Research on Public Engineering Emergency Decision-Making Based on Multi-Granularity Language Information

To effectively deal with fuzzy and uncertain information in public engineering emergencies,an emergency decision-making method based on multi-granularity language information is proposed.Firstly,decision makers select the appropriate language phrase set according to their own situation,give the preference information of the weight of each key indicator,and then transform the multi-granularity language information through consistency.On this basis,the sequential optimization technology of the approximately ideal scheme is introduced to obtain the weight coefficient of each key indicator.Subsequently,the weighted average operator is used to aggregate the preference information of each alternative scheme with the relative importance of decision-makers and the weight of key indicators in sequence,and the comprehensive evaluation value of each scheme is obtained to determine the optimal scheme.Lastly,the effectiveness and practicability of the method are verified by taking the earthwork collapse accident in the construction of a reservoir as an example.

Information Aggregation of Group Decision-Making in Emergency Events

Information is a key factor in emergency management, which helps decision makers to make effective decisions. In this paper, aiming at clarifying the information aggregation laws, and according to the characteristic of emergency information, information relative entropy is applied in the information aggregation to establish the information aggregation model of emergency group decision-making. The analysis shows that support and credibility of decision rule are the two factors in information aggregation. The results of four emergency decision-making groups in case study support the analysis in the paper.

Characteristics of Decision-Making by Family Members When Older Adults Are Hospitalized in Emergency Cases with Life-Threatening Conditions

Aim: This study aims to elucidate decision-making characteristics based on interviews with family members with experience in having to select treatments for older adult patients who have been hospitalized following emergency transport to the hospital. Design: Semi-structured interviews were conducted with 10 individuals with experience in surrogate decision-making for an older adult family member. Methods: The recorded interview data were transcribed verbatim, divided into minimum semantic units, and coded. Next, categories and subcategories were abstracted. A comparison was made with the conceptual constructs of a previous study that examined decision-making by families in a life-threatening crisis. Results: Four categories were extracted from 489 antecedents, 370 attributes, and 388 consequences. One new category was abstracted for each of: 1) antecedents: observing abnormalities and responding, while being worried about death;2) attributes: deliberating on the patient prognosis, the relationship with the patient, and what they believe the patient would want;and 3) consequences: continuing support during convalescence. It is desirable to provide support based on the characteristics of families of older adults, including considering the psychological burden on the families who make surrogate decisions, and also the burden of subsequent caregiving because it is not and in the present environment has not been common for patients to express their wishes beforehand.

Construction of an Index System for Earthquake Emergency Loss Assessment and Decision-making

Loss assessment and decision-making are essential for earthquake emergency rescues,and for scientific prediction of seismic damage and determination of rescue objectives.In practice,however,there exist some problems,such as basic data not being precise and rich enough and decision making not having systematic and complete criteria.This paper tries to solve these problems using the method of data indexation by constructing an index system for earthquake emergency loss assessment and decision-making.

Spillovers of US unconventional monetary policy:quantitative easing,spreads,and international financial markets

This study investigates the international spillover effects of US unconventional monetary policy(UMP)-frequently called large-scale asset purchases or quantitative easing(QE)—on advanced and emerging market economies,using structural vector autoregressive models with high-frequency daily data.Blinder(Federal Reserve Bank of St.Louis Rev 92(6):465–479,2010)argued that the QE measures primarily aim to reduce US interest rate spreads,such as term and risk premiums.Considering this argument and recent empirical evidence,we use two spreads as indicators of US UMP:the mortgage and term spreads.Based on data from 20 emerging and 20 advanced countries,our empirical findings reveal that US unconventional monetary policies significantly affect financial conditions in emerging and advanced countries by altering the risktaking behavior of investors.This result suggests that the risk-taking channel plays an important role in transmitting the effects of these policies to the rest of the world.The extent of these effects depends on the type of QE measures.QE measures such as purchases of private sector securities that lower the US mortgage spread exert stronger and more significant spillover effects on international financial markets than those that reduce the US term spread.Furthermore,the estimated financial spillovers vary substantially across countries and between and within the emerging and advanced countries that we examine in this study.

Don’t forget emergency surgery! Lessons to learn from elective indocyanine green-guided gastrointestinal interventions

Fluorescence-based imaging has found application in several fields of elective surgery,but there is still a lack of evidence in the literature about its use in the emergency setting.Clinical trials have consistently shown that indocyanine green(ICG)-guided surgery can dramatically reduce the risk of postoperative complic-ations,length of in-hospital stay and total healthcare costs in the elective setting.It is well-known that emergency surgery has a higher complication rate than its elective counterpart,therefore an impelling need for research studies to explore,validate and develop this issue has been highlighted.The present editorial aims to provide a critical overview of currently available applications and pitfalls of ICG fluorescence in abdominal emergencies.Furthermore,we evidenced how the experience of ICG-fluorescence in elective surgery might be of great help in implementing its use in acute situations.In the first paragraph we analyzed the tips and tricks of ICG-guided cancer surgery that might be exploited in acute cases.We then deepened the two most described topics in ICG-guided emergency surgery:Acute cholecystitis and intestinal ischemia,focusing on both the advantages and limitations of green-fluorescence application in these two fields.In emergency situations,ICG fluorescence demonstrates a promising role in preventing undue intestinal resections or their entity,facilitating the detection of intestinal ischemic zones,identifying biliary tree anatomy,reducing post-operative complications,and mitigating high mortality rates.The need to improve its application still exists,therefore we strongly believe that the elective and routinary use of the dye is the best way to acquire the necessary skills for emer-gency procedures.

Intelligent decision-making method for vehicles in emergency conditions based on artificial potential fields and finite state machines

This study aims to propose a decision-making method based on artificial potential fields(APFs)and finite state machines(FSMs)in emergency conditions.This study presents a decision-making method based on APFs and FSMs for emergency conditions.By modeling the longitudinal and lateral potential energy fields of the vehicle,the driving state is identified,and the trigger conditions are provided for path planning during lane changing.In addition,this study also designed the state transition rules based on the longitudinal and lateral virtual forces.It established the vehicle decision-making model based on the finite state machine to ensure driving safety in emergency situations.To illustrate the performance of the decision-making model by considering APFs and finite state machines.The version of the model in the co-simulation platform of MATLAB and CarSim shows that the developed decision model in this study accurately generates driving behaviors of the vehicle at different time intervals.The contributions of this study are two-fold.A hierarchical vehicle state machine decision model is proposed to enhance driving safety in emergency scenarios.Mathematical models for determining the transition thresholds of lateral and longitudinal vehicle states are established based on the vehicle potential field model,leading to the formulation of transition rules between different states of autonomous vehicles(AVs).

A comparison of perspectives on costs in emergency care among emergency department patients and residents

BACKGROUND: Costs of care are increasingly important in healthcare policy and, more recently, in clinical care in the emergency department(ED). We compare ED resident and patient perspectives surrounding costs in emergency care.METHODS: We conducted a mixed methods study using surveys and qualitative interviews at a single, academic ED in the United States. The two study populations were a convenience sample of adult ED patients(>17 years of age) and ED residents training at the same institution. Participants answered open- and closed-ended questions on costs, medical decision making, cost-related compliance, and communication about costs. Closed-ended data were tabulated and described using standard statistics while open-ended responses were analyzed using grounded theory.RESULTS: Thirty ED patients and 24 ED residents participated in the study. Both patients and residents generally did not have knowledge of medical costs. Patients were comfortable discussing costs while residents were less comfortable. Residents agreed that doctors should consider costs when making medical decisions whereas patients somewhat disagreed. Additionally, residents generally took costs into consideration during clinical decision-making, yet nearly all residents agreed that they had too little education on costs.CONCLUSION: There were several notable differences in ED patient and resident perspectives on costs in this U.S. sample. While patients somewhat disagree that cost should factor into decision making, generally they are comfortable discussing costs yet report having insuf? cient knowledge of what care costs. Conversely, ED residents view costs as important and agree that cost should factor into decision making but lack education on what emergency care costs.

Key elements and checklist of shared decisionmaking conversation on life-sustaining treatment in emergency:a multispecialty study from China

BACKGROUND:Shared decision-making(SDM)has broad application in emergencies.Most published studies have focused on SDM for a certain disease or expert opinions on future research gaps without revealing the full picture or detailed guidance for clinical practice.This study is to investigate the optimal application of SDM to guide life-sustaining treatment(LST)in emergencies.METHODS:This study was a prospective two-round Delphi consensus-seeking survey among multiple stakeholders at the China Consortium of Elite Teaching Hospitals for Residency Education.Participants were identified based on their expertise in medicine,law,administration,medical education,or patient advocacy.All individual items and questions in the questionnaire were scored using a 5-point Likert scale,with responses ranging from"very unimportant"(a score of 1)to"extremely important"(a score of 5).The percentages of the responses that had scores of 4-5on the 5-point Likert scale were calculated.A Kendall’s W coefficient was calculated to evaluate the consensus of experts.RESULTS:A two-level framework consisting of 4 domains and 22 items as well as a ready-touse checklist for the informed consent process for LST was established.An acceptable Kendall’s W coefficient was achieved.CONCLUSION:A consensus-based framework supporting SDM during LST in an emergency department can inform the implementation of guidelines for clinical interventions,research studies,medical education,and policy initiatives.

灌溉水盐度对玉米出苗、产量、品质及土壤盐分动态的影响

为探究适宜于我国北方干旱半干旱农业区玉米正常出苗、籽粒高产优质、土壤积盐有限的灌溉水盐分浓度,在内蒙古河套灌区开展了为期2年的膜下滴灌玉米大田试验。设置5个灌溉水盐度水平(1、2、3、4、5 g/L),在土壤基质势下限-20 kPa和灌水定额22.5 mm/次条件下,玉米耗水量、植株干物质量和籽粒产量均与灌溉水盐度呈显著二次函数关系(R^(2)>0.84),当灌溉水盐度为2 g/L时植株干物质量和籽粒产量达到极大值,当灌溉水盐度超过3 g/L时,含盐水灌溉对玉米出苗、植株干物质积累和籽粒产量均产生不利影响。灌溉水盐度在1~5 g/L范围内每增加1 g/L,膜下滴灌玉米对应水分利用效率下降0.29 kg/m~3;籽粒蛋白质含量随灌溉水盐度增加而增加,籽粒淀粉含量随灌溉水盐度增加而降低。此外,当灌溉水盐度高于3 g/L时,膜下滴灌对应土壤盐分等值线垂直半径和水平半径均随灌溉水盐度的增加而减小。基于玉米生育期内籽粒高产优质、减少土壤积盐的目标,在试验设计条件下,推荐河套灌区膜下滴灌玉米的灌溉水盐度上限为3 g/L。

基于随机森林的非常规突发事件结构化情景体系模型

为降低非常规突发事件发生所造成的各类损失,构建基于随机森林的非常规突发事件结构化情景体系模型。根据随机森林相关理论知识,使用python进行了试验仿真,并将交通隧道工程的坍塌事故视为非常规突发事件进行处理。首先,针对传统的非常规突发事件结构化情景模型存在的问题,构建非常规突发事件结构化描述空间,利用随机森林模型对非常规突发事件进行了分级,按照分级的结果,进行非常规突发事件的结构化描述。其次,基于朴素贝叶斯模型与支持向量机模型进行了对比试验,在相同的试验环境下,使用不同的数据集通过多次试验分析比较。最后,基于随机森林的回归模型预测事故类型,使用决策树模型对数据进行了可视化分析,并计算使用重要特征预测事故类型的时间效率与准确率。利用实际发生的交通隧道工程坍塌事故验证了随机森林回归模型的实用性。结果表明:随机森林模型的平均准确率比其他两种模型提高了至少8.77%;仿真结果与真实值几乎相近,仿真准确率值为1。研究结果为国家应急管理部门提供了应急决策依据,帮助决策者在最短的时间内提出合理的应急响应和应急预警方案,可以有效减少非常规突发事件发生所造成的经济损失,因此随机森林模型有较高的使用价值。

Clinical decision-making by the emergency department resident physicians for critically ill patients

The application of main methodologies for clinical decision-making by residents in emergency medical practice was assessed,and issues in this area were investigated.The treatments provided to 2611 critical patients by the Emergency Department of Peking Union Medical College Hospital were analyzed by independent investigators who evaluated the main clinical decision-making processes applied by the hospital residents.The application of decision-making strategies by PG1 and PG3 groups,which means the residents in first year and the third year,were compared.The patients were treated according to pattern recognition(43.0%),hypotheticodeductive reasoning(23.4%),event-driven models(19.3%),and rule-using algorithms(5.9%).A significant difference was found between PG1 and PG3 groups(χ^(2)=498.01,P<0.001).Pattern recognition and hypotheticdeductive methods were the most common techniques applied by emergency physicians in evaluating critically ill patients.The decision-making processes applied by junior and senior residents were significantly different,although neither group adequately applied rule-using algorithms.Inclusion of clinical decision-making in medical curricula is needed to improve decision-making in critical care.

A method for emergency response alternative decision-making under uncertainty

In this paper,an emergency decision-making method,based on case-based reasoning and cloud model,is proposed to solve the risk decision-making problem in emergency response.Casebased reasoning,by allowing the decision-maker to referring to past decisions,introduces a short-cut to formulate feasible emergency alternatives.Cloud model is used to evaluate and optimise the emergency response alternatives.To evaluate emergency response alternatives,the decision criterion must be determined according to the aim and characteristics of emergency rescue in disasters or accidents.Then,the weight cloud and evaluation cloud of the decision criterion are determined by the Delphi method combined with backward cloud generator,and the synthesised cloud of each alternative is calculated through arithmetic rules of cloud.Finally,a ranking of all response alternatives can be determined,and the best alternative is selected.Case study shows that the method makes the conversion between qualitative description and quantitative indication more effective.

基于系统动力学的突发事件演化模型

针对非常规突发事件骤发性,演变不确定性以及应对复杂性等特征,基于突发事件的结构化描述框架界定事件的发展演化方式;根据自行构建的地震案例库绘出了非常规突发地震的发展演化图.在此基础上,选取地震衍生的堰塞湖事件直链式发展演化过程为例,以汶川地震衍生的唐家山堰塞湖相关数据进行了系统动力学仿真,验证了模型的可行性和有效性.最后给出地震衍生堰塞湖应对的决策建议,为应对其它类型突发事件提供决策支持.

非常规突发事件应急决策方法研究

为深入研究非常规突发事件应急决策方法,提高对非常规突发事件的应对能力,调查研究基于应急预案、范例推理和智能规划等3种非常规突发事件的应急决策方法,对比分析这3种方法的特点。研究发现:这3种方法都可以在一定程度上为非常规突发事件提供辅助决策,但是基于智能规划的应急决策方法更适于非常规突发事件复杂的决策环境,有较大发展潜力。然后针对该方法,提出一些需要深入研究的开放性课题。

非常规突发事件应急决策系统动态作用机理

根据系统科学理论,分析非常规突发事件应急决策系统内部结构;构建SD因果关系模型,研究非常规突发事件应急决策系统各子系统间反馈机制和相互耦合机制以及应急决策动态调整机理;提出非常规突发事件应急决策系统优化建议。

面向非常规突发事件的应急资源合作博弈调度

当非常规突发事件发生后,根据灾区灾情的严重情况,往往需要同时联合使用多种运输方式将应急资源快速高效地调度到灾区,由此设计了应急资源调度的多模式分层网络。在此基础上,以博弈论为分析工具,提出了基于合作博弈的应急资源调度模型与求解算法。在该调度模型中,把不同的运输方式映射为博弈模型的局中人,可能的资源调度方式组合方案映射为策略集,不同的运输方式调度应急资源所造成的损失映射为效用函数,将应急资源的合理调度问题转化为对合作博弈调度模型的核心求解问题。接着介绍了一种求解核心的Shapley值法。通过应急资源调度的算例对比分析,验证了所建模型的可行性和求解结果作为调度策略的优越性。

非常规突发事件情景演化机理及集群决策模式研究

分析了非常规突发事件的事态情景演化机理,响应情景演化机理以及事态-响应耦合机理;构建了非常规突发事件的事态-响应的集群决策模式,并对预警、监视和响应三个子系统的协同运行进行了探讨。

面向突发事件应急决策的情景建模方法

情景是非常规突发事件应急决策的基础和依据.针对情景建模中跨学科、跨领域的知识支撑和对事件经验知识依赖的不足,本文从事件本身、事件属性以及属性间关系三个角度对非常规突发事件的情景进行刻画,提出了一种基于知识元的情景表示模型;在此基础上,针对非常规突发事件的不确定性特点,运用贝叶斯网络扩展知识元模型的不确定性表示和推理,构建了适用于情景推演的贝叶斯网络模型,解决了非常规突发事件情景的不确定推演问题;最后,通过舟曲泥石流事件验证本文提出的模型与实际情况相符,能够为非常规突发事件应急决策提供科学有效的辅助支持.

非常规突发水灾害事件动态应急决策模式探讨

以复杂性科学为指导,提出了基于情景依赖的非常规突发水灾害事件动态应急决策模式。不同情景下,水灾害事件中的多个应急主体在强互惠者的统一指挥和协调下,通过沟通、适应、协同等规则进行自适应演化,形成以政府为主导、多主体无缝合作的共识方案,实现和支持"情景—沟通—合作—共识/认同—行动"的动态应急决策过程。以淮河流域极端洪水灾害为例,建立了淮河流域极端洪水灾害动态应急决策模式,旨在最快、最大限度地降低洪灾损失,确保灾区人民生命和财产安全。