The Discrete-Time Bulk-Service Geo/Geo/1

This paper deals with a discrete-time bulk-service Geo/Geo/1 queueing system with infinite buffer space and multiple working vacations. Considering an early arrival system, as soon as the server empties the system in a regular busy period, he leaves the system and takes a working vacation for a random duration at time n. The service times both in a working vacation and in a busy period and the vacation times are assumed to be geometrically distributed. By using embedded Markov chain approach and difference operator method, queue length of the whole system at random slots and the waiting time for an arriving customer are obtained. The queue length distributions of the outside observer’s observation epoch are investigated. Numerical experiment is performed to validate the analytical results

Solid Dynamic Models for Analysis of Stress and Strain in Human Hearts

This paper proposes a solid model based on four-dimensional trivariate B-spline for strain and stress analysis of ventricular myocardium. With a series of processing steps in the four-dimensional medical images, the feature points of ventricular inner and outer wall are obtained. A B-spline surface is then used to build the dynamic deformation model of the myocardial walls. With such a surface model, a hexahedron control mesh can be constructed by sweeping the cloud data, and the ventricular solid model is built by fitting the trivariate B-spline parameters. Based on these models, a method of isogeometric analysis can be applied to calculate the stress and strain continuously distributed in the ventricle. The model is represented smoothly in the cylindrical coordinate system and is easy to measure myocardium dynamics for finding abnormal motion. Experiments are carried out for comparing the stress and strain distribution. It is found that the solid model can determine ventricular dynamics which can well reflect the deformation distribution in the heart and imply early clues of cardiac diseases

How Do Consumers Identify Useful Review Information in a Social Media Environment?

The popularity of social network services (SNS) provides consumers with new channels to obtain information, and the convenience and diversity of information help consumers reduce the uncertainty and risk in online shopping. However, with the development of the internet, increasing information is available to consumers, and the information overload of online reviews (ORs) creates higher requirements for consumer information screening. Therefore, how to quickly and accurately identify useful information becomes important. There is much literature discussing the usefulness of online word of mouth and ORs, but these studies generally explore information selection and judgment in the traditional business to consumer environment and do not specifically explore social shopping in SNS. In addition, the existing results often only consider the quality factor of ORs and ignore the influence of consumers’ personal choice preferences and the characteristics of OR publishers on consumer behavior. From this, based on the theory of planned behavior and the online trust model, this paper determines the relevant factors and frameworks that affect the usefulness of ORs in the SNS environment. We start from the perspectives of reviewer-related and information-related aspects. Partial least squares structural equation modeling (PLS-SEM) was used to analyze 237 samples for eight factors: credibility, social distance, evaluation (positive and negative), information quality (accuracy, timeliness, and integrity), and presentation. This study enriches the theory of OR usefulness in the SNS environment and provides a reference for the online marketing of enterprises

Research on the Construction Mechanism of Consumers’ Trust Intentions and Behaviors in the Context of Live Streaming Shopping

As a new-type media form integrating text, image, video, and audio, live streaming itself is an excellent way of informationcarrying and interaction. And the development of information technology makes the use of live streaming shopping easier and more convenient. At the same time, with the popularity of live streaming marketing, there are also some consumption traps, which not only harm the rights and interests of consumers but also affect its own development. Thus, how to build trust and improve the credit evaluation mechanism has become a common concern of academic and industrial circles. Anchored in the theory of planned behavior (TPB) and other research results, this paper expounds on the definition and connotation of trust intention in live streaming shopping in detail. From the perspective of consumers, the trust model of live streaming shopping is constructed based on the comprehensive consideration of social presence, consumers\u27 personal attitude, and structural assurance. It adopts partial least squares (PLS) structural equation modeling (SEM) to evaluate the research model and hypothesis. On the basis of 259 samples, the result shows that consumers\u27 trust behavior in live streaming shopping is mainly affected by live streamers\u27 personalities, comment information, social presence, platform characteristics, usefulness, and structural assurance. The research result of this paper will play a positive role in building a more credible environment, improving the trust relationship with consumers, and promoting potential transactions. Meanwhile, it also lays a foundation for understanding consumers\u27 trust behavior and related theories in the context of China

Determination of scutellarin in breviscapine preparations using quantitative proton nuclear magnetic resonance spectroscopy

AbstractThe objective of the present study was to develop the selection criteria of proton signals for the determination of scutellarin using quantitative nuclear magnetic resonance (qNMR), which is the main bioactive compound in breviscapine preparations for the treatment of cerebrovascular disease. The methyl singlet signal of 3-(trimethylsilyl)propionic-2,2,3,3-d4 acid sodium salt was selected as the internal standard for quantification. The molar concentration of scutellarin was determined by employing different proton signals. To obtain optimum proton signals for the quantification, different combinations of proton signals were investigated according to two selection criteria: the recovery rate of qNMR method and quantitative results compared with those obtained with ultra-performance liquid chromatography. As a result, the chemical shift of H-2′ and H-6′ at δ 7.88 was demonstrated as the most suitable signal with excellent linearity range, precision, and recovery for determining scutellarin in breviscapine preparations from different manufacturers, batch numbers, and dosage forms. Hierarchical cluster analysis was employed to evaluate the determination results. The results demonstrated that the selection criteria of proton signals established in this work were reliable for the qNMR study of scutellarin in breviscapine preparations