Objective:To explore the effect of implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure.Methods:Seventy-eight patient...Objective:To explore the effect of implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure.Methods:Seventy-eight patients with severe pneumonia and respiratory failure admitted from January 2024 to February 2025 were selected and randomly divided into two groups using a computer-based random drawing method.The control group(39 patients)received routine nursing,while the observation group(39 patients)received a time-sensitive incentive model combined with specialized rehabilitation nursing.Lung function and adverse emotional states were compared between the two groups.Results:After 2 weeks of nursing,the lung function of the observation group was higher than that of the control group(P<0.05),and the adverse emotional states of the observation group were lower than those of the control group(P<0.05).Conclusion:Implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure can improve lung function and emotional state.展开更多
Blockchain offers decentralization and data security in a trustless environment.Transaction details are logged to trace a transaction trail.Blockchain has multiple components that are crucial to overall performance.On...Blockchain offers decentralization and data security in a trustless environment.Transaction details are logged to trace a transaction trail.Blockchain has multiple components that are crucial to overall performance.One such component is the consensus model.It is responsible for network scaling,and blockchain suffers from scaling problems.It is also important for the growth and existence of the network to satisfy the transaction proposers and validators.To maintain the network,incentives are given to validators in a digital asset form,commonly using cryptocurrency.A lack of appropriate incentives can lead to suboptimal network performance,preventing networks from reaching their full potential.This paper introduces a noncooperative game theory-based incentive model to improve network performance while enhancing the scaling feature of a permissioned blockchain network.The model is generic and focuses on the incentive structure of the network.The proposed model is based on five design goals.They are generability,scalability,energy awareness,fairness,and dynamism.The proposed model is not a consensus model but a complement to a suitable voting-based consensus model.An extensive simulation campaign was conducted to demonstrate the effectiveness of the proposed model.展开更多
With the deepening of electric power market reform in China,the monopoly edge of the state-owned electric power enterprises will lose.On the basis of the existing post performance salary mechanism,Chinese power enterp...With the deepening of electric power market reform in China,the monopoly edge of the state-owned electric power enterprises will lose.On the basis of the existing post performance salary mechanism,Chinese power enterprises need to optimize the incentive mechanism of R&D staff,to arouse the R&D staff's enthusiasm and creativity,to adapt to the new market competition and further improve market value.Whilst the incentive mechanism optimizing processing needs to consider not only the changing market environment but also the personal and working characteristics of R&D staff.This paper summarizes the characteristics of the current Chinese power enterprises' R&D staff:staff's theory quality is high,but insensitive to the market;they are confronted with heavy workload and diversified job choices;managers can observe their behavior choices or not;besides,the process of R&D is complex and the market reactions of R&D achievements are uncertain.Based on the premise of the above features,two incentive models are established in this paper from the point of view of enterprise managers.One is for the situation when staff's behavior choices can be observed;the other is for the situation when staff's behavior choices cannot be observed.Through solving the model,we analyze the optimization path of electric power enterprises R&D staff incentive mechanism under these conditions:(1) when staff's behavior choices can be observed,managers can pay more to the R&D staff who develop products with higher output value,in order to encourage them to work harder.(2) when staff's behavior choices cannot be observed,managers should take reasonable strategies according to the different situations:a.when R&D staff incentive totally depend on the market value of the R&D achievements,managers should allocate workload rationally according to their different technical levels;b.when the market reactions of R&D results become more precarious,managers need to reduce the incentive intensity which based on the market value and raise their fixed salary level;c.when R&D staff become more risk averse,managers should reduce the incentive intensity which based on the market value and raise their fixed salary level;on the contrary,managers should improve the incentive intensity and reduce the fixed salary level.展开更多
文摘Objective:To explore the effect of implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure.Methods:Seventy-eight patients with severe pneumonia and respiratory failure admitted from January 2024 to February 2025 were selected and randomly divided into two groups using a computer-based random drawing method.The control group(39 patients)received routine nursing,while the observation group(39 patients)received a time-sensitive incentive model combined with specialized rehabilitation nursing.Lung function and adverse emotional states were compared between the two groups.Results:After 2 weeks of nursing,the lung function of the observation group was higher than that of the control group(P<0.05),and the adverse emotional states of the observation group were lower than those of the control group(P<0.05).Conclusion:Implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure can improve lung function and emotional state.
文摘Blockchain offers decentralization and data security in a trustless environment.Transaction details are logged to trace a transaction trail.Blockchain has multiple components that are crucial to overall performance.One such component is the consensus model.It is responsible for network scaling,and blockchain suffers from scaling problems.It is also important for the growth and existence of the network to satisfy the transaction proposers and validators.To maintain the network,incentives are given to validators in a digital asset form,commonly using cryptocurrency.A lack of appropriate incentives can lead to suboptimal network performance,preventing networks from reaching their full potential.This paper introduces a noncooperative game theory-based incentive model to improve network performance while enhancing the scaling feature of a permissioned blockchain network.The model is generic and focuses on the incentive structure of the network.The proposed model is based on five design goals.They are generability,scalability,energy awareness,fairness,and dynamism.The proposed model is not a consensus model but a complement to a suitable voting-based consensus model.An extensive simulation campaign was conducted to demonstrate the effectiveness of the proposed model.
基金supported by 2016 annual North China Electric Power University undergraduate innovative training program research project(Grant No.20162183)
文摘With the deepening of electric power market reform in China,the monopoly edge of the state-owned electric power enterprises will lose.On the basis of the existing post performance salary mechanism,Chinese power enterprises need to optimize the incentive mechanism of R&D staff,to arouse the R&D staff's enthusiasm and creativity,to adapt to the new market competition and further improve market value.Whilst the incentive mechanism optimizing processing needs to consider not only the changing market environment but also the personal and working characteristics of R&D staff.This paper summarizes the characteristics of the current Chinese power enterprises' R&D staff:staff's theory quality is high,but insensitive to the market;they are confronted with heavy workload and diversified job choices;managers can observe their behavior choices or not;besides,the process of R&D is complex and the market reactions of R&D achievements are uncertain.Based on the premise of the above features,two incentive models are established in this paper from the point of view of enterprise managers.One is for the situation when staff's behavior choices can be observed;the other is for the situation when staff's behavior choices cannot be observed.Through solving the model,we analyze the optimization path of electric power enterprises R&D staff incentive mechanism under these conditions:(1) when staff's behavior choices can be observed,managers can pay more to the R&D staff who develop products with higher output value,in order to encourage them to work harder.(2) when staff's behavior choices cannot be observed,managers should take reasonable strategies according to the different situations:a.when R&D staff incentive totally depend on the market value of the R&D achievements,managers should allocate workload rationally according to their different technical levels;b.when the market reactions of R&D results become more precarious,managers need to reduce the incentive intensity which based on the market value and raise their fixed salary level;c.when R&D staff become more risk averse,managers should reduce the incentive intensity which based on the market value and raise their fixed salary level;on the contrary,managers should improve the incentive intensity and reduce the fixed salary level.
