Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive data.Data security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing mechanisms.In this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary market.Moreover,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and users.Specifically,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic bidding.The incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading scenario.With temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation strategies.Furthermore,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

Neural mechanism of proposer's decision-making in the ultimatum and dictator games

Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer＇s decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. ＂The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.

A Study on Renewable Power Pricing Mechanism and Price Incentive Policies in China

The basic framework of price policies for promoting renewable power de- velopment in China is introduced. The background, concept and implementation of price policies, focused on wind power, biomass power and solar power, are summarized in the article. The experiences and lessons of implementation of these price policies are analyzed. It is concluded that reasonable price policy is quite effective for promoting re- newable power development. According to the requirement of China's renewable power development, the suggestions for improving renewable power pricing mechanism and price incentive policies are proposed.

Pricing Mechanism in Power Market Construction

The reform on electricity pricing mechanism is a critical problem in power market construction in China, and is in mutual supplementation and promotion with the latter. In particular, the pricing mechanism for electricity fed into network and that for electricity transmission and distribution as well as the relationship between coal and electricity prices, etc. have to be studied in depth. This paper presents several solutions and suggestions to these problems.

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.

Fundamental issues and solutions in the design of China's ETS pilots:Allowance allocation,price mechanism and state-owned key enterprises

This paper analyzes the three main fundamental issues in the design of China's ETS pilots,including allowance allocation,price mechanism and state-owned key enterprises,and proposed suggested solutions.For the issue of allowance allocation,we suggest that the gradual hybrid mode could be applied at the beginning,which starts with mainly free allocation and then increases auction ratio gradually.And grandfathering is a suitable method of free allocation.For the issue of price mechanism,we suggest a price floating zone with open market operation to reduce the uncertainty of prices.For the issue of state-owned key enterprises,we suggest a good coordination with SASAC,defining the state-owned property right and supervision right when state-owned key enterprises are involved into the carbon market,and the local government can set rules of allocation and transaction to limit their potential market power.

Incentive Mechanism Design for Public Goods Provision:Price Cap Regulation and Optimal Regulation

This paper studies the mechanism design that induces firms to provide public goods under two regulatory means： price cap regulation and optimal regulation, respectively. We first outline two models of monopoly regulation with unobservable marginal costs and effort, which can be regard as an optimal problem with dual restrictions. By solving this problem, we get the two optimal regulatory mechanisms to induce the provision of public goods. Further, by comparative statics, the conclusion is drawn that the welfare loss as sociated with price cap regulation, with respective to optimal regulation, increases more with increase of the expense of public goods.

Pricing Mechanism of China’s Trans-regional and Trans-provincial Electricity Trading

With the large-scale development of Chinese electric power, the contradiction of China’s energy supply and demand that reverse distributed is very prominent, therefore, promoting electricity trading is one of the important measures to get optimized configuration of energy resources in nationwide. For the two kinds of trading method, the “power point to the grid” trading and the “grid to grid” trading, this paper designed pricing mechanism model, and took one area as an example, we analyzed the impact of the participants by using different pricing mechanism, and put forward reasonable policy proposals for China’s pricing mechanism of trans-regional and trans-provincial electricity trading.

Stock Price Prediction Based on the Bi-GRU-Attention Model

The stock market, as one of the hotspots in the financial field, forms a data system with a huge volume of data and complex relationships between various factors, making stock price prediction an area of keen interest for further in-depth mining and research. Mathematical statistics methods struggle to deal with nonlinear relationships in practical applications, making it difficult to explore deep information about stocks. Meanwhile, machine learning methods, particularly neural network models and composite models, which have achieved outstanding results in other fields, are being applied to the stock market with significant results. However, researchers have found that these methods do not grasp the essential information of the data as well as expected. In response to these issues, researchers are exploring better neural network models and combining them with other methods to analyze stock data. Thus, this paper proposes the ABiGRU composite model, which combines the attention mechanism and bidirectional gated recurrent unit (GRU) that can effectively extract data features for stock price prediction research. Models such as LSTM, GRU, and Bi-LSTM are selected for comparative experiments. To ensure the credibility and representativeness of the research data, daily stock price indices of BYD are chosen for closing price prediction studies across different models. The results show that the ABiGRU model has a lower prediction error and better fitting effect on three index-based stock prices, enhancing the learning efficiency of the neural network model and demonstrating good prediction stability. This suggests that the ABiGRU model is highly adaptable for stock price prediction.

Discussion on the Formation and Trading Mechanism of Art Market Capital Price

Under the market economy system,art is a new investment channel.With the improvement of people's living standards,it has a new understanding of art investment.Based on this,this paper takes the price of art as the research object,and elaborates the price formation and transaction of the art capital market from the aspects of the intrinsic elements of art,the investment of art,the supply and demand of art market,people's boastful consumption and social education.The constraints imposed by the mechanism.

Comparison of Group-Buying Online Auction and Posted Pricing Mechanism in an Uncertain Market

Demand uncertainty is a key factor for the seller's decision making, especially in the e-business environment, for the website to sell products through the online auction. In this paper, two kinds of demand uncertainties are considered: the consumer regime uncertainty and the inherent randomness of the market environment. Then, how to use a novel business model and group-buying auction (GBA) is analyzed in such a market environment. Based on the comparison of the GBA and the posted price mechanism, some conditions that favor the GBA are provided.

Market-Oriented Electricity Pricing Mechanism Should be Eagerly Set Up in China

Electricity pricing is the core of the power institutional reform in China, which is related to not onlyinterests redistribution of all parties, but also health and security of the entire power industry. Only byaccelerating the reform on pricing mechanism can sound development of the power industry be promoted.

Dynamic Relation Mechanism between Cotton Future Price and Stock Price of Related Listed Companies

The Dynamic relation mechanism between ZCE cotton futures price and related listed company stock price has been studied based on the metastock historical data in January 1st,2007 to September 1st,2010,Johansen co-integration analysis,Vector error correction model,Granger causality test and variance decomposition method.The results indicated that:long-term equilibrium relationship existed between ZCE cotton futures price and Xinsai share stock price while which changed in the same tendency and speed in the long-term.Cotton futures price is the main reason for the changing of Xinsai share stock price.The lead-lag relationship in changing course had been confirmed that existed between ZCE cotton futures price and the Xinsai share stock price.Meanwhile,the forward pass mechanism of price changing information had been found only from the ZCE cotton futures market to the stock market while showing asymmetry.Conclusions of the study can be used for cotton and related corporate to hedge business risks by the cotton price changes.

Use of Research Evidence in Policy and Decision-Making: Views, Attitudes and Practices of Health Policy Makers in Lusaka Province of Zambia

Background: The integration of relevant high-quality research evidence into the health decision and policy formulation process is a key strategy for improving health systems especially in developing countries such as Zambia. However, the lack of capacity to understand and value research evidence by policy and decision makers makes it difficult for them to find and use research evidence in a timely manner even when motivated to do so. This study aimed to establish the views, attitudes and practices of policy makers on the use of research evidence in policy and decision-making process in Zambia. Methodology: This descriptive cross-sectional study was conducted in Lusaka, Zambia among selected public health decision and policy making institutions. A purposive sample of 21 consenting policy makers who were working in different positions in the Ministry of Health Headquarters, Provincial and District Health Offices, Health Professions Regulatory Bodies, United Nations Agencies, International Non-Governmental Organizations and University Deans from the University of Zambia participated in the study. A self-administered questionnaire was used to collect data. The IBM? SPSS? Statistics for Windows Version 20.0 was used for data analysis. Results: The concept of Evidence Informed Health Policy was not well understood such that only less than half (47.5%) of the participants reported having heard specifically about Evidence Informed Health Policy meanwhile almost two thirds (61.9%) reported that they used research evidence in decision making and policy formulation. Similar discrepancy was expressed in the understanding of and use of rapid response mechanisms such that although (47.6%) of the participants reported having heard about it, (57%) had never used rapid response mechanisms for deci-sion-making. With regard to the sources of information, about half (52.3) of the participants reported scholarly articles as their main source of evidence. Con-clusion and Recommendations: There is need for more sensitization and ca-pacity building among the decision and policy makers on the importance of using research evidence in decision and policy making process as incorporation of relevant high-quality research evidence into the health policy making pro-cess is a key strategy for improving health systems.

On the Mechanism of CDOs behind the Current Financial Crisis and Mathematical Modeling with Levy Distributions

This paper aims to reveal the mechanism of Collateralized Debt Obligations (CDOs) and how CDOs extend the current global financial crisis. We first introduce the concept of CDOs and give a brief account of the de-velopment of CDOs. We then explicate the mechanism of CDOs within a concrete example with mortgage deals and we outline the evolution of the current financial crisis. Based on our overview of pricing CDOs in various existing random models, we propose an idea of modeling the random phenomenon with the feature of heavy tail dependence for possible implements towards a new random modeling for CDOs.

Study on the roles and acting mechanism of the real estate brokerage in China second-hand housing market

As China housing reform deepens, the second-hand housing transactions become more and more popular and real estate brokerages, as an intermediary of the transactions, become an undeniable important part of this market. This article mainly explores the roles and the acting mechanism of real estate brokerages in the second-hand housing market. The results show that the participation of real estate brokers in the second-hand housing market may have positive and negative influences. On one side, brokers ease the housing transaction process and benefits buyers and sellers by shortening the sale time on the market. On the other side, if brokers are the only participants in the housing transaction, acting as buyer and seller like some firms do, housing prices will increase and this negative effect will become even stronger as the participation of many more brokers increases. Therefore, the regulation and management of the industry is vital for the long and healthy development of the housing market in China.

基于季节性碳交易机制的园区综合能源系统低碳经济调度

为有效提高碳排放配额分配的合理性,并且避免年度结算时碳排放量超标导致环境污染加剧问题,提出基于奖惩因子的季节性碳交易机制,以园区综合能源系统(park integrated energy system,PIES)为对象进行低碳经济调度。首先,构建包含能量层–碳流层–管理层的综合能源系统(integrated energy system,IES)运行框架,建立电气热多能流供需动态一致性模型;其次,分析系统内“日–季节–年度”碳排放特性,打破传统应用指标法的配额分配方法,采用灰色关联分析法建立碳排放配额分配模型,并基于奖惩阶梯碳价制定季节性碳交易机制;最后,以系统内全寿命周期运行成本及碳交易成本最小为目标,对执行季节性碳交易机制的PIES进行低碳经济调度,分析长时间尺度下季节性储能参与调度的减碳量。搭建IEEE 33节点电网5节点气网7节点热网的PIES,并基于多场景进行算例分析,验证此调度方法能够实现零碳经济运行,保证系统供能可靠性,为建立零碳园区奠定理论基础。

新上市药品首发价格形成机制与鼓励高质量创新的经济学理论分析

目的:本研究旨在探究新上市药品首发价格形成机制的经济学本质,及其面临的挑战与待解决的问题。方法:从药品价格形成机制的基本原理出发,本文引入了内生与外生价格、非对称信息博弈、创新药品市场竞争以及新制度经济学的相关理论,探索药品首发价格形成机制的经济学理论基础。结论及建议:建立合理的药品首发价格形成机制,是发挥市场在资源配置中起决定性作用的同时更好发挥政府作用的举措。以鼓励高质量创新为目标的药品首发价格形成机制,应当以降低制度性交易成本为核心目标。建议以创新价值、竞争情况等相关信息披露为基础,对新上市药品合理分类,降低信息不对称程度,治理当前新药市场的逆向选择问题。在保证高质量创新药定价权最大化的同时约束同质化创新的垄断定价权,兼顾效率和公平。