Fuzzy Views on Black-Litterman Portfolio Selection Model

In this paper, views of investor are described in fuzzy sets, and two fuzzy Black-Litterman models are constructed with fuzzy views and fuzzy random views respectively. In the models, expected returns and uncertainty matrix of views are redefined and the views are formulated by fuzzy approaches suitably. Then the models are tested with data from Chinese financial markets. Empirical results show that the fuzzy random views model performs the best, and both the fuzzy models are better than the traditional ones, demonstrating that the fuzzy approaches can contain more information in the views and measure the uncertainty more correctly.     

乡村振兴绩效评价:意义、维度与路径

2018年,中共中央、国务院印发《中国乡村振兴战略规划(2018-2022年)》,全面部署和布局乡村振兴战略.文章基于政府绩效评价的理念和方法,构建乡村振兴绩效评价指标体系,明确评价维度,为实现乡村振兴、城乡融合发展提供价值导向、度量体系和动力工具.该评价维度包涵资源投入、过程监管、目标实现情况和社会满意度四个方面.文章指出,相关单位以绩效评价推进乡村振兴时应注重顶层设计,强化部门协同,构建评价体系,引入第三方评价主体,凸显农民获得感.     

Modeling eBay price using stochastic differential equations

Online auctions have become increasingly popular in recent years. There is a growing body of research on this topic, whereas modeling online auction price curves constitutes one of the most interesting problems. Most research treats price curves as deterministic functions, which ignores the random effects of external and internal factors. To account for the randomness, a more realistic model using stochastic differential equations is proposed in this paper. The online auction price is modeled by a stochastic differential equation in which the deterministic part is equivalent to the second‐order differential equation model proposed in Wang et al. (Journal of the American Statistical Association, 2008, 103, 1100–1118). The model also includes a component representing the measurement errors. Explicit expressions for the likelihood function are also obtained, from which statistical inference can be conducted. Forecast accuracy of the proposed model is compared with the ODE (ordinary differential equation) approach. Simulation results show that the proposed model performs better.     

Aristotle Said “Happiness is a State of Activity” — Predicting Mood Through Body Sensing with Smartwatches

We measure and predict states of Activation and Happiness using a body sensing application connected to smartwatches. Through the sensors of commercially available smartwatches we collect individual mood states and correlate them with body sensing data such as acceleration, heart rate, light level data, and location, through the GPS sensor built into the smartphone connected to the smartwatch. We polled users on the smartwatch for seven weeks four times per day asking for their mood state. We found that both Happiness and Activation are negatively correlated with heart beats and with the levels of light. People tend to be happier when they are moving more intensely and are feeling less activated during weekends. We also found that people with a lower Conscientiousness and Neuroticism and higher Agreeableness tend to be happy more frequently. In addition, more Activation can be predicted by lower Openness to experience and higher Agreeableness and Conscientiousness. Lastly, we find that tracking people’s geographical coordinates might play an important role in predicting Happiness and Activation. The methodology we propose is a first step towards building an automated mood tracking system, to be used for better teamwork and in combination with social network analysis studies.     

Early SIV and HIV infection promotes the LILRB2/MHC-I inhibitory axis in cDCs

Classical dendritic cells (cDCs) play a pivotal role in the early events that tip the immune response toward persistence or viral control. In vitro studies indicate that HIV infection induces the dysregulation of cDCs through binding of the LILRB2 inhibitory receptor to its MHC-I ligands and the strength of this interaction was proposed to drive disease progression. However, the dynamics of the LILRB2/MHC-I inhibitory axis in cDCs during early immune responses against HIV are yet unknown. Here, we show that early HIV-1 infection induces a strong and simultaneous increase of LILRB2 and MHC-I expression on the surface of blood cDCs. We further characterized the early dynamics of LILRB2 and MHC-I expression by showing that SIVmac251 infection of macaques promotes coordinated up-regulation of LILRB2 and MHC-I on cDCs and monocytes/macrophages, from blood and lymph nodes. Orientation towards the LILRB2/MHC-I inhibitory axis starts from the first days of infection and is transiently induced in the entire cDC population in acute phase. Analysis of the factors involved indicates that HIV-1 replication, TLR7/8 triggering, and treatment by IL-10 or type I IFNs increase LILRB2 expression. Finally, enhancement of the LILRB2/MHC-I inhibitory axis is specific to HIV-1 and SIVmac251 infections, as expression of LILRB2 on cDCs decreased in naturally controlled chikungunya virus infection of macaques. Altogether, our data reveal a unique up-regulation of LILRB2 and its MHC-I ligands on cDCs in the early phase of SIV/HIV infection, which may account for immune dysregulation at a critical stage of the anti-viral response.     

基于小波分析对地面电场信号的去噪及闪电信息提取

基于小波分析方法,通过对7种小波函数在误差控制和阈值方法选取上的对比,参考信噪比及均方误差等计算结果,选取了较为合理的Rigrsure阈值分析方法和sym5小波函数作为地面大气电场信号的去噪处理方法.该方法不仅能够较好地对电场信号波形平滑处理,降低电场波形中噪声信号的叠加度,还可保留闪电引起的电场的快速变化.在此基础上,利用差分计算方法实现了对闪电信号的自动识别,引入了总闪电频数误差及分时段闪电频数与人工分析结果的相关系数等2个参考量来选取差分计算方法中电场差分阈值,通过该方法可以实现闪电频数和极性等有关信息的提取.     

Notch Effect and Frequency Compensation of Dual-Sensor OBC Data in Shallow Water

Reverberation is significant in shallow water and produces obvious notches in OBC spec-tra. It also degrades the quality of sections and increases the difficulty of processing and interpretation. This ...     

河南农业科技创新联盟建设与发展的思考

农业科技创新联盟是联盟发展的新产物,是农业科技创新进行协作的组织形式。本文主要通过对农业科技创新联盟及其重要作用和农业科技创新联盟功能定位、管理体制与存在问题进行了分析论述,提出了河南农业科技创新联盟建设发展的对策建议     

EVOKE: A Value-Driven Concept Selection Method for Early System Design

The development of new technologically advanced products requires the contribution from a range of skills and disciplines, which are often difficult to find within a single company or organization. Requirements establishment practices in Systems Engineering (SE), while ensuring coordination of activities and tasks across the supply network, fall short when it comes to facilitate knowledge sharing and negotiation during early system design. Empirical observations show that when system-level requirements are not available or not mature enough, engineers dealing with the development of long lead-time sub-systems tend to target local optima, rather than opening up the design space. This phenomenon causes design teams to generate solutions that do not embody the best possible configuration for the overall system. The aim of this paper is to show how methodologies for value-driven design may address this issue, facilitating early stage design iterations and the resolution of early stage design trade-offs. The paper describes how such methodologies may help gathering and dispatching relevant knowledge about the ‘design intent’ of a system to the cross-functional engineering teams, so to facilitate a more concurrent process for requirement elicitation in SE. The paper also describes EVOKE (Early Value Oriented design exploration with KnowledgE maturity), a concept selection method that allows benchmarking design options at sub-system level on the base of value-related information communicated by the system integrators. The use of EVOKE is exemplified in an industrial case study related to the design of an aero-engine component. EVOKE’s ability to raise awareness on the value contribution of early stage design concepts in the SE process has been further verified with industrial practitioners in ad-hoc design episodes.