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.

Consideration of the influence of supports in modeling the electromagnetic fields of 25 kV traction networks under emergency conditions

Single-phase 25 kV traction networks of electrified alternating current(AC)railways create electromagnetic fields(EMFs)with significant levels of intensity.The most intense magnetic fields occur when short circuits exist between the contact wire and rails or ground.Despite the short duration of exposure,they can adversely affect electronic devices and induce significant voltages in adjacent power lines,which is dangerous for operating personnel.Although numerous investigations have focused on modeling the EMF of traction networks and power lines,the challenge of determining the three-dimensional electromagnetic fields near metal supports during the flow of a short-circuit current through them is yet to be resolved.In this case,the field has a complex spatial structure that significantly complicates the calculations of intensities.This study proposes a methodology,algorithms,software,and digital models for determining the EMF in the described emergency scenarios.During the modeling process,the objects being studied were represented by segments of thin wires to analyze the distribution of the electric charge and calculate the intensities of the electric and magnetic fields.This approach was implemented in the Fazonord software,and the modeling results show a substantial increase in EMF levels close to the support,with a noticeable decrease in the levels as the distance from it increases.The procedure implemented in the commercial software Fazonord is universal and can be used to determine electromagnetic fields at any electrical power facility that includes live parts of limited length.Based on the proposed procedure,the EMF near the supports of overhead power lines and traction networks of various designs could be determined,the EMF levels at substations can be calculated,and the influence of metal structures located near traction networks,such as pedestrian crossings at railway stations,can be considered.

Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

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.

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.

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.

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).

Science and Technology Promotion Policies of Strategic Emerging Industries in Anhui Province

In recent years,based on advantages of industry,market,science and technology and other development environment,strategic emerging industries in Anhui Province are developing rapidly,and emerging industries such as new energy,new materials,new generation of information technology occupy an important market share in China and even the world.However,there are still a number of problems in the process of development,and the policy support has a greater impact.In this paper,the development status of strategic emerging industries in Anhui Province was discussed firstly,and then the challenges and problems of the development was discussed.Finally,some science and technology promotion policies of strategic emerging industries in Anhui Province were proposed.

An LCC-HVDC Adaptive Emergency Power Support Strategy Based on Unbalanced Power On-Line Estimation

HVDC auxiliary power control can significantly improve the transient stability of AC/DC power grid.An HVDC adaptive emergency power support method based on unbalanced power on line estimation is proposed in this paper.By establishing the extended state equation of the system,the on line dynamic estimation of unbalanced power of the system was realized.On this basis,power support was realized based on the principle of the ladder increment.The optimal DC was selected by the power support factor,and the emergency power support controller was installed on the DC.This emergency power support method can realize dynamic optimal power support with minimized control cost.The three infeed HVDC system was built on PSCAD.The simulation results show the effectiveness of the proposed method.

Knowledge,attitude and anxiety pertaining to basic life support and medical emergencies among dental interns in Mangalore City,India

BACKGROUND: This cross-sectional study aimed to assess the knowledge, attitude and anxiety pertaining to basic life support(BLS) and medical emergencies among interns in dental colleges of Mangalore city, Karnataka, India.METHODS: The study subjects comprised of interns who volunteered from the four dental colleges. The knowledge and attitude of interns were assessed using a 30-item questionnaire prepared based on the Basic Life Support Manual from American Heart Association and the anxiety of interns pertaining to BLS and medical emergencies were assessed using a State-Trait Anxiety Inventory(STAI) Questionnaire. Chi-square test was performed on SPSS 21.0(IBM Statistics, 2012) to determine statistically signifi cant differences(P<0.05) between assessed knowledge and anxiety.RESULTS: Out of 183 interns, 39.89% had below average knowledge. A total of 123(67.21%) reported unavailability of professional training. The majority(180, 98.36%) felt the urgent need of training in basic life support procedures. Assessment of stress showed a total of 27.1% participants to be above highstress level. Comparison of assessed knowledge and stress was found to be insignifi cant(P=0.983).CONCLUSION: There was an evident lack of knowledge pertaining to the management of medical emergencies among the interns. As oral health care providers moving out to the society, a focus should be placed on the training of dental interns with respect to Basic Life Support procedures.

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.

An Implementation of a Decision Support Tool to Assess Treatment of Emerging Contaminants in India

Emerging contaminants have been increasingly studied over the past decade to improve the understanding of their fate, occurrence and toxicological effects on the environment and human health. Originally wastewater treatment plants were not designed to remove these pollutants of emerging concern. However, research is now focusing on determining which existing treatment unit processes are suited to their removal. This research sets out to determine suitable treatment options for thirty nine emerging contaminants including various Pharmaceuticals and Personal Care products. The treatment options used in this study are taken from a developed decision support tool (WiSDOM) which formulates wastewater trains/packages for treatment of wastewater in India. The tool also evaluates the performance of each optimal solution in terms of removal of conventional pollutants (such as biochemical oxygen demand, chemical oxygen demand, total nitrogen, total phosphorous, faecal coliform etc.), using multi-objective genetic algorithms and multi-criteria decision analysis. An Excel Spreadsheet Program (ESP) was developed as an add-on to the tool, allowing the ESP to take an initial concentration of any of the thirty nine emerging contaminant and pass it through the treatment trains (generated/selected by the WiSDOM tool) to determine the removal efficiency. Three scenarios were developed to analyse the removal of emerging contaminants in India. The scenarios were designed to capture the influence of different socio-economic contexts and wastewater characteristics on the treatment technology selection. The tool generated results suggest that the use of constructed wetlands can remove a large proportion of emerging contaminants, resulting in low energy requirements and operational costs and wildlife habitats. However, the land requirement for this process is not always suited to urban areas in India. Advanced oxidation processes were also efficient at removing emerging contaminants. However, the energy requirements for this process were high. Emerging contaminants have different physical and chemical properties;therefore, future evaluations of each chemical should be monitored separately to generate suitable technologies suited to optimal removal.

Midwives’ Adherence to Preoperative Care Guidelines Prior to Emergency Caesarean Section at Bwaila Maternity Hospital in Malawi

A study was conducted to describe midwives’ adherence to preoperative care during emergency caesarian section at Bwaila Maternity Wing in 2012 in Malawi. The study utilized a descriptive prospective and retrospective design. A structured questionnaire was administered to all 28 midwives who were directly involved in the preparation of clients for emergency caesarean section. Clients charts were also reviewed using a standard checklist to determine adherence to preoperative care. Data were analyzed using SPSS version 16.0 and descriptive statistics in the form of frequencies and percentages were computed for the dataset. A midwife was supposed to score at least 80% on each component of preoperative care guidelines to be compliant to the stipulated pre-operation standards. The midwives scored above 80% on only four of the 14 preoperative care guidelines which were;bladder catheterization (100%, n = 14), obtaining informed consent (92.9%, n = 12), administration of IV (96.4%, n = 13) and administration of preoperative antibiotics (82.1%, n = 11). Midwives however scored less than 80% on preoperative procedures that dealt with vital signs (28.6%, n = 4): BP check (28.6%, n = 4);Pulse rate check (25%, n = 3.5);respiration check (25%, n = 3.5) and temperature check (25%, n = 3.5). The midwives scored further below standard on blood specimen collection (78.6%, n = 11). Psychological support to clients was also below standard at 60.7%, n = 8. Other components of psychological support such as surgery information (57.1%, n = 8), allowing clients ask questions (28.6%, n = 4) and answering clients’ questions (25%, n = 3.5) were also scored below standard. Overall the standard of preoperative care was below standard at the facility. Most of the midwives were new graduates, who had never received any in-service training on preoperative care. Therefore in service training it is recommended for the midwives to provide good quality of care.

Research on Occurrence Mechanism of Public Security Emergency from the perspective of the Structure Box

Public security emergency is a public crisis event, and we cannot anticipate the specific time, actual scale, specific situation and influence depth of emergencies. If the emergencies are not under control, the crisis will get worse and its destructive energy will be released quickly.Structure box is an invisible closed system which is constructed by local politics, economy, and culture. Namely, structure box is local social ecological environment. Structure box is a closed area which is full of anger. Therefore, in such environment with too much pressure, we need an outlet to release pressure. Anger is the social and psychological basis of the emotional resonance of onlooker, when the fuse incident occurred, so that the widespread anger in structure box will find the spotlight. The words and actions of the leaders in the informal group will produce a great social infection and circulatory response, and groups’ stirring will cause emotional resonance which is easy to burst. Thus, irrational behavior may caused by people. This processcan use five links to describe： occurrence of fuse events, information diffusion, emotional resonance, situational catalysis, control failure, and occurrence of public security emergency. This is the occurrence mechanism of public security emergency.

领悟社会支持对突发公共卫生事件中一线人员正念干预效用中的中介效应

目的研究正念干预在突发公共卫生事件中一线人员中的效果,并考察领悟社会支持在正念干预效用中的中介效应。方法选择2021年3月至2022年4月在医院一线工作的200名医务人员为研究对象,按照随机数字表法分为对照组和观察组,每组100名。对照组给予常规心理干预,观察组给予正念干预。干预后比较两组医护人员的正念水平、领悟社会支持能力、睡眠质量和心理情况。分析以上四者之间的相关性,采用中介效应模型分析领悟社会支持在正念干预效用中的中介效应。结果干预后,观察组医护人员的正念水平和领悟社会支持量表评分明显高于对照组(P<0.05),观察组分别为(89.59±8.45)分和(88.48±8.53)分,对照组分别为(71.35±7.47)分和(76.34±7.58)分。观察组医护人员的睡眠质量和焦虑-抑郁-压力量表评分明显低于对照组(P<0.05),分别为(7.35±1.24)分和(16.46±2.29)分,对照组分别为(13.56±2.31)分和(29.48±3.05)分。医护人员的正念水平与领悟社会能力呈正相关,两者分别与焦虑-抑郁-压力和睡眠质量呈负相关。领悟社会支持在正念水平和正念干预效果中发挥中介效应,正念与睡眠质量的总效应值为-0.347,与焦虑之间为-0.439,与抑郁之间为-0.508,与压力之间为-0.395。结论正念干预能可直接或通过领悟社会支持能力间接作用,显著提高突发公共卫生事件中一线人员改善其睡眠质量及负面情绪,具有重要临床应用价值。

数字金融推动新质生产力发展的逻辑解析、困境审视及路径设计

“新质生产力”概念是马克思主义生产力理论的最新成果,是加快实现中国式现代化的重要动力。数字金融推动新质生产力发展,主要依靠核心要素培育、科技创新支持、产业场景塑造三大逻辑,充分发挥资源配置功能,集中体现“新质”变化。数字金融紧密对接生产力变革的各个领域,提供人才、技术、资金支持,打造生产方式新质态、生产流程新质效,推动发展新技术、打造新产业、创造新动能,超前布局战略性新兴产业与未来产业发展。当前,各参与方应当注重推进数字金融服务普惠化与差异化,强调创新驱动在新质生产力发展中的核心地位,明确政策引领和法规监管对数字金融应用方向的指导规范作用,充分承担参与主体责任,为数字金融推动新质生产力发展铺平道路。

突发公共卫生事件科技支撑能力的质性研究

目的:探索应对突发公共卫生事件的科技支撑能力的构成及本质,为突发公共卫生事件的预防和处置提供支持。方法:采用扎根理论,通过访谈及收集相关文献资料,使用Nvivo软件进行开放性编码、选择性编码以及理论性编码,解构了突发公共卫生事件的科技支撑能力的构成及关系。结果:凝练出718个初始节点、139个概念节点、15个初始范畴及4个核心范畴,并以此构建了突发公共卫生事件科技支撑能力的理论模型。结论:科技支撑能力包括自主创新能力、成果转化能力、组织管理能力和抵御风险能力四个组成部分。进一步将这四种能力划分为基础层、核心层和目的层三个层次,构建了科技支撑能力的金字塔模型,系统性地理解这些能力的重要性、能力的组成及相互间的关联与依赖关系。

重大突发疫情中的对口支援关系匹配优化研究

重大突发事件中的对口支援是典型的具有中国特色的应急救援措施,也是我国社会制度优越性的重要体现。现有相关研究大多为定性研讨,鲜有从管理科学视角探讨供需双方如何实现匹配优化。研究应急响应阶段中的对口支援关系优化问题,并以全国支援湖北抗击疫情为例:首先从“人”“机”“物”等角度界定支援地供应能力,同时创新定义了受灾地的需求紧迫度和供需匹配函数,然后借鉴指派优化问题的建模思想,以加权的需求满足率最大化为目标函数,构建了应急响应阶段的对口支援结对关系匹配优化模型。计算实验表明:所提出的模型兼顾了应急资源分配的公平性,能最大限度地覆盖灾区需求情况;在资源紧缺和资源充裕两个极端情况下,“物”和“人”分别是提升灾区需求满足率的关键。