FePt granular films were prepared by direct current facing-target magnetron sputtering system onto glass substrates and subsequently in-situ annealed in vacuum. Vibrating sample magnetometer, X-ray diffraction and sca...FePt granular films were prepared by direct current facing-target magnetron sputtering system onto glass substrates and subsequently in-situ annealed in vacuum. Vibrating sample magnetometer, X-ray diffraction and scanning probe microscope were applied to study the magnetic properties, microstructures, morphologies and domain structures of the samples. （FePt）27Ti73 bilayer films were fabricated at various conditions to investigate the effect of Ti on FePt grains. The results show that without Ti matrix layer, FePt films deposited onto the glass substrates are fcc disordered; with addition of Ti matrix layer, FePt/Ti films form a ternary （FePt）27Ti73 alloy possessing fcc and L10 （111） mixed texture. FePt/（FePt）27Ti73 films with perfectly ordered L10（111） structure and unique magnetic properties can be obtained at Ti thickness of 35nm and substrate temperature of 250℃. The maximum coercivity is more than 240kA/m and the squareness ratio is more than 0.9. The obtained results suggest that the granular FePt/（FePt）27Ti73 films can be applicable to ultrahigh-density magnetic recording media.展开更多
TiCoTi granular films were prepared by DC facing-target magnetron sputtering system onto glass substrates and subsequently in situ annealing in vacuum. Structural of Ti (t nm)/Co (40 nm)/Ti (t nm) films were investiga...TiCoTi granular films were prepared by DC facing-target magnetron sputtering system onto glass substrates and subsequently in situ annealing in vacuum. Structural of Ti (t nm)/Co (40 nm)/Ti (t nm) films were investigated in detail, which shows that the majority Co nanograins are formed as the hexagonal-close-packed (HCP) structure. Vibrating sample magnetometer (VSM) and scanning probe microscope (SPM) were applied to study the magnetic properties, morphologies and domain structures of these samples. It has been found that the structure and magnetic properties of the Ti/Co/Ti films depend strongly on the Ti layer thickness. The out-of-plane coercivities (Hc) of the film is maximum about 78.8 kA·m-1 when t=5 nm with annealing at 300 ℃; the distributing of grains of the sample is uniformity; and the average size of particles is about 13 nm. The obtained results suggest that this system is perpendicular anisotropy and might be applicable to perpendicular magnetic recording media.展开更多
目的:为解决传统临床病种库系统存在的依赖大量人工判断、缺乏辅助标注、电子病历数据可用性差等问题,设计一种基于后结构化技术的临床病种库系统。方法:先通过I2B2标准以及双向长短期记忆网络(bi-directional long short-term memory,B...目的:为解决传统临床病种库系统存在的依赖大量人工判断、缺乏辅助标注、电子病历数据可用性差等问题,设计一种基于后结构化技术的临床病种库系统。方法:先通过I2B2标准以及双向长短期记忆网络(bi-directional long short-term memory,BiLSTM)模型构建实体识别模型,形成病历模板库,然后组合病历模板库形成关系模板,抽取复杂的医学实体,实现电子病历的后结构化。之后,基于电子病历后结构化技术构建包括病历结构化、结构化评估、数据标注、常规功能和系统管理5个模块的临床病种库系统。结果:该系统可以将电子病历文本转化为结构化语言,提供更精细化的数据要素提取、更智能的结构化服务,提高了临床和科研工作的效率。结论:该系统提高了临床病种的数据可用性,减轻了用户数据加工的工作强度,保证了数据应用的高质量,为医学研究、临床辅助决策打下了坚实的基础。展开更多
Fe100-xPtx(x=30at.%-60at.%) nanocomposite films were deposited on natural-oxidized Si(100) substrates by magnetron sputtering. The as-deposited films were annealed between 373 and 1073 K. In situ X-ray diffraction sho...Fe100-xPtx(x=30at.%-60at.%) nanocomposite films were deposited on natural-oxidized Si(100) substrates by magnetron sputtering. The as-deposited films were annealed between 373 and 1073 K. In situ X-ray diffraction shows that the FePt nanocomposite films undergo a phase transformation from a disordered FCC phase to an ordered L10 phase between 673 and 773 K. The coercivity is 306 kA·m-1 whiles the average grain sizes is about 10 nm in the optimized FePt alloy film sample annealed at 673 K. The adjustable coercivity and fine grain size suggest that this FePt nanocomposites system is suitable as recording media at extremely high areal density.展开更多
Sodium homeostasis disorder is one of the most common abnormal symptoms of elderly patients in intensive care unit(ICU),which may lead to physiological disorders of many organs.The current prediction of serum sodium i...Sodium homeostasis disorder is one of the most common abnormal symptoms of elderly patients in intensive care unit(ICU),which may lead to physiological disorders of many organs.The current prediction of serum sodium in ICU is mainly based on the subjective judgment of doctors’experience.This study aims at this problem by studying the clinical retrospective electronic medical record data of ICU to establish a machine learning model to predict the short-term serum sodium value of ICU patients.The data set used in this study is the open-source intensive care medical information set Medical Information Mart for Intensive Care(MIMIC)-IV.The time point of serum sodium detection was selected from the ICU clinical records,and the ICU records of 25risk factors related to serum sodium were extracted from the patients within the first 12 h for statistical analysis.A prediction model of serum sodium value within 48 h was established using a feedforward neural network,and compared with previous methods.Our research results show that the neural network learning model can predict the development of serum sodium in patients using physiological indicators recorded in clinical electronic medical records within 12 h,and has better prediction effect than the serum sodium formula and other machine learning models.展开更多
基金Project(10274018) supported by the National Natural Science Foundation of China project(Z200102) supported the KeyFoundation of Hebei Normal University project(2002116) supported the Foundation Education Department of of Hebei Provin
文摘FePt granular films were prepared by direct current facing-target magnetron sputtering system onto glass substrates and subsequently in-situ annealed in vacuum. Vibrating sample magnetometer, X-ray diffraction and scanning probe microscope were applied to study the magnetic properties, microstructures, morphologies and domain structures of the samples. （FePt）27Ti73 bilayer films were fabricated at various conditions to investigate the effect of Ti on FePt grains. The results show that without Ti matrix layer, FePt films deposited onto the glass substrates are fcc disordered; with addition of Ti matrix layer, FePt/Ti films form a ternary （FePt）27Ti73 alloy possessing fcc and L10 （111） mixed texture. FePt/（FePt）27Ti73 films with perfectly ordered L10（111） structure and unique magnetic properties can be obtained at Ti thickness of 35nm and substrate temperature of 250℃. The maximum coercivity is more than 240kA/m and the squareness ratio is more than 0.9. The obtained results suggest that the granular FePt/（FePt）27Ti73 films can be applicable to ultrahigh-density magnetic recording media.
基金This work was financially supported by the National Natural Science Foundation of China (No.10274018) and the Foundation of Hebei Provincial Education Department (No.2002116).
文摘TiCoTi granular films were prepared by DC facing-target magnetron sputtering system onto glass substrates and subsequently in situ annealing in vacuum. Structural of Ti (t nm)/Co (40 nm)/Ti (t nm) films were investigated in detail, which shows that the majority Co nanograins are formed as the hexagonal-close-packed (HCP) structure. Vibrating sample magnetometer (VSM) and scanning probe microscope (SPM) were applied to study the magnetic properties, morphologies and domain structures of these samples. It has been found that the structure and magnetic properties of the Ti/Co/Ti films depend strongly on the Ti layer thickness. The out-of-plane coercivities (Hc) of the film is maximum about 78.8 kA·m-1 when t=5 nm with annealing at 300 ℃; the distributing of grains of the sample is uniformity; and the average size of particles is about 13 nm. The obtained results suggest that this system is perpendicular anisotropy and might be applicable to perpendicular magnetic recording media.
文摘目的:为解决传统临床病种库系统存在的依赖大量人工判断、缺乏辅助标注、电子病历数据可用性差等问题,设计一种基于后结构化技术的临床病种库系统。方法:先通过I2B2标准以及双向长短期记忆网络(bi-directional long short-term memory,BiLSTM)模型构建实体识别模型,形成病历模板库,然后组合病历模板库形成关系模板,抽取复杂的医学实体,实现电子病历的后结构化。之后,基于电子病历后结构化技术构建包括病历结构化、结构化评估、数据标注、常规功能和系统管理5个模块的临床病种库系统。结果:该系统可以将电子病历文本转化为结构化语言,提供更精细化的数据要素提取、更智能的结构化服务,提高了临床和科研工作的效率。结论:该系统提高了临床病种的数据可用性,减轻了用户数据加工的工作强度,保证了数据应用的高质量,为医学研究、临床辅助决策打下了坚实的基础。
基金This work was financially supported by the National Science Fund for Distinguished Young Scholars and the National Natural Science Foundation of China (No. 50325209, 50232030).
文摘Fe100-xPtx(x=30at.%-60at.%) nanocomposite films were deposited on natural-oxidized Si(100) substrates by magnetron sputtering. The as-deposited films were annealed between 373 and 1073 K. In situ X-ray diffraction shows that the FePt nanocomposite films undergo a phase transformation from a disordered FCC phase to an ordered L10 phase between 673 and 773 K. The coercivity is 306 kA·m-1 whiles the average grain sizes is about 10 nm in the optimized FePt alloy film sample annealed at 673 K. The adjustable coercivity and fine grain size suggest that this FePt nanocomposites system is suitable as recording media at extremely high areal density.
基金supported by the National Natural Science Foundation of China(No.12345678)。
文摘Sodium homeostasis disorder is one of the most common abnormal symptoms of elderly patients in intensive care unit(ICU),which may lead to physiological disorders of many organs.The current prediction of serum sodium in ICU is mainly based on the subjective judgment of doctors’experience.This study aims at this problem by studying the clinical retrospective electronic medical record data of ICU to establish a machine learning model to predict the short-term serum sodium value of ICU patients.The data set used in this study is the open-source intensive care medical information set Medical Information Mart for Intensive Care(MIMIC)-IV.The time point of serum sodium detection was selected from the ICU clinical records,and the ICU records of 25risk factors related to serum sodium were extracted from the patients within the first 12 h for statistical analysis.A prediction model of serum sodium value within 48 h was established using a feedforward neural network,and compared with previous methods.Our research results show that the neural network learning model can predict the development of serum sodium in patients using physiological indicators recorded in clinical electronic medical records within 12 h,and has better prediction effect than the serum sodium formula and other machine learning models.
