System Reliability Analysis Method Based on T-S FTA and HE-BN

For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.

An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

Levels of evidence and grades of recommendation supporting European society for medical oncology clinical practice guidelines

Background:The European Society for Medical Oncology(ESMO)guidelines are among the most comprehensive and widely used clinical practice guidelines(CPGs)globally.However,the level of scientific evidence supporting ESMO CPG recommendations has not been systematically investigated.This study assessed ESMO CPG levels of evidence(LOE)and grades of recommendations(GOR),as well as their trends over time across various cancer settings.Methods:We manually extracted every recommendation with the Infectious Diseases Society of America(IDSA)classification from each CPG.We examined the distribution of LOE and GOR in all available ESMO CPG guidelines across different topics and cancer types.Results:Among the 1,823 recommendations in the current CPG,30%were classified as LOEⅠ,and 43%were classified as GOR A.Overall,there was a slight decrease in LOEⅠ(−2%)and an increase in the proportion of GOR A(+1%)in the current CPG compared to previous versions.The proportion of GOR A recommendations based on higher levels of evidence such as randomized trials(LOEⅠ–Ⅱ)shows a decrease(71%vs.63%,p=0.009)while recommendations based on lower levels of evidence(LOEⅢ–Ⅴ)show an increase(29%vs.37%,p=0.01)between previous and current version.In the current versions,the highest proportion of LOEⅠ(42%)was found in recommendations related to pharmacotherapy,while the highest proportion of GOR A recommendations was found in the areas of pathology(50%)and diagnostic(50%)recommendations.Significant variability in LOEⅠand GOR A recommendations and their changes over time was observed across different cancer types.Conclusion:One-third of the current ESMO CPG recommendations are supported by the highest level of evidence.More well-designed randomized clinical trials are needed to increase the proportion of LOEⅠand GOR A recommendations,ultimately leading to improved outcomes for cancer patients.

Are case reports valuable?Exploring their role in evidence based medicine and patient care

Case reports,often overlooked in evidence-based medicine(EBM),play a pivotal role in healthcare research.They provide unique insights into rare conditions,novel treatments,and adverse effects,serving as valuable educational tools and generating new hypothesis.Despite their limitations in generalizability,case reports contribute significantly to evidence-based practice by offering detailed clinical information and fostering critical thinking among healthcare professionals.By acknowledging their limitations and adhering to reporting guidelines,case reports can contribute significantly to medical knowledge and patient care within the evolving landscape of EBM.This editorial explores the intrinsic value of case reports in EBM and patient care.

Real-World Evidence in Localized Pancreatic: Coping with Uncertainty in Unselected Populations

Background: Localized pancreatic cancer, including resectable (R), borderline resectable (BR) and locally advanced unresectable disease (LAU), is considered in clinical guidelines for diverse treatment options based on clinical trials in selected populations. Hence, exploring with real world evidence (RWE) clinicians’ preferences for treatment options and their results seems pertinent. Methods: In a set of consecutive patients with localized pancreatic cancer assisted in a third level hospital from January 2013 to December 2022, medical records, symptoms, diagnostic process, distribution between subtypes, and treatment plans, with safety and efficacy results, were assessed. Results: A total of 152 patients with localized disease were included (43.4% R, 21.0% BR, 33.6% LAU). The population characteristics exemplified differences between daily practice and clinical trials. Tumor location and symptoms were as expected. Treatment plan was conditioned by PS or comorbidities in 23.0% of patients. In patients with R disease, surgery followed by different adjuvant chemotherapy (CT) regimes was the antineoplastic treatment of choice (64.8%) with efficacy results (OS 37.5 months;95% CI 18.4 - 56.7), in the range of contemporary standards. The common use of neoadjuvant CT for BR disease (94.4%), with surgery in 50% of them, and its results (OS 30.8 months;95% CI 10.5 - 51.2) reflected current controversies of treatment recommendations and evolution in this scenario. Paliative CT with or without radiotherapy was the standard specific treatment in LAU disease (95.1%) with survival results (PFS: 10.8 months;95% CI 8.8 - 12.7. OS: 20.3 months;95% CI 13.5 - 27.2) that justify the distinct character and the specific study of this entity. Conclusion: RWE for localized pancreatic cancer aroused from the analysis of this population confirms the distinct nature of patients assisted in daily practice, as well as mirrors the complexity of decision making in clinical assumptions in which achieving stronger evidence should be paramount.

Non-alcoholic fatty liver disease in type 2 diabetes:Emerging evidence of benefit of peroxisome proliferator-activated receptors agonists and incretin-based therapies

Nonalcoholic fatty liver disease(NAFLD)is a global epidemic,affecting more than half of the people living with type 2 diabetes(T2D).The relationship between NAFLD and T2D is bidirectional and the presence of one perpetuates the other,which significantly increases the hepatic as well as extrahepatic complications.Until recently,there was no approved pharmacological treatment for NAFLD/nonalcoholic steatohepatitits(NASH).However,there is evidence that drugs used for diabetes may have beneficial effects on NAFLD.Insulin sensitizers acting through peroxisome proliferator-activated receptor(PPAR)modulation act on multiple levels of NAFLD pathogenesis.Pioglitazone(PPARγ agonist)and saroglitazar(PPARα/γagonist)are particularly beneficial and recommended by several authoritative bodies for treating NAFLD in T2D,although data on biopsyproven NASH are lacking with the latter.Initial data on elafibanor(PPARα/δ agonist)and Lanifibranor(pan PPAR agonist)are promising.On the other hand,incretin therapies based on glucagon-like peptide-1(GLP-1)receptor agonists(GLP-1RA)and dual-and triple-hormone receptor co-agonists reported impressive weight loss and may have anti-inflammatory and antifibrotic properties.GLP-1 RAs have shown beneficial effects on NAFLD/NASH and more studies on potential direct effects on liver function by dual-and triple-agonists are required.Furthermore,the long-term safety of these therapies in NAFLD needs to be established.Collaborative efforts among healthcare providers such as primary care doctors,hepatologists,and endocrinologists are warranted for selecting patients for the best possible management of NAFLD in T2D.

Preceptors'experiences in guiding nursing students to use research findings and to implement evidence-based practice

Objective:Evidence-based practices(EBPs)have been taught to students by identifying the best evidence/evidence from research results.However,the experiences of Indonesian nurse preceptors in helping students implement research findings have not been explored thoroughly.This study aimed to explore Indonesian nurse preceptors in guiding nursing students to use research findings.Methods:This study used interpretive phenomenology analysis that involves 9 nurse preceptors from hospitals in West Kalimantan,Indonesia.Semi-structured in-depth interviews were recorded and then transcribed verbatim.Results:Three themes were generated during the analysis:“types of student supervision,”“issues during supervision,”and“the need for research literacy and supervision.”Conclusions:Nurse preceptors need support to supervise the nursing students to use research findings.In addition to upgrading nursing skills,nurse preceptors must receive training in research and its utilization.Developing an appropriate strategy to assist students in using research findings will enhance the promotion of evidence-based nursing practices on a daily basis.

Security Risk Assessment in Container Terminals:Empirical Evidence from Greece

The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lines of environmental,health and hygiene and port product issues.This paper examines security risk assessment approaches within the emerging role of ports.This paper contributes to the current literature by considering the ports of Greece as a case in point and by measuring the degree of its security risk orientation based on certain valid risk factors drawn from the current literature.Moreover,it presents a security risk assessment methodology into the domain of port container terminals.Their potential for ports were quantitatively and qualitatively assessed by discussing issues of security approaches within the maritime industry,in order to facilitate improvement strategies.A two-dimension empirical study was conducted,in a time range of ten years(2010-2020)in order to provide evidence regarding security risk assessment in the port container terminal of Thessaloniki,in Greece.The findings of this study have significant strategic policy implications and shed more light on the role of security risks in the overall risk orientation of container terminals in practice.Finally,further research directions in security risk in ports are proposed.

Summary of the Best Evidence for Tube Feeding Intolerance in Critically Ill Children

Objective:To summarize the evidence of tube feeding intolerance in critically ill children,aiming to provide evidence-based information for clinical nursing staff.Methods:Evidence search was done in Chinese and English databases to guide network and professional associations at home and abroad.The search time limit was from January 2014 to January 2024,nearly 10 years of relevant literature,mainly including guidelines,consensus,expert advice,best practice,evidence summary,system evaluation,and meta-analysis.Literature quality evaluation and evidence extraction were independently performed by two researchers.Results:This paper included 13 articles,including three guidelines,three systematic evaluations,three expert opinions,and four expert consensus.Twenty-six pieces of evidence were summarized from 10 aspects of feeding intolerance definition,team building,nutritional assessment,nutritional preparation,feeding protocol,feeding route,feeding management,pipeline management,gastric residual volume,and drug application.Conclusion:This paper summarized the evidence of tube feeding intolerance in critically ill children,which can provide evidence-based information for clinical practice.The abdominal signs should be closely observed when evaluating feeding intolerance,focusing on the prevention and reduction of feeding interruption.

Endoscopic ultrasound-guided treatments: Are we getting evidence based- a systematic review

The continued need to develop less invasive alternatives to surgical and radiologic interventions has driven the development of endoscopic ultrasound(EUS)-guided treatments.These include EUS-guided drainage of pancreatic fluid collections,EUS-guided necrosectomy,EUS-guided cholangiography and biliary drainage,EUSguided pancreatography and pancreatic duct drainage,EUS-guided gallbladder drainage,EUS-guided drainage of abdominal and pelvic fluid collections,EUS-guided celiac plexus block and celiac plexus neurolysis,EUSguided pancreatic cyst ablation,EUS-guided vascular interventions,EUS-guided delivery of antitumoral agents and EUS-guided fiducial placement and brachytherapy.However these procedures are technically challenging and require expertise in both EUS and interventional endoscopy,such as endoscopic retrograde cholangiopancreatography and gastrointestinal stenting.We undertook a systematic review to record the entire body of literature accumulated over the past 2decades on EUS-guided interventions with the objective of performing a critical appraisal of published articles,based on the classification of studies according to levels of evidence,in order to assess the scientific progress made in this field.

AN INTRUSION DETECTION SYSTEM BASED ON EVIDENCE THEORY AND ROUGH SET THEORY

In this paper,we propose a novel Intrusion Detection System (IDS) architecture utilizing both the evidence theory and Rough Set Theory (RST). Evidence theory is an effective tool in dealing with uncertainty question. It relies on the expert knowledge to provide evidences,needing the evidences to be independent,and this make it difficult in application. To solve this problem,a hybrid system of rough sets and evidence theory is proposed. Firstly,simplification are made based on Variable Precision Rough Set (VPRS) conditional entropy. Thus,the Basic Belief Assignment (BBA) for all evidences can be calculated. Secondly,Dempster’s rule of combination is used,and a decision-making is given. In the proposed approach,the difficulties in acquiring the BBAs are solved,the correlativity among the evidences is reduced and the subjectivity of evidences is weakened. An illustrative example in an intrusion detection shows that the two theories combination is feasible and effective.

A Digital Evidence Fusion Method in Network Forensics Systems with Dempster-Shafer Theory

Network intrusion forensics is an important extension to present security infrastructure,and is becoming the focus of forensics research field.However,comparison with sophisticated multi-stage attacks and volume of sensor data,current practices in network forensic analysis are to manually examine,an error prone,labor-intensive and time consuming process.To solve these problems,in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments,and fuse digital evidence from different sources such as hosts and sub-networks automatically.In the end,we evaluate the method on well-known KDD Cup1999 dataset.The results prove our method is very effective for real-time network forensics,and can provide comprehensible messages for a forensic investigators.

Fault diagnosis method of hydraulic system based on fusion of neural network and D-S evidence theory

According to fault type diversity and fault information uncertainty problem of the hydraulic driven rocket launcher servo system（HDRLSS） , the fault diagnosis method based on the evidence theory and neural network ensemble is proposed. In order to overcome the shortcomings of the single neural network, two improved neural network models are set up at the com-mon nodes to simplify the network structure. The initial fault diagnosis is based on the iron spectrum data and the pressure, flow and temperature（PFT） characteristic parameters as the input vectors of the two improved neural network models, and the diagnosis result is taken as the basic probability distribution of the evidence theory. Then the objectivity of assignment is real-ized. The initial diagnosis results of two improved neural networks are fused by D-S evidence theory. The experimental results show that this method can avoid the misdiagnosis of neural network recognition and improve the accuracy of the fault diagnosis of HDRLSS.

Fault Isolation of Light Rail Vehicle Suspension System Based on D-S Evidence Theory and Improvement Application Case

This paper presents an innovative approach for the fault isolation of Light Rail Vehicle (LRV) suspension system based on the Dempster-Shafer (D-S) evidence theory and its improvement application case. The considered LRV has three rolling stocks and each one equips three sensors for monitoring the suspension system. A Kalman filter is applied to generate the residuals for fault diagnosis. For the purpose of fault isolation, a fault feature database is built in advance. The Eros and the norm distance between the fault feature of the new occurred fault and the one in the feature database are applied to measure the similarity of the feature which is the basis for the basic belief assignment to the fault, respectively. After the basic belief assignments are obtained, they are fused by using the D-S evidence theory. The fusion of the basic belief assignments increases the isolation accuracy significantly. The efficiency of the proposed method is demonstrated by two case studies.

Expert system for earthquake prediction（ESEP）（2）－Knowledge representation and evidence combination

This paper deals with knowledge representation of ESEP (Expert System for Earthqauke Prediction). Attending the characteristics of the knowledge in earthquake prediction domain, production representation and procedural representation are connected in the knowledge repesentation model of ESEP named ESEP/K, and three new ways of evidence conbination are proposed for production rules besides 'AND' and 'OR'.

A Map-Matching Algorithm forGPS/DR Integrated Navigation Systems Basedon Dempster-Shafer Evidence Reasoning

GPS (Global Positioning System) has been widely used in car navigation systems. Most car navigation systems estimate the car position from GPS and DR (dead reckoning). However, the unknown GPS noise characteristic and the unbounded DR accumulation of errors over time make the position information with undesirable position errors. The map matching can improve the position accuracy and availability of the vehicular position system. In this paper, general principle of map matching is investigated according to segmentation and feature extraction, and a map matching algorithm based on D-S (Dempster-Shafer) evidence reasoning for GPS integrated navigation system is proposed, which can find the exact road on which a car moves. For the experiments, a car navigation system is developed with some sensors and the field test demonstrates the effectiveness and applicability of the algorithm for the car location and navigation.

An Approach for Designing and Implementing Evidence Management Systems

Generally speaking, the software of management systems in law field is based on the frames of events. However, we are going to study and develop the new software of management system in which the basic elements are evidence. This kind of software is often called evidence management system. Here we are supposed to present a designing plan and an implementing approach for the evidence management system in detail. Some functions such as global, dynamic and systematic managing of evidence can be implemented in this system. We attempt to provide a function of individual searching as well. Users may carry out multi-dimensional data analysis based on the information of our database of the management systems.

A novel adaptive temporal-spatial information fusion model based on Dempster-Shafer evidence theory

In the field of target recognition based on the temporal-spatial information fusion,evidence the-ory has received extensive attention.To achieve accurate and efficient target recognition by the evi-dence theory,an adaptive temporal-spatial information fusion model is proposed.Firstly,an adaptive evaluation correction mechanism is constructed by the evidence distance and Deng entropy,which realizes the credibility discrimination and adaptive correction of the spatial evidence.Secondly,the credibility decay operator is introduced to obtain the dynamic credibility of temporal evidence.Finally,the sequential combination of temporal-spatial evidences is achieved by Shafer’s discount criterion and Dempster’s combination rule.The simulation results show that the proposed method not only considers the dynamic and sequential characteristics of the temporal-spatial evidences com-bination,but also has a strong conflict information processing capability,which provides a new refer-ence for the field of temporal-spatial information fusion.

A New Prediction System Based on Self-Growth Belief Rule Base with Interpretability Constraints

Prediction systems are an important aspect of intelligent decisions.In engineering practice,the complex system structure and the external environment cause many uncertain factors in the model,which influence the modeling accuracy of the model.The belief rule base(BRB)can implement nonlinear modeling and express a variety of uncertain information,including fuzziness,ignorance,randomness,etc.However,the BRB system also has two main problems:Firstly,modeling methods based on expert knowledge make it difficult to guarantee the model’s accuracy.Secondly,interpretability is not considered in the optimization process of current research,resulting in the destruction of the interpretability of BRB.To balance the accuracy and interpretability of the model,a self-growth belief rule basewith interpretability constraints(SBRB-I)is proposed.The reasoning process of the SBRB-I model is based on the evidence reasoning(ER)approach.Moreover,the self-growth learning strategy ensures effective cooperation between the datadriven model and the expert system.A case study showed that the accuracy and interpretability of the model could be guaranteed.The SBRB-I model has good application prospects in prediction systems.