow and abnormal sensitivity of process path and parameters to product quality in the hot-rolled strip production,a three-dimensional continuous time series process data sampling method based on time-temperature-deformation was designed.The basic information of strip steel(chemical composition and typical process parameters)is fused with the local process information collected by multi-grained scanning,so that the next link’s input has both local and global features.Furthermore,in the multi-grained scanning structure,a sub sampling scheme with a variable window was designed,so that input data with different dimensions can get output characteristics of the same dimension after passing through the multi-grained scanning structure,allowing the cascade forest structure to be trained normally.Finally,actual production data of three steel grades was used to conduct the experimental evaluation.The results revealed that the gcForest-based mechanical property prediction model outperforms the competition in terms of comprehensive performance,ease of parameter adjustment,and ability to sustain high prediction accuracy with fewer samples.

Poroelastodynamic responses and elastic moduli of a transversely isotropic porous cylinder under forced deformation test

Existing transversely isotropic poroelastodynamics solutions are limited to infinite domains and without experimental validation. Furthermore, there is a lack of analytical simulations for the elastic moduli dispersion of fluid-saturated porous cylinders. To address these three limitations and investigate the mechanisms of moduli dispersion, we present the analytical solutions of the poromechanical responses and the elastic moduli dispersion of a transversely isotropic, fluid-saturated, finite porous cylinder subjected to a forced deformation test. Through an example, we demonstrate the effects of loading frequency, boundary conditions, and material's anisotropy, dimension, and permeability on the responses of pore pressure,force, displacement, and dynamic elastic moduli of the cylinder. The specimen's responses are significantly influenced by the frequency of the applied load, resulting in a drained state at low frequencies and an undrained state at high frequencies. At high frequencies, the sample behaves identically for an open or a closed lateral boundary, and permeability has insignificant effects. The dynamic elastic moduli are mainly controlled by the loading frequency and the ratio of the sample's radius to its height. Lastly,we show excellent matches between the newly derived analytical solution and laboratory measurements on one clay and two shale samples from Mont Terri.

Alterations in the human oral microbiome in cholangiocarcinoma

Dear Editor,Alterations in the human microbiome are closely related to various hepatobiliary diseases.Gut microbial dysbiosis has been found in patients with cholangiocarcinoma(CCA)[1].However,the characteristics of oral microbiome in patients with CCA have not been studied.

Optical anapole modes in hybrid metal–dielectric nanoantenna for near-field enhancement and optical sensing

Metal–dielectric nanostructures in the optical anapole modes are essential for light–matter interactions due to the low material loss and high near-field enhancement. Herein, a hybrid metal–dielectric nanoantenna composed of six wedgeshaped gold(Au) nanoblocks as well as silica(SiO2) and silicon(Si) nanodiscs is designed and analyzed by the finite element method(FEM). The nanoantenna exhibits flexibility in excitation and manipulation of the anapole mode through the strong coupling between the metal and dielectrics, consequently improving the near-field enhancement at the gap. By systematically optimizing the structural parameters, the electric field enhancement factors at wavelengths corresponding to the anapole modes(AM1 and AM2) can be increased to 518 and 1482, respectively. Moreover, the nanoantenna delivers great performance in optical sensing such as a sensitivity of 550 nm/RIU. The results provide guidance and insights into enhancing the coupling between metals and dielectrics for applications such as surface-enhanced Raman scattering and optical sensing.

Impact of seepage flow on sediment resuspension by internal solitary waves:parameterization and mechanism

Sediment incipient motion is the first step in sediment resuspension.Previous studies ignored the effect of seepage flow on the mobility of sediment particles and simplified the seabed surface as a rigid boundary.A flume experiment was designed to innovatively divide the seabed into two parts to control the dynamic response of the seabed and control the seepage conditions.In the experiment,the seabed sediments and the amplitude of internal solitary waves(ISWs)were changed to compare and analyze the impact of seepage flow on the sediment resuspension by shoaling ISWs.Moreover,parametric research and verification were carried out.Results indicate that seepage flow can greatly influence fine sand,promote sediment resuspension,and increase the amount of suspension by two times on average.However,seepage flow had a little effect on the suspension of clayey silt and sandy silt.Besides,seepage force was added to the traditional gravity,drag force,and uplift force,and the parameterization of threshold starting shear stress of coarse-grained sediments was developed.The results of this parameterization were verified,and seepage force was critical to parameterization.The threshold starting shear stress was reduced by 54.6%after increasing the seepage force.The physical mechanism of this process corresponded to the vertical reciprocating transient seepage in and out the seabed interface caused by the wave-induced transient excess pore water pressure.This quantitative study on seepage flow for shear stress of coarse-grained sediments induced by ISWs is critical to geohazard assessment.

The Stellar Spectra Factory(SSF)Based on SLAM

An empirical stellar spectral library with large coverage of stellar parameters is essential for stellar population synthesis and studies of stellar evolution.In this work,we present Stellar Spectra Factory(SSF),a tool to generate empirical-based stellar spectra from arbitrary stellar atmospheric parameters.The relative flux-calibrated empirical spectra can be predicted by SSF given arbitrary effective temperature,surface gravity,and metallicity.SSF constructs the interpolation approach based on the Stellar LAbel Machine,using ATLAS-A library,which contains spectra covering from O type to M type,as the training data set.SSF is composed of four data-driven sub-models to predict empirical stellar spectra.Sub-model SSF-N can generate spectra from A to K type and some M giant stars,covering 3700<T_(eff)<8700 K,0<logg<dex,and-1.5<[M/H]<0.5 dex.Sub-model SSF-gM is mainly used to predict M giant spectra with 3520<T_(eff)<4000 K and-1.5<[M/H]<0.4 dex.Sub-model SSF-dM is for generating M dwarf spectra with 3295<T_(eff)<4040 K,-1.0<[M/H]<0.1 dex.Sub-model SSF-B can predict B-type spectra with 9000<T_(eff)<24,000 K and-5.2<M_(G)<1.5 mag.The accuracy of the predicted spectra is validated by comparing the flux of predicted spectra to those with same stellar parameters selected from the known spectral libraries,MILES and MaStar.The averaged difference of flux over optical wavelength between the predicted spectra and the corresponding ones in MILES and MaStar is less than 5%.More verification is conducted between the magnitudes calculated from the integration of the predicted spectra and the observations in PS1 and APASS bands with the same stellar parameters.No significant systematic difference is found between the predicted spectra and the photometric observations.The uncertainty is 0.08 mag in the r band for SSF-gM when comparing with the stars with the same stellar parameters selected from PS1.The uncertainty becomes 0.31 mag in the i band for SSF-dM when comparing with the stars with the same stellar parameters selected from APASS.

Atmospheric Parameters and Kinematic Information for the M Giant Stars from LAMOST DR9

A catalog of more than 43,000 M giant stars has been selected by Li et al.from the ninth data release of LAMOST.Using the data-driven method SLAM,we obtain the stellar parameters(T_(eff),logg,[M/H],[α/M])for all the M giant stars with uncertainties of 57 K,0.25 dex,0.16 dex and 0.06 dex at SNR>100,respectively.With those stellar parameters,we constrain the absolute magnitude in the K-band,which brings distance with relative uncertainties around 25%statistically.Radial velocities are also calculated by applying cross correlation on the spectra between 8000 and 8950?with synthetic spectra from ATLAS9,which covers the CaⅡtriplet.Comparison between our radial velocities and those from APOGEE DR17 and Gaia DR3 shows that our radial velocities have a system offset and dispersion around 1 and 4.6 km s^(-1),respectively.With the distances and radial velocities combining with the astrometric data from Gaia DR3,we calculate the full 6D position and velocity information,which are able to be used for further chemo-dynamic studies on the disk and substructures in the halo,especially the Sagittarius Stream.

Classifying Globular Clusters and Applying them to Estimate the mass of the Milky Way

We combine the kinematics of 159 globular clusters(GCs) provided by the Gaia Early Data Release 3(EDR3) with other observational data to classify the GCs,and to estimate the mass of the Milky Way(MW).We use the agemetallicity relation,integrals of motion,action space and the GC orbits to identify the GCs as either formed in situ(Bulge and Disk) or ex situ(via accretion).We find that 45.3% have formed in situ,while 38.4% may be related to known merger events:Gaia-Sausage-Enceladus,the Sagittarius dwarf galaxy,the Helmi streams,the Sequoia galaxy and the Kraken galaxy.We also further identify three new sub-structures associated with the Gaia-Sausage-Enceladus.The remaining 16.3% of GCs are unrelated to the known mergers and thought to be from small accretion events.We select 46 GCs which have radii 8.0 <r<37.3 kpc and obtain the anisotropy parameter β=0.315_(-0.049)^(+0.055),which is lower than the recent result using the sample of GCs in Gaia Data Release 2,but still in agreement with it by considering the error bar.By using the same sample,we obtain the MW mass inside the outermost GC as M(<37.3 kpc)=0.423_(-0.02)^(+0.02)×10^(12)M_(⊙),and the corresponding M_(200)=1.11_(-0.18)^(+0.25)×10^(12)M_(⊙).The estimated mass is consistent with the results in many recent studies.We also find that the estimated β and mass depend on the selected sample of GCs.However,it is difficult to determine whether a GC fully traces the potential of the MW.

A cloud optical and microphysical property product for the advanced geosynchronous radiation imager onboard China's Fengyun-4 satellites: The first version

风云四号作为中国新一代静止气象卫星,提供了高时空分辨率的监测产品。本文介绍风云四号搭载的先进地球同步轨道辐射成像仪AGRI的云光学和微物理特性产品.该产品包含了基于双光谱通道反演的云光学厚度和云粒子有效半径产品,以及基于机器学习的云识别和云相态产品。与时空匹配的主动卫星观测结果对比显示,该产品的云识别和云相态的准确率分别在95%和85%;该产品提供的云光学厚度和云有效粒径与经典的MODIS产品的相关系数达到0.76和0.63.团队将持续优化和更新该云光学和微物理特性定量产品,服务风云四号卫星定量应用。

A Multi-Domain Compression Radiative Transfer Model for the Fengyun-4 Geosynchronous Interferometric Infrared Sounder (GIIRS)

Forward radiative transfer(RT)models are essential for atmospheric applications such as remote sensing and weather and climate models,where computational efficiency becomes equally as important as accuracy for high-resolution hyperspectral measurements that need rigorous RT simulations for thousands of channels.This study introduces a fast and accurate RT model for the hyperspectral infrared(HIR)sounder based on principal component analysis(PCA)or machine learning(i.e.,neural network,NN).The Geosynchronous Interferometric Infrared Sounder(GIIRS),the first HIR sounder onboard the geostationary Fengyun-4 satellites,is considered to be a candidate example for model development and validation.Our method uses either PCA or NN(PCA/NN)twice for the atmospheric transmittance and radiance,respectively,to reduce the number of independent but similar simulations to accelerate RT simulations;thereby,it is referred to as a multi-domain compression model.The first PCA/NN gives monochromatic gas transmittance in both spectral and atmospheric pressure domains for each gas independently.The second PCA/NN is performed in the traditional spectral radiance domain.Meanwhile,a new method is introduced to choose representative variables for the PCA/NN scheme developments.The model is three orders of magnitude faster than the standard line-by-line-based simulations with averaged brightness temperature difference(BTD)less than 0.1 K,and the compressions based on PCA or NN methods result in comparable efficiency and accuracy.Our fast model not only avoids an excessively complicated transmittance scheme by using PCA/NN but is also highly flexible for hyperspectral instruments with similar spectral ranges simply by updating the corresponding spectral response functions.

LAMOST medium-resolution spectroscopic survey of binarity and exotic star(LAMOST-MRS-B):Observation strategy and target selection

LAMOST-MRS-B is one of the sub-surveys of LAMOST medium-resolution(R~7500)spectroscopic survey.It aims at studying the statistical properties(e.g.,binary fraction,orbital period distribution,mass ratio distribution)of binary stars and exotic stars.We intend to observe about 30000 stars(10 mag≤G<14.5 mag)with at least 10 visits in five years.We first planned to observe 25 plates around the galactic plane in 2018.Then the plates were reduced to 12 in 2019 because of the limitation of observation.At the same time,two new plates located at the high galactic latitude were added to explore binary properties influenced by the different environments.In this survey project,we set the identified exotic and low-metallicity stars with the highest observation priorities.For the rest of the selected stars,we gave the higher priority to the relatively brighter stars in order to obtain high quality spectra as many as possible.Spectra of49129 stars have been obtained in LAMOST-MRS-B field and released in DR8,of which 28828 and 3375 stars have been visited more than twice and ten times with SNR≥10,respectively.Most of the sources are B-,A-,and F-type stars with-0.6<[Fe/H]<0.4 dex.We also obtain 347 identified variable and exotic stars and about 250 stars with[Fe/H]<-1 dex.We measure radial velocities(RVs)by using 892233 spectra of the stars.The uncertainties of RV achieve about 1 km·s^(-1)and 10 km·s^(-1)for 95%of late-and early-type stars,respectively.The datasets presented in this paper are available at http://www.doi.org/10.57760/sciencedb.j00113.00035.