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.

A Multi-Attribute Decision-Making Method Using Belief-Based Probabilistic Linguistic Term Sets and Its Application in Emergency Decision-Making

Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers(DMs)in certain circumstances,such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete,thus affecting their role in the decision-making process.Belief function theory is a leading streamof thought in uncertainty processing that is suitable for dealing with the limitations of PLTS.Therefore,the purpose of this study is to extend PLTS to incorporate belief function theory.First,we provide the basic concepts of the extended PLTS(i.e.,belief-based PLTS)through case analyses.Second,the aggregation operator of belief-based PLTS is defined with the ordered weighted average(OWA)-based soft likelihood function,which is improved by considering the reliability of the information source.Third,to measure the magnitude of different belief-based PLTSs,the belief interval of singleton is calculated,and the comparison method of belief-based PLTS is constructed based on probabilities.On the basis of the preceding discussion,we further develop an emergency decision framework that includes several novel techniques,such as attribute weight determination and decision information aggregation.Finally,the usefulness of the framework is demonstrated through a case study,and its effectiveness is illustrated through a series of comparisons.

Emergency Decision-Making Based on q-Rung Orthopair Fuzzy Rough Aggregation Information

With the frequent occurrences of emergency events,emergency decision making(EDM)plays an increasingly significant role in coping with such situations and has become an important and challenging research area in recent times.It is essential for decision makers to make reliable and reasonable emergency decisions within a short span of time,since inappropriate decisions may result in enormous economic losses and social disorder.To handle emergency effectively and quickly,this paper proposes a new EDM method based on the novel concept of q-rung orthopair fuzzy rough(q-ROPR)set.A novel list of q-ROFR aggregation information,detailed description of the fundamental characteristics of the developed aggregation operators and the q-ROFR entropy measure that determine the unknown weight information of decision makers as well as the criteria weights are specified.Further an algorithm is given to tackle the uncertain scenario in emergency to give reliable and reasonable emergency decisions.By using proposed list of q-ROFR aggregation information all emergency alternatives are ranked to get the optimal one.Besides this,the q-ROFR entropy measure method is used to determine criteria and experts’weights objectively in the EDM process.Finally,through an illustrative example of COVID-19 analysis is compared with existing EDM methods.The results verify the effectiveness and practicability of the proposed methodology.

Non-Cooperative Behavior Management in Large-Scale Group Decision-Making Considering the Altruistic Behaviors of Experts and Its Application in Emergency Alternative Selection

Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooperative behavior management assumed that the maximumdegree of cooperation of experts is to totally accept the revisions suggested by the moderator,which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process.In addition,when grouping a large group into subgroups by clustering methods,existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously.In this study,we introduce a clustering method considering the similarity of evaluation values and the trust relations of experts and then develop a consensusmodel taking into account the altruistic behaviors of experts.First,we cluster experts into subgroups by a constrained Kmeans clustering algorithm according to the opinion similarity and trust relationship of experts.Then,we calculate the weights of experts and clusters based on the centrality degrees of experts.Next,to enhance the quality of consensus reaching,we identify three kinds of non-cooperative behaviors and propose corresponding feedback mechanisms relying on the altruistic behaviors of experts.A numerical example is given to show the effectiveness and practicality of the proposed method in emergency decision-making.The study finds that integrating altruistic behavior analysis in group decision-making can safeguard the interests of experts and ensure the integrity of decision-making information.

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.

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Innovative pathways allow safe discharge of mild acute pancreatitis from the emergency room

Acute pancreatitis(AP)is a leading cause of gastrointestinal-related hospitalizations in the United States,resulting in 300000 admissions per year with an estimated cost of over$2.6 billion annually.The severity of AP is determined by the presence of pancreatic complications and end-organ damage.While moderate/severe pancreatitis can be associated with significant morbidity and mortality,the majority of patients have a mild presentation with an uncomplicated course and mortality rate of less than 2%.Despite favorable outcomes,the majority of mild AP patients are admitted,contributing to healthcare cost and burden.In this Editorial we review the performance of an emergency department(ED)pathway for patients with mild AP at a tertiary care center with the goal of reducing hospitalizations,resource utilization,and costs after several years of implementation of the pathway.We discuss the clinical course and outcomes of mild AP patients enrolled in the pathway who were successfully discharged from the ED compared to those who were admitted to the hospital,and identify predictors of successful ED discharge to select patients who can potentially be triaged to the pathway.We conclude that by implementing innovative clinical pathways which are established and reproducible,selected AP patients can be safely discharged from the ED,reducing hospitalizations and healthcare costs,without compromising clinical outcomes.We also identify a subset of patients most likely to succeed in this pathway.

Risk factors for postpartum posttraumatic stress disorder after emergency admission

BACKGROUND:Postpartum posttraumatic stress disorder(PTSD)can occur in women who give birth after emergency admission.The identification of risk factors for this condition is crucial for developing effective preventive measures.This retrospective study aimed to explore the incidence and risk factors for postpartum PTSD in women who give birth after emergency admission.METHODS:Medical records of women who gave birth after emergency admission were collected between March 2021 and April 2023.The patients’general conditions and perinatal clinical indicators were recorded.The puerperae were divided into PTSD group and control group based on symptom occurrence at six weeks postpartum.Multivariate logistic regression analysis was performed to identify risk factors.RESULTS:A total of 276 puerperae were included,with a PTSD incidence of 20.3% at six weeks postpartum.Multivariate logistic regression analysis identified emergency cesarean section(odds ratio[OR]=2.102;95%confidence interval[CI]:1.114-3.966,P=0.022),admission to the emergency department after midnight(12:00 AM)(OR=2.245;95%CI:1.170-4.305,P<0.001),and cervical dilation(OR=3.203;95%CI:1.670–6.141,P=0.039)as independent risk factors for postpartum PTSD.Analgesia pump use(OR=0.500;95%CI:0.259–0.966,P=0.015)was found to be a protective factor against postpartum PTSD.CONCLUSION:Emergency cesarean section,admission to the emergency department after midnight,and cervical dilation were identified as independent risk factors for postpartum PTSD,while analgesic pump use was a protective factor.These findings provide insights for developing more effective preventive measures for women who give birth after emergency admission.

Mega-Constellations Based TT&C Resource Sharing: Keep Reliable Aeronautical Communication in an Emergency

With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of the aircraft play an important role in the judgment and command of the Operational Control Center(OCC). However, how to transmit various operational status data from abnormal aircraft back to the OCC in an emergency is still an open problem. In this paper, we propose a novel Telemetry, Tracking,and Command(TT&C) architecture named Collaborative TT&C(CoTT&C) based on mega-constellation to solve such a problem. CoTT&C allows each satellite to help the abnormal aircraft by sharing TT&C resources when needed, realizing real-time and reliable aeronautical communication in an emergency. Specifically, we design a dynamic resource sharing mechanism for CoTT&C and model the mechanism as a single-leader-multi-follower Stackelberg game. Further, we give an unique Nash Equilibrium(NE) of the game as a closed form. Simulation results demonstrate that the proposed resource sharing mechanism is effective, incentive compatible, fair, and reciprocal. We hope that our findings can shed some light for future research on aeronautical communications in an emergency.

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done.

A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

Factors Associated with Mortality in Diabetic Patients with End-Stage Renal Failure Starting Emergency Hemodialysis

Background: Diabetic nephropathy is the leading cause of end-stage chronic kidney disease with poor prognosis in resource-limited settings. This study aimed to determine factors associated with mortality in patients starting dialysis treatment for end-stage chronic renal disease in an emergency context. Patients and Methods: This was a retrospective study from January 2020 to December 2022 at CHU-B. Data from 79 diabetic patients requiring emergency dialysis were compared with those of 79 non-diabetic patients with an end-stage renal disease requiring emergency dialysis. Data were collected from the Nephrology Department registry. We studied their initial clinical and biological profiles and factors related to mortality. Results: Out of 545 compiled records, 79 diabetic chronic kidney disease patients needing dialysis were included (group 1). A control group of 79 non-diabetic chronic kidney disease patients requiring emergency dialysis was also included (group 2). The average age of patients was 53.5 ± 17 years, and the duration of diabetes at dialysis initiation was 14.8 ± 4.3 years. Twenty-three percent were hypertensive. Fifty-two percent of patients experienced intra-dialytic hypotension. Death occurred in 22% of patients. Results show that age (adjusted OR 1.955;CI: 1.025 - 1.086;p-value: Conclusion: Emergency dialysis in diabetics is associated with unfavorable outcomes in terms of mortality. Despite follow-up, renal involvement remains poorly explored, emphasizing the need for physician awareness.

Management of obstructed colorectal carcinoma in an emergency setting:An update

Colorectal carcinoma is common,particularly on the left side.In 20%of patients,obstruction and ileus may be the first clinical manifestations of a carcinoma that has advanced(stage II,III or even IV).Diagnosis is based on clinical presentation,plain abdominal radiogram,computed tomography(CT),CT colonography and positron emission tomography/CT.The best management strategy in terms of short-term operative or interventional and long-term oncological outcomes re-mains unknown.For the most common left-sided obstruction,the first choice should be either emergency surgery or endoscopic decompression by self-expen-dable metal stents or tubes.The operative plan should be either one-stage or two-stage resection.One-stage resection with on-table bowel decompression and irrigation can be accompanied or not accompanied by proximal defunctioning stoma(colostomy or ileostomy).Primary anastomosis is more convenient but has increased risks of anastomotic leakage and morbidity.Two-stage resection(Hart-mann’s procedure)is safer and the most widely used despite temporally affecting quality of life.Damage control surgery in high-risk frail patients is less frequently performed since it can be successfully substituted with endoscopic stenting or tubing.For the less common right-sided obstruction,one-stage surgical resection is more beneficial than endoscopic decompression.The role of minimally invasive surgery(laparoscopic or robotic)is a subject of debate.Emergency laparoscopic-assisted management is advantageous to some extent but requires much expertise due to inherent difficulties in dissecting the distended colon and the risk of rup-ture and subsequent septic complications.The decompressing stent as a bridge to elective surgery more substantially decreases the risks of morbidity and mortality than emergency surgery for decompression and has equivalent medium-term overall survival and disease-free survival rates.Its combination with neoadjuvant chemotherapy or radiation may have a positive effect on long-term oncological outcomes.Management plans are crucial and must be individualized to better fit each case.Core Tip:Acute obstruction is common in patients with more advanced colorectal carcinoma and may be the first manifestation mainly of left-sided obstruction and in elderly individuals.Emergency decompression is mandatory.Emergency surgical resection and primary anastomosis accompanied or not accompanied by proximal defunctioning stoma must be the first treatment choice for fit patients under 70 years.Hartmann’s two-stage procedure,although more preferable,must be the second alternative choice.Emergency endoscopic self-expendable metal stents must be preferred in unfit patients as a bridge to surgery and for palliative treatment in all inoperable cases.However,these basic management principles constitute a general direction.Decision-making is important and should be individualized.

Low-temperature characteristicsof rubbers and performance testsof type 120 emergencyvalve diaphragms

Purpose–The type 120 emergency valve is an essential braking component of railway freight trains,butcorresponding diaphragms consisting of natural rubber(NR)and chloroprene rubber(CR)exhibit insufficientaging resistance and low-temperature resistance,respectively.In order to develop type 120 emergency valverubber diaphragms with long-life and high-performance,low-temperatureresistant CR and NR were processed.Design/methodology/approach–The physical properties of the low-temperature-resistant CR and NRwere tested by low-temperature stretching,dynamic mechanical analysis,differential scanning calorimetryand thermogravimetric analysis.Single-valve and single-vehicle tests of type 120 emergency valves werecarried out for emergency diaphragms consisting of NR and CR.Findings–The low-temperature-resistant CR and NR exhibited excellent physical properties.The elasticityand low-temperature resistance of NR were superior to those of CR,whereas the mechanical properties of thetwo rubbers were similar in the temperature range of 0℃–150℃.The NR and CR emergency diaphragms metthe requirements of the single-valve test.In the low-temperature single-vehicle test,only the low-temperaturesensitivity test of the NR emergency diaphragm met the requirements.Originality/value–The innovation of this study is that it provides valuable data and experience for futuredevelopment of type 120 valve rubber diaphragms.

Approach to traumatic cardiac arrest in the emergency department: a narrative literature review for emergency providers

BACKGROUND:Traumatic cardiac arrest(TCA)is a major contributor to mortality and morbidity in all age groups and poses a significant burden on the healthcare system.Although there have been advances in treatment modalities,survival rates for TCA patients remain low.This narrative literature review critically examines the indications and eff ectiveness of current therapeutic approaches in treating TCA.METHODS:We performed a literature search in the PubMed and Scopus databases for studies published before December 31,2022.The search was refi ned by combining search terms,examining relevant study references,and restricting publications to the English language.Following the search,943 articles were retrieved,and two independent reviewers conducted a screening process.RESULTS:A review of various studies on pre-and intra-arrest prognostic factors showed that survival rates were higher when patients had an initial shockable rhythm.There were conflicting results regarding other prognostic factors,such as witnessed arrest,bystander cardiopulmonary resuscitation(CPR),and the use of prehospital or in-hospital epinephrine.Emergency thoracotomy was found to result in more favorable outcomes in cases of penetrating trauma than in those with blunt trauma.Resuscitative endovascular balloon occlusion of the aorta(REBOA)provides an advantage to emergency thoracotomy in terms of occupational safety for the operator as an alternative in managing hemorrhagic shock.When implemented in the setting of aortic occlusion,emergency thoracotomy and REBOA resulted in comparable mortality rates.Veno-venous extracorporeal life support(V-V ECLS)and veno-arterial extracorporeal life support(V-A ECLS)are viable options for treating respiratory failure and cardiogenic shock,respectively.In the context of traumatic injuries,V-V ECLS has been associated with higher rates of survival to discharge than V-A ECLS.CONCLUSION:TCA remains a signifi cant challenge for emergency medical services due to its high morbidity and mortality rates.Pre-and intra-arrest prognostic factors can help identify patients who are likely to benefit from aggressive and resource-intensive resuscitation measures.Further research is needed to enhance guidelines for the clinical use of established and emerging therapeutic approaches that can help optimize treatment effi cacy and ameliorate survival outcomes.

Decision-Making and Management of Self-Care in Persons with Traumatic Spinal Cord Injuries: A Preliminary Study

Patients and physicians understand the importance of self-care following spinal cord injury (SCI), yet many individuals with SCI do not adhere to recommended self-care activities despite logistical supports. Neurobehavioral determinants of SCI self-care behavior, such as impulsivity, are not widely studied, yet understanding them could inform efforts to improve SCI self-care. We explored associations between impulsivity and self-care in an observational study of 35 US adults age 18 - 50 who had traumatic SCI with paraplegia at least six months before assessment. The primary outcome measure was self-reported self-care. In LASSO regression models that included all neurobehavioral measures and demographics as predictors of self-care, dispositional measures of greater impulsivity (negative urgency, lack of premeditation, lack of perseverance), and reduced mindfulness were associated with reduced self-care. Outcome (magnitude) sensitivity, a latent decision-making parameter derived from computationally modeling successive choices in a gambling task, was also associated with self-care behavior. These results are preliminary;more research is needed to demonstrate the utility of these findings in clinical settings. Information about associations between impulsivity and poor self-care in people with SCI could guide the development of interventions to improve SCI self-care and help patients with elevated risks related to self-care and secondary health conditions.

Crossing the Achilles Heel of Algorithms:Identifying the Developmental Dilemma of Artificial Intelligence-Assisted Judicial Decision-Making

In the developmental dilemma of artificial intelligence(AI)-assisted judicial decision-making,the technical architecture of AI determines its inherent lack of transparency and interpretability,which is challenging to fundamentally improve.This can be considered a true challenge in the realm of AI-assisted judicial decision-making.By examining the court’s acceptance,integration,and trade-offs of AI technology embedded in the judicial field,the exploration of potential conflicts,interactions,and even mutual shaping between the two will not only reshape their conceptual connotations and intellectual boundaries but also strengthen the cognition and re-interpretation of the basic principles and core values of the judicial trial system.

An Emergency Plan Selection Method for Emergency Latency

Drawing upon a characteristic analysis of the latency period in emergencies,this paper proposes an emergency plan selection method based on interval language variables and information entropy to address the challenge of acquiring critical information during this crucial stage.Initially,decision-makers employ interval language variables to express the preference information regarding emergency plans,while also introducing an enhanced information entropy theory to derive the weight coefficients of key indicators.Subsequently,the weighted arithmetic average operator of interval language is applied twice to aggregate the preference information alongside the relative importance of decision-makers and the weight coefficients of key indicators.Finally,the ranking coefficients of each emergency plan are sorted to determine the optimal scheme.The feasibility and effectiveness of this method are demonstrated through a case study involving the selection of an emergency plan for a flood disaster in a specific location.