Development of an improved divergence‐free‐condition compensated coupled framework to solve flow problems with time‐varying geometries

In this article a coupled version of the improved divergence‐free‐condition compensated method will be proposed to simulate time‐varying geometries by direct forcing immersed boundary method. The proposed method can be seen as a quasi‐multi‐moment framework due to the fact that the momentum equations are discretized by both cell‐centered and cell‐face velocity. For simulating time‐varying geometries, a semi‐implicit iterative method is proposed for calculating the direct forcing terms. Treatments for suppressing spurious force oscillations, calculating drag/lift forces, and evaluating velocity and pressure for freshly cells will also be addressed. In order to show the applicability and accuracy, analytical as well as benchmark problems will be investigated by the present framework and compared with other numerical and experimental results.     

Analytical and numerical studies for Seiches in a closed basin with bottom friction

A standing wave oscillation in a closed basin, known as a seiche, could cause destruction when its period matches the period of another wave generated by external forces such as wind, quakes, or abrupt changes in atmospheric pressure. It is due to the resonance phenomena that allow waves to have higher amplitude and greater energy, resulting in damages around the area. One condition that might restrict the resonance from occurring is when the bottom friction is present. Therefore, a modified mathematical model based on the shallow water equations will be used in this paper to investigate resonance phenomena in closed basins and to analyze the effects of bottom friction on the phenomena. The study will be conducted for several closed basin shapes. The model will be solved analytically and numerically in order to determine the natural resonant period of the basin, which is the period that can generate a resonance. The computational scheme proposed to solve the model is developed using the staggered grid finite volume method. The numerical scheme will be validated by comparing its results with the analytical solutions. As a result of the comparison, a rather excellent compatibility between the two results is achieved. Furthermore, the impacts that the friction coefficient has on the resonance phenomena are evaluated. It is observed that in the prevention of resonances, the bottom friction provides the best performance in the rectangular type while functioning the least efficient in the triangular basin. In addition, non-linearity effect as one of other factors that provide wave restriction is also considered and studied to compare its effect with the bottom friction effect on preventing resonance.     

有效因子综合偏好强度与CVaR整合优化模型

本文从股票多维特征因子中选择有效因子,融合形成最大化有效因子综合偏好强度(IPS)的附加理性,构建并验证IPS-均值-CVaR投资组合优化模型。基于沪深300股2006~2015年数据分析显示:(1)有效因子IPS投资组合优越于单因子投资组合;(2)IPS方法相较于因子打分法,具有更优的多维数据整合功效;(3)IPS-均值-CVaR投资组合优化模型相对于均值-CVaR模型具有更优越的资产选择能力,也拓展了投资组合模型的多维数据处理能力和适用性。     

企业自主研发与合作创新的风险测度及组合优化

企业在整合内部创新要素进行自主研发的同时,也会寻求外部创新资源进行合作创新,当前同时从事多个R&D项目已成为常见的企业经营活动,如何在不确定条件下分析多个R&D项目投资的策略选择及风险优化,对于企业的长期发展具有重要意义。根据企业是否采取合作创新策略,可将其R&D项目分为自主研发与合作创新两类,以项目的研发成功率和投资收益率代表技术风险和市场风险,分别测度自主研发与合作创新项目的风险特性,并在此基础上构建企业R&D项目投资组合优化模型,以在自主研发与合作创新项目之间进行权衡取舍。结果表明,企业对于自主研发与合作创新项目投资组合的最优投资权重,主要取决于这两类组合的期望收益率、收益率方差、期望成功率以及两组合之间的协方差。企业可基于关键参数制定出最优的R&D项目投资组合选择策略,合理分配资金以达到风险最小化的投资目标。     

A machine learning efficient frontier

We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the mean–variance efficient frontier out-of-sample. Our results, therefore, shed important light on the appeal of machine learning into portfolio selection under estimation risk.     

Wound Healing Attributes of Polyelectrolyte Multilayers Prepared with Multi‐l‐arginyl‐poly‐l‐aspartate Pairing with Hyaluronic Acid and γ‐Polyglutamic Acid

Biodegradable multi‐l ‐arginyl‐poly‐l ‐aspartate (MAPA), more commonly cyanophycin, prepared with recombinant Escherichia coli contains a polyaspartate backbone with lysine and arginine as side chains. Two assemblies of polyelectrolyte multilayers (PEMs) are fabricated at three different concentration ratios of insoluble MAPA (iMAPA) with hyaluronic acid (iMAPA/HA) and with γ‐polyglutamic acid (iMAPA/γ‐PGA), respectively, utilizing a layer‐by‐layer approach. Both films with iMAPA and its counterpart, HA or γ‐PGA, as the terminal layer are prepared to assess the effect on film roughness, cell growth, and cell migration. iMAPA incorporation is higher for a higher concentration of the anionic polymer due to better charge interaction. The iMAPA/HA films when compared to iMAPA/γ‐PGA multilayers show least roughness. The growth rates of L929 fibroblast cells on the PEMs are similar to those on glass substrate, with no supplementary effect of the terminal layer. However, the migration rates of L929 cells increase for all PEMs. γ‐PGA incorporated films impart 50% enhancement to the cell migration after 12 h of culture as compared to the untreated glass, and the smooth films containing HA display a maximum 82% improvement. The results present the use of iMAPA to construct a new layer‐by‐layer system of polyelectrolyte biopolymers with a potential application in wound dressing.     

Universal power law behavior of the AC conductivity versus frequency of agglomerate morphologies in conductive carbon nanotube‐reinforced epoxy networks

The Jonscher universal power law for ac conductivity versus frequency (f = ω/2π) in the dispersion region was tested for a multiwall carbon nanotube/epoxy nanocomposite. The effect of changes in agglomerate morphology on the fitting parameters A and n in the equation σ_{ac =} Aωⁿ was investigated. Changing nanotube agglomerate morphology was tracked by optical microscopy through curing. Evolving morphology was compared alongside ac conductivity obtained via a broadband dielectric spectrometer to elucidate possible physical meaning of the universal power law in the context of this system. The ?logA/n was unaffected by changes in agglomerate morphology affected during cure, yet connected with each other in their dependence on temperature. For this system, the relationship between the fitting parameters in the universal dynamic response equation remains empirical at this stage with regard to biphasic “texture” or morphology within such a network. Electrical conductivity σ versus frequency ω for a composite consisting of agglomerated multiwalled carbon nanotubes dispersed throughout a cured epoxy matrix was discovered to follow the empirical universal dynamic response equation of Jonscher. The frequency behavior of the exponent n is discussed in terms of underlying morphology throughout which charge carriers migrate. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 1918–1923     

Complex dynamics in equilibrium asset pricing models with boundedly rational,heterogeneous agents

We study a simple model based upon the Lucas framework where heterogeneous agents behave rationally in a fully intertemporal setting but do not know other investors' personal preferences, wealth or investment portfolios. As a consequence, agents initially do not know the equilibrium asset pricing function and must make guesses, which they update via adaptive learning with constant gain. We demonstrate that even in this simple environment the economy can, depending on parameters, exhibit either stable convergence to equilibrium, or chaotic dynamical behavior of asset prices and trading volume without converging to the rational expectations equilibrium of the Lucas model. This contradicts the assertion that the Lucas model is stable in the face of modest deviations from the strong assumptions required to compute the equilibrium. © 2013 Wiley Periodicals, Inc. Complexity 19: 38–55, 2014     

Analysis of survivorship life insurance portfolios with stochastic rates of return

A general portfolio of survivorship life insurance contracts is studied in a stochastic rate of return environment with a dependent mortality model. Two methods are used to derive the first two moments of the prospective loss random variable. The first one is based on the individual loss random variables while the second one studies annual stochastic cash flows. The distribution function of the present value of future losses at a given valuation time is derived. For illustrative purposes, an AR(1) process is used to model the stochastic rates of return, and the future lifetimes of a couple are assumed to follow a copula model. The effects of the mortality dependence, the portfolio size and the policy type, as well as the impact of investment strategies on the riskiness of portfolios of survivorship life insurance policies are analyzed by means of moments and probability distributions.