借代推测与间接言语行为

语用学可从哲学和认知科学两个角度研究。对间接言语行为的施为用意的研究主要是从哲学角度进行的,然而哲学并不能满意地回答受话者是如何以光速领悟说者的间接施为用意的。Panther和Thornburg提出言语行为图式的假设,认为言语行为是个整体,各部分由借代链接连接,从认知语言学的角度对这一问题给与比较合理的回答,是当代认知语用学一个重要发展。     

间接前指标准的认知解读

间接前指是一种较难把握的句法语义现象,Sidorov＆Gelbukh（1999）提出了两条指导性的标准,并辅以大量的例证说明标准的实用性,但两位学者没有对提出标准的依据展开讨论。本文从指称词语所对应的认知地位入手,结合语言运用的认知处理过程,对两条标准的认知理据展开探讨,验证了两条标准的可靠性。     

商业银行利率风险管理技术综述

一、引言(一)现实背景从2000年9月21日起,我国利率市场化改革进入实质性阶段,预计三年内完成。利率市场化是一场系统性的金融革命,必将对经济金融领域的方方面面产生重要影响。商业银行应积极采取措施,应对利率市场化将带来的一系列风险。近几年,我国发行了大量的国债和金融债,     

经济承压背景下中国能源经济预测与展望

2019年中央经济工作会议强调,中国正处在转变发展方式、优化经济结构、转换增长动力的攻关期,经济下行压力不断加大。以此为背景阐述能源经济发展现状,分析重点行业发展前景,通过不同情景下的预测分析,探讨经济承压背景下中国能源经济发展的路径与趋势。根据预测结果,经济承压对各行业的能源消费量存在普遍影响,尤其是煤炭、黑色金属冶炼和汽车行业的能源消费量在未来一段时间将呈下降趋势;在基准情形下,预计到2030年,中国GDP将达到171.97万亿元（2018年不变价水平）,能源消费总量约57.09亿吨标准煤,煤炭消费占比将不断下降,清洁能源占比预计达到41.7%。根据预测结果,有针对性地在能源消费结构、能源效率和能源合作方面提出政策建议。     

Scenario Tree Modeling to Analyze the Probability of Classical Swine Fever Virus Introduction into Member States of the European Union

The introduction of classical swine fever virus (CSFV) into a country free of disease without vaccination may have huge consequences in terms of both disease spread and economic losses. More quantitative insight into the main factors determining the probability of CSFV introduction (PCSFV) is needed to optimally use resources for the prevention of CSFV introduction. For this purpose a spreadsheet model was constructed that calculates the annual PCSFV into member states of the European Union (EU). The scenario pathway approach was used as most probabilities in the model are very small. Probability distributions were used to take into account inherent variability of input parameters. The model contained pathways of CSFV introduction including the import of pigs and pork products, returning livestock trucks, and contacts with wild boar. All EU member states were included as possible sources of CSFV. Default results for the Netherlands showed a mean overall annual PCSFV of approximately 0.06, indicating that the Netherlands can expect CSFV introduction on average once every 18 years from the pathways and countries included in the model. Almost 65% of this probability could be attributed to the pathway of returning livestock trucks. The most likely sources of CSFV introduction were Germany, Belgium, and the United Kingdom. Although the calculated probabilities were rather low when compared with expert estimates and recent history, the most likely causes of CSFV introduction indicated by the model were considered to be realistic. It was therefore concluded that the model is a useful tool to structure and analyze information for decision making concerning the prevention of CSFV introduction.     

LMDI方法分析结构效应对天津市碳排放的影响及对策

文章对1995—2010年天津市能源消费碳排放进行分析,基于对数平均迪氏指数法（ LMDI）,对碳排放进行因素分解实证研究,并进行情景分析,寻求天津市碳减排对策。研究发现,虽然人均GDP效应、人口效应以及能源强度效应贡献量相对较大,但结构效应对于天津碳排放的影响也不容忽视,其对于能源消费碳排放的拉动或减缓作用与低碳能源比重、第三产业比重的大小有很强的关联性。情景分析进一步表明优化产业及能源结构对碳减排的积极作用。     

《红岩启示录》油画作品美学论

高小华先生在创作中大胆尝试,将历史文物与艺术形式有机结合,并采用现代艺术形式拓展传统油画.文章通过五个方面,论述这一歌颂中华民族伟大精神的历史画卷的艺术性和思想性.     

Communicating Geographical Risks in Crisis Management: The Need for Research

In any crisis, there is a great deal of uncertainty, often geographical uncertainty or, more precisely, spatiotemporal uncertainty. Examples include the spread of contamination from an industrial accident, drifting volcanic ash, and the path of a hurricane. Estimating spatiotemporal probabilities is usually a difficult task, but that is not our primary concern. Rather, we ask how analysts can communicate spatiotemporal uncertainty to those handling the crisis. We comment on the somewhat limited literature on the representation of spatial uncertainty on maps. We note that many cognitive issues arise and that the potential for confusion is high. We note that in the early stages of handling a crisis, the uncertainties involved may be deep, i.e., difficult or impossible to quantify in the time available. In such circumstance, we suggest the idea of presenting multiple scenarios.     

Systemic risk statistics with scenario analysis

In this paper, we introduce two new classes of risk statistics, named convex and positively homogeneous systemic risk statistics, respectively. Structural decomposition results and representation results for them are provided. These new risk statistics can be considered as a kind of systemic risk extension of risk statistics introduced by Kou, Peng, and Heyde, and also empirical versions of system risk measures introduced by Cehn, Iyengar, and Mollemi and Kromer, Overbeck, and Zich. Finally, some examples are also given.     

The Multiscale Importance of Road Segments in a Network Disruption Scenario: A Risk‐Based Approach

This article addresses the problem of the multiscale importance of road networks, with the aim of helping to establish a more resilient network in the event of a road disruption scenario. A new model for identifying the most important roads is described and applied on a local and regional scale. The work presented here represents a step forward, since it focuses on the interaction between identifying the most important roads in a network that connect people and health services, the specificity of the natural hazards that threaten the normal functioning of the network, and an assessment of the consequences of three real‐world interruptions from a multiscale perspective. The case studies concern three different past events: road interruptions due to a flood, a forest fire, and a mass movement. On the basis of the results obtained, it is possible to establish the roads for which risk management should be a priority. The multiscale perspective shows that in a road interruption the regional system may have the capacity to reorganize itself, although the interruption may have consequences for local dynamics. Coordination between local and regional scales is therefore important. The model proposed here allows for the scaling of emergency response facilities and human and physical resources. It represents an innovative approach to defining priorities, not only in the prevention phase but also in terms of the response to natural disasters, such as awareness of the consequences of road disruption for the rescue services sent out to local communities.