医院安全氛围在护士感知工作环境及满意度间的中介效应分析

目的探讨护士感知工作环境、医院安全氛围和护士满意度之间的关系和影响路径。方法采用便利抽样法,于2021年9月至11月选取成都市2家三级甲等综合医院和1家三级甲等专科医院护士为研究对象,以护士感知工作环境问卷、医院安全氛围量表和工作满意度量表对护士进行调查,采用Pearson相关性分析医院安全氛围、护士感知工作环境与满意度之间相关性,根据相关性检验结果建立路径关系模型,用Bootstrap法进行中介效应检验,深入剖析医院安全氛围在护士感知工作环境和满意度之间的中介效应。结果护士工作环境感知与满意度呈正相关(r=0.428,P<0.01),医院安全氛围与护士工作环境呈正相关(r=0.693,P<0.01),医院安全氛围与护士满意度呈正相关(r=0.466,P<0.01),护士感知工作环境正向预测医院安全氛围(β=0.773,P=0.003),对满意度的正向预测作用差异无统计学意义(β=0.060,P=0.530),医院安全氛围在护士感知工作环境和满意度间的间接效应值为0.414(95%CI 0.557~1.531),占总效应的87.34%。结论医院安全氛围在护士感知工作环境和满意度间起到完全中介作用,促进护理队伍健康稳定发展。

Analysis on Content and Distribution of Residual Film in Fields of Different Crops

Before spring ploughing in 2019,the representative fields of the 8^(th) Division were selected,and residual film at different depths of soil in three areas of the 8^(th) Division was collected. Through the analysis on the weight and amount of residual film at different depths of soil,it was found that the average content of residual film in the 8^(th) Division was 104 kg/hm^2. From high to low,the content sequence of residual film in the three areas was Anjihai area,Mosuowan area and Xiayedi area. The average amount of residual film collected from the cotton field in the three areas was greater than that from the corn field. In the three areas,the content of residual film in the cotton field at the depth of 0-10 and 11-30 cm was higher than that in the corn field,while the content of residual film at the depth of 31-50 cm in the corn field was higher than that in the cotton field.

Probabilistic movement primitive based motion learning for a lower limb exoskeleton with black-box optimization

As a wearable robot,an exoskeleton provides a direct transfer of mechanical power to assist or augment the wearer’s movement with an anthropomorphic configuration.When an exoskeleton is used to facilitate the wearer’s movement,a motion generation process often plays an important role in high-level control.One of the main challenges in this area is to generate in real time a reference trajectory that is parallel with human intention and can adapt to different situations.In this paper,we first describe a novel motion modeling method based on probabilistic movement primitive(ProMP)for a lower limb exoskeleton,which is a new and powerful representative tool for generating motion trajectories.To adapt the trajectory to different situations when the exoskeleton is used by different wearers,we propose a novel motion learning scheme based on black-box optimization(BBO)PIBB combined with ProMP.The motion model is first learned by ProMP offline,which can generate reference trajectories for use by exoskeleton controllers online.PIBB is adopted to learn and update the model for online trajectory generation,which provides the capability of adaptation of the system and eliminates the effects of uncertainties.Simulations and experiments involving six subjects using the lower limb exoskeleton HEXO demonstrate the effectiveness of the proposed methods.

Integral Real-time Locomotion Mode Recognition Based on GA-CNN for Lower Limb Exoskeleton

The wearable lower limb exoskeleton is a typical human-in-loop human–robot coupled system,which conducts natural and close cooperation with the human by recognizing human locomotion timely.Requiring subject-specific training is the main challenge of the existing approaches,and most methods have the problem of insufficient recognition.This paper proposes an integral subject-adaptive real-time Locomotion Mode Recognition(LMR)method based on GA-CNN for a lower limb exoskeleton system.The LMR method is a combination of Convolutional Neural Networks(CNN)and Genetic Algorithm(GA)-based multi-sensor information selection.To improve network performance,the hyper-parameters are optimized by Bayesian optimization.An exoskeleton prototype system with multi-type sensors and novel sensing-shoes is used to verify the proposed method.Twelve locomotion modes,which composed an integral locomotion system for the daily application of the exoskeleton,can be recognized by the proposed method.According to a series of experiments,the recognizer shows strong comprehensive abilities including high accuracy,low delay,and sufficient adaption to different subjects.

Pyroelectric property of SrTiO_(3)/Si ferroelectric-semiconductor heterojunctions near room temperature

A nonlinear thermodynamic formalism is developed to calculate the pyroeletric property of epitaxial single domain SrTiO_(3)/Si heterojunctions by taking into account the thermal expansion misfit strain at diferent temperatures.It has been demonstrated that the crucial role was played by the contribution associated with the structure order parameter arising from the rotations of oxygen octahedral on pyroelectricity.A dramatic decrease in the pyroelectric cofficient due to the strong coupling between the polarization and the structure order parameter is found at ferroelectric T_(p1)-T_(p2) phase transition.At the same time,the thermal expansion mismatch between film and substrate is also found to provide an additional weak decrease of pyroelectricity.The analytic relationship of the out-of-plane pyroeletric coefficient and dielectric constant of ferroeletric phases by considering the thermal expansion of thin films and substrates has been determined for the first time.Our research provides another avenue for the investigation of the pyroelectric effects of ferroic thin films,especially,such as antiferroelectric and muliferroic materials having two or more order parameters.