Bayesian Network-Based Knowledge Graph Inference for Highway Transportation Safety Risks

Accurate inference of knowledge about highway transportation safety risks forms a crucial aspect of building a knowledge graph. Based on the data related to highway transportation accidents, this study has developed a Bayesian network model. The initial identification of the network nodes is through expert scoring. The network structure is then constructed by utilizing the prior expert knowledge and K2 greedy search algorithm. Later, the network parameters are trained via the expectation-maximization (EM) algorithm. Finally, knowledge about highway transportation safety risks is inferred using the junction tree algorithm. A comparison is made between the trained conditional and actual probabilities during the network parameter training to verify the validity of the proposed model that accords with expert experience, thereby proving the model validity. Further, its main “causal chain” is inferred to be an improper emergency response-human failure-accident occurrence, where the probability of driver failure is 82%, and the probability of accident occurrence is 68% by taking “a certain road traffic accident” as an example. There is consistency between the inference results and the actual accident sequence that suggests the effectiveness of the proposed knowledge inference method

Molecular dynamics study on the mechanical properties of nanocrystalline Ni-W alloys with bimodal structure

In order to study the effects of coarse grain size and Ni content on the mechanical properties, the molecular dynamics (MD) simulation of nanocrystalline (NC) Ni-W alloys with bimodal structure is carried out. The bimodal NC Ni-W alloys samples are established by embedding coarse grain into the fine grain matrix. The solute Ni atoms in the alloys are segregated in the grain boundary affected zone (GBAZ) through severe plastic deformation (SPD). The uniaxial tensile simulation of the samples shows that the coarse grain size and Ni content have obvious effects on the mechanical properties of bimodal NC Ni-W alloys. The dislocation activities and deformation mechanism of the NC Ni-W alloys are discussed in detail by observing the atomic configurations and strain evolutions diagrams obtained by MD simulation. At the same time, the phenomenon of Hall-Petch relationship and inverse Hall-Petch relationship is also observed in the research process

Erratum to: Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (Autophagy, 12, 1, 1-222, 10.1080/15548627.2015.1100356

non present