Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for ...Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.展开更多
Using the method of undetermined function, a set of 12 parameter rectangular plate element with double set parameter and geometry symmetry is constructed. Their consistency error are O(h\+2) , one order higher than...Using the method of undetermined function, a set of 12 parameter rectangular plate element with double set parameter and geometry symmetry is constructed. Their consistency error are O(h\+2) , one order higher than the usual 12 parameter rectangular plate elements.展开更多
PLS （Partial Least Squares regression） is introduced into an automatic estimation of fundamental stellar spectral parameters. It extracts the most correlative spectral component to the parameters （Teff, log g and [...PLS （Partial Least Squares regression） is introduced into an automatic estimation of fundamental stellar spectral parameters. It extracts the most correlative spectral component to the parameters （Teff, log g and [Fe/H]）, and sets up a linear regression function from spectra to the corresponding parameters. Considering the properties of stellar spectra and the PLS algorithm, we present a piecewise PLS regression method for estimation of stellar parameters, which is composed of one PLS model for Teff, and seven PLS models for log g and [Fe/H] estimation. Its performance is investigated by large experiments on flux calibrated spectra and continuum normalized spectra at different signal-to-noise ratios （SNRs） and resolutions. The results show that the piecewise PLS method is robust for spectra at the medium resolution of 0.23 nm. For low resolution 0.5 nm and 1 nm spectra, it achieves competitive results at higher SNR. Experiments using ELODIE spectra of 0.23 nm resolution illustrate that our piecewise PLS models trained with MILES spectra are efficient for O ～ G stars： for flux calibrated spectra, the systematic offsets are 3.8%, 0.14 dex, and -0.09 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.44 dex and 0.38 dex, respectively; for continuum normalized spectra, the systematic offsets are 3.8%, 0.12dex, and -0.13 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.49 dex and 0.41 dex, respectively. The PLS method is rapid, easy to use and does not rely as strongly on the tightness of a parameter grid of templates to reach high precision as Artificial Neural Networks or minimum distance methods do.展开更多
目的探讨小而密低密度脂蛋白胆固醇(small dense low density lipoprotein-cholesterol,sdLDL-C)水平及其比值与2型糖尿病患者血糖控制程度的相关性。方法回顾性选取2023年9月—2024年8月在江苏省太湖康复医院体检的2683例糖尿病患者的...目的探讨小而密低密度脂蛋白胆固醇(small dense low density lipoprotein-cholesterol,sdLDL-C)水平及其比值与2型糖尿病患者血糖控制程度的相关性。方法回顾性选取2023年9月—2024年8月在江苏省太湖康复医院体检的2683例糖尿病患者的临床资料,依据糖化血红蛋白及空腹血糖水平将血糖控制程度分为理想组、良好组及不佳组,采用分层随机抽样方法每组纳入患者100例。分析3组sdLDL-C、sdLDL-C/低密度脂蛋白胆固醇(low density lipoprotein-cholesterol,LDL-C)、sdLDL-C/高密度脂蛋白胆固醇(high density lipoprotein-cholesterol,HDL-C)及sdLDL-C/载脂蛋白B(apolipoprotein,ApoB)的水平,并采用Pearson相关系数分析sdLDL-C及其比值与2型糖尿病患者血糖控制程度的相关性。结果3组sdLDL-C、sdLDL-C/HDL-C、sdLDL-C/LDL-C比较,差异均有统计学意义(P均<0.05)。3组sdLDL-C/ApoB比较,差异无统计学意义(P>0.05)。sdLDL-C、sdLDL-C/HDL-C与2型糖尿病血糖控制程度呈正相关,sdLDL-C/LDL-C与2型糖尿病血糖控制程度无明显相关性。结论sdLDL-C水平及其sdLDL-C/HDL-C与2型糖尿病患者血糖控制程度存在一定的相关性。展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 41705082, 41475101, 41690122(41690120))a Chinese Academy of Sciences Strategic Priority Project-the Western Pacific Ocean System (Grant Nos. XDA11010105 and XDA11020306)+1 种基金the National Programme on Global Change and Air–Sea Interaction (Grant Nos. GASI-IPOVAI06 and GASI-IPOVAI-01-01)the China Postdoctoral Science Foundation, and a Qingdao Postdoctoral Application Research Project
文摘Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.
文摘Using the method of undetermined function, a set of 12 parameter rectangular plate element with double set parameter and geometry symmetry is constructed. Their consistency error are O(h\+2) , one order higher than the usual 12 parameter rectangular plate elements.
基金Supported by the National Natural Science Foundation of China
文摘PLS （Partial Least Squares regression） is introduced into an automatic estimation of fundamental stellar spectral parameters. It extracts the most correlative spectral component to the parameters （Teff, log g and [Fe/H]）, and sets up a linear regression function from spectra to the corresponding parameters. Considering the properties of stellar spectra and the PLS algorithm, we present a piecewise PLS regression method for estimation of stellar parameters, which is composed of one PLS model for Teff, and seven PLS models for log g and [Fe/H] estimation. Its performance is investigated by large experiments on flux calibrated spectra and continuum normalized spectra at different signal-to-noise ratios （SNRs） and resolutions. The results show that the piecewise PLS method is robust for spectra at the medium resolution of 0.23 nm. For low resolution 0.5 nm and 1 nm spectra, it achieves competitive results at higher SNR. Experiments using ELODIE spectra of 0.23 nm resolution illustrate that our piecewise PLS models trained with MILES spectra are efficient for O ～ G stars： for flux calibrated spectra, the systematic offsets are 3.8%, 0.14 dex, and -0.09 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.44 dex and 0.38 dex, respectively; for continuum normalized spectra, the systematic offsets are 3.8%, 0.12dex, and -0.13 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.49 dex and 0.41 dex, respectively. The PLS method is rapid, easy to use and does not rely as strongly on the tightness of a parameter grid of templates to reach high precision as Artificial Neural Networks or minimum distance methods do.
文摘目的探讨带线锚钉重建三角韧带(deltoid ligament)对踝关节骨折合并韧带损伤患者多维运动功能的影响。方法采用回顾性研究方法,纳入2023年3月至2024年3月期间在医院接受切开复位内固定术治疗的DL损伤合并关节骨折患者共210例。根据是否接受三角韧带重建分为重建组(110例)和对照组(单纯骨折固定,100例),其中重建组失访4例,对照组失访2例。比较两组术后优良率,并于术前及术后3、6、12个月评估六自由度(Six Degrees of Freedom,6DOF)运动参数、美国足踝外科协会评分(AOFAS)、疼痛视觉模拟评分(VAS)及影像学指标(间踝间隙和距骨倾斜角),同时记录术后并发症发生率。结果重建组手术时间、术中出血量和住院时间均显著高于对照组(P<0.001)。术后12个月,重建组优良率显著高于对照组(93.40%vs.81.63%,P<0.05)。两组术后所有评估指标随时间持续改善,且重建组在踝关节6DOF运动参数(内旋/外旋、背伸/跖屈、内翻/外翻、上移/下移、内移/外移、前移/后移)、AOFAS评分及VAS评分方面改善程度均优于对照组(P<0.001)。影像学结果显示,重建组间踝间隙及距骨倾斜角恢复更佳(P<0.001)。两组术后并发症发生率差异无统计学意义(P>0.05)。结论在关节骨折合并三角韧带损伤的治疗中,带线锚钉重建三角韧带可有效改善踝关节运动功能,提高AOFAS评分,减轻疼痛,促进影像学复位,且不增加术后并发症风险,是治疗此类损伤的安全有效方法。
文摘目的探讨小而密低密度脂蛋白胆固醇(small dense low density lipoprotein-cholesterol,sdLDL-C)水平及其比值与2型糖尿病患者血糖控制程度的相关性。方法回顾性选取2023年9月—2024年8月在江苏省太湖康复医院体检的2683例糖尿病患者的临床资料,依据糖化血红蛋白及空腹血糖水平将血糖控制程度分为理想组、良好组及不佳组,采用分层随机抽样方法每组纳入患者100例。分析3组sdLDL-C、sdLDL-C/低密度脂蛋白胆固醇(low density lipoprotein-cholesterol,LDL-C)、sdLDL-C/高密度脂蛋白胆固醇(high density lipoprotein-cholesterol,HDL-C)及sdLDL-C/载脂蛋白B(apolipoprotein,ApoB)的水平,并采用Pearson相关系数分析sdLDL-C及其比值与2型糖尿病患者血糖控制程度的相关性。结果3组sdLDL-C、sdLDL-C/HDL-C、sdLDL-C/LDL-C比较,差异均有统计学意义(P均<0.05)。3组sdLDL-C/ApoB比较,差异无统计学意义(P>0.05)。sdLDL-C、sdLDL-C/HDL-C与2型糖尿病血糖控制程度呈正相关,sdLDL-C/LDL-C与2型糖尿病血糖控制程度无明显相关性。结论sdLDL-C水平及其sdLDL-C/HDL-C与2型糖尿病患者血糖控制程度存在一定的相关性。
