On the Special Application of the Principle of Proportionality under Emergency State

As the two fundamental aspects of modern society,the emergency state and the routine state are not exceptions to the rule of law.They just abide by special legal rules and must adhere to the spirit of the rule of law,such as human rights protection and power restrictions and apply the principle of proportionality.In a state of emergency,public interests are faced with major and urgent threats.In this state,the positioning of the purpose,the examination of the consequences,or the measurement of the legal benefits of the purpose and the consequences all have a certain degree of particularity and complexity.In order to increase the rationality of the principle of proportionality in the state of emergency,and to perform its value function scientifically and effectively,it is necessary to adopt loose application standards based on the characteristics of the state of emergency,grasp the key application links,and limit the scope of application to the review of the rationality of the exercise of emergency powers.Judgment of the legitimacy of the purpose of the exercise of emergency powers and the derogation of civil rights such as human dignity are not within the scope of the principle of proportionality.

Load Shedding Control Strategy in Power Grid Emergency State Based on Deep Reinforcement Learning

In viewing the power grid for large-scale new energy integration and power electrification of power grid equipment,the impact of power system faults is increased,and the ability of anti-disturbance is decreased,which makes the power system fault clearance more dificult.In this paper,a load shedding control strategy based on artificial intelligence is proposed,this action strategy of load shedding,which is selected by deep reinforcement learning,can support autonomous voltage control.First,the power system operation data is used as the basic data to construct the network training dataset,and then a novel reward function for voltage is established.This value function,which conforms to the power grid operation characteristics,will act as the reward value for deep reinforcement learning,and the Deep Deterministic Policy Gradient algorithm(DDPG)algorithm,with the continuous action strategy,will be adopted.Finally,the deep reinforcement learning network is continuously trained,and the load shedding strategy concerning the grid voltage control problem will be obtained in the power system emergency control situation,and this strategy action is input into the Pypower module for simulation verification,thereby realizing the joint drive of data and model.According to the numerical simulation analysis,it shows that this method can effectively determine the accurate action selection of load shedding,and improve the stable operational ability of the power system.

新型冠状病毒肺炎疫情下的紧急政府采购:以上海市疾病预防控制中心为例

以上海市疾病预防控制中心在新型冠状病毒肺炎疫情防控期间开展的紧急政府采购为例,分析紧急政府采购在突发公共卫生事件处置中发挥的重要保障作用,并探讨应急采购执行及监督管理的方式。

Evaluation of the effect of the state of emergency for the first wave of COVID-19 in Japan

In this paper,we evaluate the effect of the state of emergency for the first wave of COVID-19 in Japan,2020 from the viewpoint of mathematical modelling.In Japan,it was announced during the period of the state of emergency from April 7 to May 25,2020 that the 80%reduction of the contact rate is needed to control the outbreak.By numerical simulation,we show that the reduction rate seems to have reached up to 86%.Moreover,we estimate the control reproduction number R c during the period of the state of emergency as R c?0:36(95%CI,0.34e0.39),and show that the effective reproduction number R e after the lifting of the state of emergency could be greater than 1.This result suggests us that the second wave of COVID-19 in Japan could possibly occur if any effective intervention will not be taken again.

Clinical application of Chinese Nanjing persistent vegetative state scale

Background:It is a challenge to characterize the consciousness level of patients with severe disturbance of consciousness and predict their prognosis effectively for Chinese doctors.We aimed to investigate the psychometric property and the diagnostic practicality of severe disturbance of consciousness by Chinese Nanjing persistent vegetative state scale(CNPVSS)which was first set up in 1996 and modified in 2001 and 2011.Methods:The concurrent validity,inter-rater consistency and diagnostic accuracy of CNPVSS and Chinese version of coma recovery scale-revised(CRS-R)were investigated by assessment of 380 patients with severe disorders of consciousness.Results:Total scores of the CNPVSS were correlated significantly with that of the CRS-R,indicating acceptable concurrent validity.Sub-scale analysis showed moderate to high inter-rater reliability and test-retest reliability.CNPVSS was superior to CRS-R on the diagnosis sensitivity.The CNPVSS was able to distinguish 65 patients in emergence from minimal consciousness state who were misclassified as in minimal consciousness state(MCS)by the CRS-R,and it could also distinguish two patients in MCS who were misclassified as in vegetative state by the CRS-R.Conclusion:The CNPVSS is an appropriate measurement and is sensitive to distinguish the MCS patients from the VS patients.