Estimation of global subsurface temperature anomaly based on multisource satellite observations

基于表层卫星遥感观测的中深层海洋遥感对于了解海洋内部异常及其动力过程有重要意义。如何从现有的海洋表层遥感观测资料提取海洋内部关键动力环境信息场是; 具有挑战性的海洋遥感技术前沿。本文采用支持向量回归(SVR)方法,通过卫星遥感观测获取的多源海表参量(海表高度异常(SSHA)、海表温度异常(S; STA)、海表盐度异常(SSSA)和海表风场异常(SSWA)),选择最优参量输入组合,感知海洋次表层温度异常(STA),并用实测Argo数据作精; 度验证。结果表明SVR模型可准确估算全球尺度的STA(1000; m深度以浅);当SVR输入变量为2个(SSHA、SSTA)、3个(SSHA、SSTA、SSSA)、4个(SSHA、SSTA、SSSA、SSWA); 时对应的平均均方差(MSE)分别为0.0090、0.0086、0.0087,平均决定系数(R~2)分别为0.443、0.457、0.485。因此; ,除了SSHA和SSTA外,SSSA与SSWA的输入对SVR模型的估算有积极影响,有助于提高STA的估算精度。在全球增暖与减缓背景下,该研究可为; 从表层卫星遥感观测提取海洋内部热力异常信息研究提供重要技术支持,有利于拓展卫星对海观测范围。Subsurface thermal structure of the global ocean is a key factor that; reflects the impact of global climate variability and change. Accurately; determining and describing the global subsurface and deeper ocean; thermal structure from satellite measurements are becoming even more; important for understanding the ocean interior anomaly and dynamic; processes during recent global warming and hiatus. The extent to which; such surface remote sensing observations can be used to develop; information about the global ocean interior is essential but; challenging. This work proposes a Support Vector Regression (SVR); method, a popular machine learning method for data regression used to; estimate Subsurface Temperature Anomaly (STA) in the global ocean. The; SVR model can well estimate the global STA upper 1000 m through a suite; of satellite remote sensing observations of sea surface parameters; [including Sea Surface Height Anomaly (SSHA), Sea Surface Temperature; Anomaly (SSTA), Sea Surface Salinity Anomaly (SSSA), and Sea Surface; Wind Anomaly (SSWA)] with in situ Argo data for training and testing at; different depth levels. In this study, we employed the Mean Squared; Error (MSE) and squared correlation coefficient (R~2) to assess the; performance of SVR on STA estimation. Results from the SVR model were; validated to test the accuracy and reliability using the worldwide Argo; STA data (upper 1000 m depth). The average MSE and R~2 of the 15 levels; are 0.0090/0.0086/0.0087 and 0.443/0.457/0.485 for two attributes (SSHA,; SSTA)/three attributes (SSHA, SSTA, SSSA)/four attributes (SSHA, SSTA,; SSSA, SSWA) SVR, respectively. The estimation accuracy was improved by; including SSSA and SSWA for SVR input (MSE decreased by 0.4%/0.3% and; R~2 increased by 1.4%/4.2% on average). The estimation accuracy; gradually decreased with the increase in depth from 500 m. With the; increase in depth, the absolute value of STA became smaller, i.e., it; became more indistinctive in the spatial heterogeneity. The STA became; less intensive in the deeper ocean due to the water stratification and; stability. Results showed that SSSA and SSWA, in addition to SSTA and; SSHA, are useful parameters that can help estimate the subsurface; thermal structure and improve the STA estimation accuracy. Moreover, an; obvious advantage for SVR is the absence of limitation on the input of; sea surface parameters. Therefore, we can figure out more potential and; useful sea surface parameters from satellite remote sensing as input; attributes to further improve the STA sensing accuracy from SVR machine; learning. This study provides a helpful technique for studying thermal; variability in the ocean interior, which has played an important role in; recent global warming and hiatus from satellite observations over global; scale.国家自然科学基金; 国家海洋局全球变化与海气相互作用专项; 国家自然科学基金; 国家自然科学基金; 福建省自然科学基金;; 中国博士后科学基金面上资助; 海西政务大数据应用协同创新中心资

Rapid Quality Control of Licorice in Its GAP Research

目的　建立甘草 GAP过程中的快速质量检验方法 ,为甘草药材的快速质量检测提供方法依据。方法　提出甘草中水溶性有效物质群的概念并建立其含量的比色测定方法。以甘草酸作为定量的标准物质 ,采用香草醛 -浓硫酸试剂作显色剂 ,用便携式小型光谱仪于 5 6 0 nm处检测。结果　回归方程为 Y=1.174 7C+0 .0 873,相关系数 r=0 .970 5 (n=3) ,回收率为 92 %～ 99% ,在 0 .0～ 0 .96 mg/m L 范围内仪器读数与甘草酸浓度呈线性关系。结论　该方法简单、快速、廉价 ,能够准确地反映甘草质量的优劣 ,适合在准确度要求相对较低的甘草生产基地推广使用Objective To develop a rapid method for the quality control of licorice in its GAP research.Methods Water-soluble triterpenoid saponins were defined as the active fraction in licorice and a colorimetric method using LED-based portable device has been developed for the first time to measure the content of this active fraction. The method was based on the specific color reaction occurring between triterpenoid saponins and vanillin-sulfuric acid reagent. Visible light absorption of 560 nm was chosen as the detection wavelength.Results The operating calibration curve(Y=1.174 7C +0.087 3 mg/mL) was found to be linear at the range of 0.0～0.96 mg/mL glycyrrhizic acid in water (r=0.970 5). The recovery is 92～99%.Conclusion The method is simple, rapid and low-cost and is recommendable to evaluate the quality of Glycyrrhiza uralensis Fisch. in its GAP research.内蒙梁外甘草 GAP研究与开发;; 国家自然科学基金 2 0 0 3重点项目 ( 2 0 2 3 5 0 2 0

全球海洋次表层温度异常遥感反演的季节时空变化特征

卫星遥感反演海洋内部多时相、大尺度热力结构信息对于了解海洋内部复杂、多维的动力过程有重要意义。本文采用随机森林回归模型,利用卫星遥感观测的海表参量(海表高度异常(SSHA)、海表温度异常(SSTA)、海表盐度异常(SSSA)和海表风场异常(SSWA)),反演不同季节、不同深度层位(1000 m深度以上)的海洋次表层温度异常(STA),并用Argo实测数据作精度验证,采用均方根误差(RMSE)、归一化均方根误差(NRMSE)以及决定系数(R2)评价模型在全球及洋盆尺度上的反演精度。结果显示,全球海洋16个深度层位的平均R2在春、夏、秋、冬四季分别为0.53、0.60、0.54、0.66,NRMSE分别为0.051、0.031、0.043、0.044。随着季节的变化,模型反演性能有所波动。模型在印度洋的反演效果最佳,不同季节、不同深度层位上的平均R2和RMSE分别为0.71和0.18℃,而大西洋的反演精度最低,平均R2和RMSE分别为0.46和0.25℃。研究表明随机森林模型适用于全球不同季节的STA遥感反演,且在不同洋盆上均有较好的反演效果;不同季节上,上层STA有明显变化信号,空间异质性显著,但300 m以深,STA信号较弱且基本不随季节变化。本研究可为长时序、大尺度海洋内部参量信息遥感反演与重建提供依据,有助于进一步发展深海遥感方法。国家自然科学基金(编号:41971384,41601444,41630963)福建省高校杰出青年科研人才培育计划(编号:KJ2017-17)福建省自然科学基金(编号:2017J01657)海西政务大数据应用协同创新中心资助(编号:2015750401)中央引导地方科技发展专项(编号:2017L3012)~

Study on Optimal Harvest Time of Semi-wild Glycyrrhiza uralensis at Liangwai,Inner Mongolia

目的 :研究甘草中甘草酸的积累动态 ,确定内蒙古梁外地区育苗移栽的半野生甘草最佳采收期。方法 :用HPLC法测定不同时间采集的不同株龄的半野生甘草中甘草酸含量。结果 :甘草中甘草酸含量 6～ 7月份最高 ,8月份开始逐渐降低 ,11～ 12月最低 ,翌年 3～ 4月份开始逐渐增加 ,直到 6～ 7月份达最高峰 ;甘草在移栽后的前三年 ,甘草酸含量无明显增加 ,第四年的各个月份的甘草酸含量均远大于头三年。结论 :育苗移栽的半野生甘草的最佳采收期为移栽后的第四年 7～ 8月份Objective: To study the dynamic accumulation of glycyrrhizic acid(GA) in semi wild Glycyrrhiza uralensis Fisch. so as to determine its optimal harvest time Methods: The content of GA in the plant samples was determined by HPLC Results: In the same growth period, the content of GA in the plant reached its highest peak in June or July, decreased gradually from August, and reached the lowest in November or December. Then the content of GA increased gradually from next March, and finally reached the highest in June or July again There was no obvious difference between the content of GA in the one year old and the two year old Glycyrrhiza uralensis But the content of GA in the three year old increased markedly, and its GA content was much higher than that of the one or two year old Conclusion:The optimal harvest time of semi wild Glycyrrhiza uralensis is in July or August after transplanted three years国家自然科学基金 2 0 0 3年重点项目( 2 0 2 3 5 0 2 0

The psychological experience of female caregivers of stroke patients in the rehabilitation period: A qualitative research (脑卒中康复期患者的女性照顾者心理体验的质性研究)

Objective To explore the psychological experience and needs of female caregivers of stroke patients in rehabilitation period. Methods The phenomenological research method was used to conduct semi-structured interviews with 12 female caregivers of stroke patients. Results Based on the real experience of female caregivers during stroke rehabilitation period, four themes were extracted, including imbalance in physical and mental health, coping with multiple roles, insufficient of nursing information acquisition and lack of social support. Conclusion The feelings of female caregivers of patients in stroke rehabilitation stage are multi-dimensional, suggesting that we should pay attention to the mental health of female caregivers and guide them to seek positive coping styles, so as to provide better care for the rehabilitation of stroke patients. (目的 探讨脑卒中康复期患者的女性照顾者的照顾心理体验及需求。方法 采用现象学研究方法, 对12例脑卒中康复期患者的女性照顾者进行半结构式访谈, 采用质性研究的类属法进行整理和分析。结果 根据脑卒中康复期女性照顾者的真实体验提炼出4个主题: 身心健康失衡、多重角色应对失调、护理信息获取不足、社会支持缺乏。结论 脑卒中康复期患者的女性照顾者的感受呈现多维度, 提示应关注女性照顾者的心理健康, 引导其寻求积极的应对方式, 进而为脑卒中患者的康复提供更好的照护。