The use of social network to model the evolution of credit scores of networked enterprises is still a challenging task. This article develops an opinion dynamics model of the evolution of credit scores of enterprises in a social network. Firstly, based on the number of potential cooperated enterprises and the initial credit scores, the leader and follower enterprises are identified. Then, taking into consideration the cooperated benefit and discrimination cost, the cooperated utility between any two enterprises is calculated, which is used to compute the weights that one enterprise assigns to other enterprises. An opinion dynamics model on the evolution of credit scores of enterprises, inspired on the classical Friedkin–Johnsen’s social network model, is developed. Some desirable properties of the proposed opinion dynamics model are theoretically stated and proved. Finally, a numerical example is provided to illustrate the feasibility of the proposed opinion dynamics model, while a simulation analysis to investigate the joint influences of the connection probabilities and the network structure on the evolution of credit scores of enterprises is reported.

Studies have demonstrated that both mortality and severe illness rates exist significant difference in different gender COVID-19 patients, but the reasons are still very mysterious to date. Here, we firstly find that the survival outcome of female patients is better to male patients through analyzing the 3044 COVID-19 cases. Secondly, we identify many important master regulators [e.g. STAT1/STAT2 and zinc finger (ZNF) proteins], in particular female patients can express more ZNF proteins and stronger transcriptional activities than male patients in response to SARS-CoV-2 infection. Thirdly, we discover that ZNF protein activity is significantly negative correlation with the SARS-CoV-2 load of COVID-19 patients, and ZNF proteins as transcription factors can also activate their target genes to participate in anti-SARS-CoV-2 infection. Fourthly, we demonstrate that ZNF protein activity is positive correlation with the abundance of multiple immune cells of COVID-19 patients, implying that the highly ZNF protein activity might promote the abundance and the antiviral activity of multiple immune cells to effectively suppress SARS-CoV-2 infection. Taken together, our study proposes an underlying anti-SARS-COV-2 role of ZNF proteins, and differences in the amount and activity of ZNF proteins might be responsible for the distinct prognosis of different gender COVID-19 patients.

The aim of this paper is pricing the vulnerable options in a vague world. Due to the vulnerability of financial markets and the economy environment in the real world, investors cannot always have precise information about firm value and default recovery rate in vulnerable option pricing. Therefore, following the framework of Klein in 1996, a fuzzy binomial tree pricing model is derived by modelling the firm value and default recovery rate as fuzzy numbers. The numerical results show that the precise information assumption about the firm value and recovery rate in Klein model may lead to underestimate the credit risk on the values of vulnerable options. This study aims to provide insights for future research on defaultable options pricing under imprecise market information.

In multiple attribute group decision making (MAGDM) problems, the conflict-resolution process is a vital procedure to get an agreement with low degree of conflict. In this paper, we present a discrete model to support the conflict-resolution process. Firstly, according to the contribution index of each expert, a weight-updating model is constructed to reduce the effect of experts whose preferences are opposed to the group preference. In the preference adjustment process, an iterative algorithm is proposed to adjust the individual preferences which have the maximum deviation from the corresponding group ones to retain the original opinion of experts as much as possible. Then, the choice of the best alternative(s) from the group decision is obtained by the simple additive weighting (SAW) method. Finally, an illustrative example is given to verify the effectiveness of our model.

Owing to the fluctuations in the financial markets, many financial variables such as expected return, volatility, or exchange rate may occur imprecisely. But many portfolio selection models consider precise input of these values. Therefore, this paper studies a multiobjective international asset allocation problem under fuzzy environment. In our portfolio selection model, both of the return risk and the exchange risk are considered. The coefficient matrices in the objectives and constraints and the decision value are considered as fuzzy variables. The calculation of the portfolio and efficient frontier is derived by considering the exchange risk in the fuzzy environment. An empirical study is performed based on a portfolio of six securities denominated in six different currencies, i.e., USD, EUR, JPY, CNY, HKD, and GBP. The α-level closed interval portfolio [Formula: see text] and the fuzzy efficient frontier are obtained with different values of α ∈ (0, 1]. The empirical results indicate that the fuzzy asset selection method is a useful tool for dealing with the imprecise problem in the real world.

In group decision making, because the decision-makers usually represent different interest backgrounds, it is worth to study how to make the different decision makers coordinate and cooperate for aggregating group opinions. In this paper, based on the analytic hierarchy process, we propose a nonlinear program model to obtain consensus priority vector, and point that the model can make decision-makers reach consensus by improving compatibility of judgement matrices. Moreover, we use the genetic-simulated annealing algorithm to obtain its optimal solution. Finally, a numerical example is presented to illustrate the application of this method.

Similar to the concept of on-line auctions presented by Ron Lavi and Noam Nisan [3], this paper discusses pricing algorithms for on-line reverse auction which bidders arrive one by one and on-line buyer must be required to make a decision immediately about each bid as it is received. For online buyer in a reverse auction, we propose on-line mean pricing algorithm and on-line randomized pricing algorithm, and then prove that the two algorithms are competitive and incentive compatible. Moreover, as the bid prices concentrated in a small domain, by competitive analysis for the two algorithms, we find their merits which can avoid the results of purchasing failure or more cost caused by reservation price algorithm. Finally, an example is obtained to illustrate their application.

This paper introduces an extensible SOA-based platform that facilitates implementation of various e-collaboration systems. First, it reviews the roadmap of SOA evolution and examines the trend of service orientation in network architecture field, then it constructs a holistic service-oriented platform integrating into Web services, component-based and messaging-based technologies. After analyzing the requirements of collaboration manufacturing (CM), a typical CM model for virtual manufacturing enterprise alliance is presented. It also defines four levels of CM services according to the degree of process-centric. Finally, it illustrates how to dynamically compose a service-oriented application solution using BPEL4WS