Objective To explore critical care clinicians’knowledge,attitudes and perceptions toward early mobilization of critically ill patients in ICUs.Design A cross-sectional national survey was conducted.From January to Au...Objective To explore critical care clinicians’knowledge,attitudes and perceptions toward early mobilization of critically ill patients in ICUs.Design A cross-sectional national survey was conducted.From January to August 2020,ICU nurses in 11 hospitals were surveyed by using a questionnaire on the knowledge,attitudes and perceptions of ICU early mobilization.Results Totally 512 nurses completed the questionnaire.The respondents’mean score for knowledge of early mobilization was 6.89±2.91.The level of knowledge was good in 2.5%(13/512),fair in 52.3%(268/512).The attitudes toward early mobilization were positive in 31.4%(161/512).In terms of perceived implementation of ICU early mobilization,42.9%(220/512)of nurses did not believe that this should be a top priority in intensive care.The attitudes of nurses from different ICUs were significantly different(F=3.58,P<0.05).The knowledge(7.34±2.78 vs.6.49±2.97,t=3.37,P<0.001)and attitudes(3.82±0.58 vs.3.52±0.56,t=5.63,P<0.001)of nurses who had early mobilization related training were higher than those of nurses who had no training.Conclusions The importance of early ICU early mobilization is increasingly recognized by critical care providers.However,there is still a gap in the knowledge,attitudes and perceptions of ICU early mobilization among nurses.In future studies,it is necessary to further systematically identify the reasons leading to the gaps in these aspects and implement targeted interventions around these gaps.Meanwhile,more nurses should be encouraged to participate in decision-making to ensure the efficient and quality implementation of ICU early mobilization practices.展开更多
The aim of human-object interaction(HOI)detection is to identify the triplets consisting of a human,a verb,and an object.Although existing methods leverage vision-language models(e.g.,CLIP)to transfer textual informat...The aim of human-object interaction(HOI)detection is to identify the triplets consisting of a human,a verb,and an object.Although existing methods leverage vision-language models(e.g.,CLIP)to transfer textual information for unseen compositions,they often fail to capture the fine-grained visual cues that are essential for complex interactions,such as spatial configurations and object affordances.In this paper,we introduce visual guidance as an alternative approach to achieving the desired outcome.We define a new visual-guided HOI detection task for the first time,aiming at detecting unseen HOI categories using a small number of guidance examples.To support this new task,we have constructed a new benchmark dataset,which contains one base set and four novel sets,taking into account the peculiarities of HOI.Then,we propose a VG-HOI model with progressive guidance,query reconstruction,and a conditional uncoupling decoder to supplement common HOI knowledge and task-specific cues to improve the generalization capability of our model.Besides,we explore a new guidance sampling strategy—disentangled guidance—for real-world scenarios.Our in-depth analysis of the experimental results shows that the proposed model can improve the ability to generalize when detecting visual-guided HOI.展开更多
基金This project is supported by the Fundamental Research Funds for the Central Universities(Project number:3332019171).
文摘Objective To explore critical care clinicians’knowledge,attitudes and perceptions toward early mobilization of critically ill patients in ICUs.Design A cross-sectional national survey was conducted.From January to August 2020,ICU nurses in 11 hospitals were surveyed by using a questionnaire on the knowledge,attitudes and perceptions of ICU early mobilization.Results Totally 512 nurses completed the questionnaire.The respondents’mean score for knowledge of early mobilization was 6.89±2.91.The level of knowledge was good in 2.5%(13/512),fair in 52.3%(268/512).The attitudes toward early mobilization were positive in 31.4%(161/512).In terms of perceived implementation of ICU early mobilization,42.9%(220/512)of nurses did not believe that this should be a top priority in intensive care.The attitudes of nurses from different ICUs were significantly different(F=3.58,P<0.05).The knowledge(7.34±2.78 vs.6.49±2.97,t=3.37,P<0.001)and attitudes(3.82±0.58 vs.3.52±0.56,t=5.63,P<0.001)of nurses who had early mobilization related training were higher than those of nurses who had no training.Conclusions The importance of early ICU early mobilization is increasingly recognized by critical care providers.However,there is still a gap in the knowledge,attitudes and perceptions of ICU early mobilization among nurses.In future studies,it is necessary to further systematically identify the reasons leading to the gaps in these aspects and implement targeted interventions around these gaps.Meanwhile,more nurses should be encouraged to participate in decision-making to ensure the efficient and quality implementation of ICU early mobilization practices.
基金supported by the National Natural Science Foundation of China(No.62401447)the Key Research and Development Program of Shaanxi(Nos.2024GX-YBXM-051 and 2024CY2-GJHX08).
文摘The aim of human-object interaction(HOI)detection is to identify the triplets consisting of a human,a verb,and an object.Although existing methods leverage vision-language models(e.g.,CLIP)to transfer textual information for unseen compositions,they often fail to capture the fine-grained visual cues that are essential for complex interactions,such as spatial configurations and object affordances.In this paper,we introduce visual guidance as an alternative approach to achieving the desired outcome.We define a new visual-guided HOI detection task for the first time,aiming at detecting unseen HOI categories using a small number of guidance examples.To support this new task,we have constructed a new benchmark dataset,which contains one base set and four novel sets,taking into account the peculiarities of HOI.Then,we propose a VG-HOI model with progressive guidance,query reconstruction,and a conditional uncoupling decoder to supplement common HOI knowledge and task-specific cues to improve the generalization capability of our model.Besides,we explore a new guidance sampling strategy—disentangled guidance—for real-world scenarios.Our in-depth analysis of the experimental results shows that the proposed model can improve the ability to generalize when detecting visual-guided HOI.
