Safety Risk Analysis of Unmanned Ships in Inland Rivers Based on a Fuzzy Bayesian Network

Risk factor identification is the basis for risk assessment. To quantify the safety risks of unmanned vessels in inland rivers, through analysis of previous studies, the safety risk impact factor framework of unmanned vessels in inland rivers is established based on three aspects: the ship aspect, the environmental aspect, and the management and control aspect. Relying on Yangtze River, a fuzzy Bayesian network of the sailing safety risk of unmanned ships in inland rivers is constructed. The proposed safety risk model has considered different operational and environmental factors that affect shipping operations. Based on the fuzzy set theory, historical data, and expert judgments and on previous works are used to estimate the base value (prior values) of various risk factors. The case study assessed the safety risk probabilities of unmanned vessels in Yangtze River. By running uncertainty and sensitivity analyses of the model, a significant change in the likelihood of the occurrence of safety risk is identified, and suggests a dominant factor in risk causation. The research results can provide effective information for analyzing the current safety status for navigation systems of unmanned ships in inland rivers. The estimated safety risk provides early warning to take appropriate preventive and mitigative measures to enhance the overall safety of shipping operations. Document type: Articl

Risk factors for repeat percutaneous coronary intervention in young patients (≤45 years of age) with acute coronary syndrome

Background The incidences of premature coronary heart disease present a rising trend worldwide. The possible risk factors that may predict the incidence of repeat percutaneous coronary intervention (PCI) in premature acute coronary syndrome (ACS) remains unclear. Methods A total of 203 patients ≤45 years with ACS from Chinese PLA General Hospital who have undergone angiography twice were included in this report. Data were collected from medical records of patients during hospitalization. Baseline characteristics which have significant differences in the univariate analysis were enrolled into the multiple logistic regression analysis. According to the odds ratio (OR) of these variables, different values were assigned to build a risk model to predict the possible risk of the premature ACS patients undergoing repeat PCI. Results Of the 203 young patients, 88 patients (43.3%) underwent repeat PCI. The intermit time (OR 1.002, (95% CI [1.001–1.002])), diastolic blood pressure of second procedure (OR 0.967, (95% CI [0.938–0.996])), stent diameter (OR 0.352, (95% CI [0.148–0.840])), HbA1C of the first procedure (OR 1.835, (95% CI [1.358–2.479])), and Troponin T of the second procedure (OR 1.24, (95% CI [0.981–1.489])) were significantly associated with the incidence of repeat PCI in patients with premature ACS. An aggregate score between 0 and 6 was calculated based on these cutpoints. Conclusion For young patients with premature ACS, risk of undergoing repeat PCI was high. HbA1C was a significant, independent predictor for the incidence of repeat revascularization, and weighed more than traditional lipid profile. The glucose metabolism and disorders in patients with premature ACS should be routinely screened

Analysis of network disruption evolution of fresh cold chain

Analysis of network disruption evolution of Chinese fresh cold chai

Random disruption- <i>P</i>(<i>L</i>) with λ variation diagram.

Random disruption- P(L) with λ variation diagram.</p

Random disruption- <i>P</i>(<i>Q</i>) with λ variation diagram.

Random disruption- P(Q) with λ variation diagram.</p

Target disruption- <i>P</i>(<i>Q</i>) with λ variation diagram.

Target disruption- P(Q) with λ variation diagram.</p

Practice network data (https://osf.io/su5kv/).

(XLSX)</p

Evaluation of urban public transport priority performance based on the improved TOPSIS method: A case study of Wuhan

By comprehensively considering four subsystems (overall development level, infrastructure construction, public transportation service level and policy support), this study establishes an index system to evaluate public transport priority performance. The performance of a public transport priority implementation in the city of Wuhan from 2006 to 2015 was evaluated by applying the structural entropy-TOPSIS model. The evaluation results showed the following: The comprehensive performance of Wuhan’s public transport priority improved from poor to medium, then to good and finally, to excellent. The performance level of the four subsystems showed a trend of increasing year by year. In the future, the performance metrics for infrastructure construction, public transport service level and policy support still have significant room for improvement. While improving the overall performance of public transport, Wuhan should also pay attention to the harmonious development of subsystems and focus on improving public transport priority infrastructure construction, expanding public service levels and providing policy support. The research ideas and methods in this paper provide a realistic basis for improving the performance of urban public transport priority. The further research areas will focus on diagnosing obstacle factors affecting the performance of urban public transport priority

Random disruption- <i>P</i>(<i>N</i>) with λ variation diagram.

Random disruption- P(N) with λ variation diagram.</p

Target disruption- <i>P</i>(<i>N</i>) with λ variation diagram.

Target disruption- P(N) with λ variation diagram.</p