No abstract

No abstract

Currently, the number of lightning casualties and casualty rates have significantly reduced in developed countries, but there has been no significant reduction in developing countries. On the one hand, this is due to the high frequency of lightning; on the other hand, the vulnerability of people in developing countries is also an influencing factor. Through case analysis and summary, this paper expounds on lightning injury’s mechanism and clinical manifestations. It points out that lightning injury is mainly related to heart problems and the impact on the nervous system, rather than burns, which usually cause fewer consequences. Medical treatment needs to pay attention to the order and principles of treatment. Implementing CPR and auxiliary AED is the most effective way to save lives. Attention should be paid to the practical and effective treatment and nursing of lightning stroke sequelae. Finally, combined with the situation of lightning casualties in china, the existing problems are put forward during the process of early treatment, post-hospital treatment, and nursing observation, which provides an objective basis for the cognition of the scientific nature of the lightning injury.

We have built active magnetic regenerator (AMR) test apparatuses operated with a gas displacer to transfer the heat from magnetic material unit (AMR bed). Because finding an optimum parameter by experiment is not easy, numerical simulation is necessary to confirm the experimental conditions. As the first step of the project, we developed a 1-dimensional porous media model for hydrogen magnetic refrigerator with a Brayton-like operation cycle. This model has been calculated separately for heat exchange fluid and magnetic material. The results using two different magnetic materials have been compared. We confirmed that the simulation results agreed with experimental data of the internal gas displacer system.

The purchase decisions of customers are influenced by the relevant reviews made by customers. Deceptive reviews are confusing and hard to detect. The existing identification method of deceptive reviews is based on the traditional algorithm of machine learning. However, the methods used to identify deceptive reviews must be improved. In order to improve the accuracy of the identification of deceptive reviews, a novel method integrating sentimental analysis and the characteristics of reviewers was proposed in this study. On the basis of the analysis of the emotional characteristics of the review texts and the behavioural characteristics of the reviewers, a method of deceptive review identification was established. The proposed method analyzed the intensity of emotions, the text similarity, the largest daily publishing comment index, and the extreme rating index on the basis of the feature-weighted model. This model verified the effectiveness of the proposed method. Results show that a direct correlation exists between the unreliability score of users and deceptive review identification. If the score exceeds 0.78, then the reviewer is deemed to be a deceptive reviewer, and the reviews made are deceptive reviews. The proposed method provides a good prospect to identify deceptive reviews.