Component ordering strategies in assembly systems with uncertain capacity and random yield

Sourcing components in a complex global supplier network may lead to a high degree of supply uncertainty. Events, such as unexpected production defects or insufficient supplier capacity, can cause unexpected shortages of required components and halt the assembly of final products. Accordingly, the assembly enterprises must effectively manage various supply uncertainties in their component ordering decisions to avoid such component shortfalls. These issues have guided this research to investigate the optimal ordering strategies of an assembler facing the following two types of supply uncertainty: the uncertain production capacity of a standard component (component 1) and the random production yield of a core component (component 2). The assembler makes the component ordering decisions before these supply uncertainties are realized. We characterize the optimal ordering decision and find that the assembler should order components 1 and 2 according to a fixed ratio, which only depends on the random yield of component 2 and the production cost of component 1, but not on the uncertain capacity of component 1. A case study is presented to further explore the intertwined effects of these two uncertainties in an assembly system. Finally, the model is extended to consider a secondary option of buying additional component 1 s after observing some or all of the supply uncertainties, and this secondary option endows the firm with different capabilities in counteracting the supply uncertainties.     

Embedded solitons in the $$(2+1)$$(2+1)-dimensional sine-Gordon equation

Nonlinear Dynamics - An effective and simple method to solve nonlinear evolution partial differential equations is the self-similarity transformation, in which one utilizes solutions of the known...     

Numerical simulation of continuous separation of microparticles in two-stage acousto-microfluidic systems

Numerical modelling of acousto-microfluidic particle manipulation systems cannot only be used to explain the complex phenomena observed in experiments, but can also be applied to optimise their performances. In this work, we present numerical simulations of continuous-flow-based two-stage acoustic microparticle separations with a reduced-fluid model, which is consisted of three main parts: (1) an acoustic focusing zone; (2) a transition zone; and (3) an acoustic separation zone. The acoustophoresis of microparticles of various sizes in the fluid channel was modelled based on Newton's second law, where the acoustic radiation forces and the flow-induced drag forces, the main driving terms for particle motion, were solved from the Gorkov equation and the Navier-Stokes equations, respectively. It was found that an acoustic focusing process configured with appropriate force amplitudes can focus all particles to the same flow vector before entering the separation zone and thus can improve the separation efficiency, and that a sheath flow injected from the transition zone can push the sample flow onto the side boundaries, which can broaden the effective separation range for more robust separations. Based on the mechanism analyses, we here numerically demonstrated acoustofluidic separation of 5 different particle fractions simultaneously in a continuous microfluidic channel ending with 9 equally spaced outlets. We also predicted here that, with carefully designed acoustic and flow fields, it is capable to acoustically separate two different particle fractions with a diameter difference of 4% (difference in acoustic mobility of only ~1.08).     

Facet-dependent antibacterial activity of Au nanocrystals

Engineered nanomaterials have attracted significantly attention as one of the most promising antimicrobial agents for against multidrug resistant infections. The toxicological responses of nanomaterials are closely related to their physicochemical properties, and establishment of a structure-activity relationship for nanomaterials at the nano-bio interface is of great significance for deep understanding antibacterial toxicity mechanisms of nanomaterials and designing safer antibacterial nanomaterials. In this study, the antibacterial behaviors of well-defined crystallographic facets of a series of Au nanocrystals, including {100}-facet cubes, {110}-facet rhombic dodecahedra, {111}-facet octahedra, {221}-facet trisoctahedra and {720}-facet concave cubes, was investigated, using the model bacteria Staphylococcus aureus. We find that Au nanocrystals display substantial facet-dependent antibacterial activities. The low-index facets of cubes, octahedra, and rhombic dodecahedra show considerable antibacterial activity, whereas the high-index facets of trisoctahedra and concave cubes remained inert under biological conditions. This result is in stark contrast to the previous paradigm that the high-index facets were considered to have higher bioactivity as compared with low-index facets. The antibacterial mechanism studies have shown that the facet-dependent antibacterial behaviors of Au nanocrystals are mainly caused by differential bacterial membrane damage as well as inhibition of cellular enzymatic activity and energy metabolism. The faceted Au nanocrystals are unique in that they do not induce generation of reactive oxygen species, as validated for most antibiotics and antimicrobial nanostructures. Our findings may provide a deeper understanding of facet-dependent toxicological responses and suggest the complexities of the nanomaterial-cell interactions, shedding some light on the development of high performance Au nanomaterials-based antibacterial therapeutics.     

快速均值回归随机波动率模型参数估计及应用

基于快速均值回归随机波动率模型, 研究双限期权的定价问题, 同时推导了考虑均值回归随机波动率的双限期权的定价公式。 根据金融市场中SPDR S&P 500 ETF期权的隐含波动率数据和标的资产的历史收益数据, 对快速均值回归随机波动率模型中的两个重要参数进行估计。 利用估计得到的参数以及定价公式, 对双限期权价格做了数值模拟。 数值模拟结果发现, 考虑了随机波动率之后双限期权的价格在标的资产价格偏高的时候会小于基于常数波动率模型的期权价格。     

Point and interval forecasting for carbon price based on an improved analysis-forecast system

Effective analysis and forecasting of carbon prices, which is an essential endeavor for the carbon trading market, is still considered a difficult task because of the nonlinearity and nonstationarity inherent in carbon prices. Previous studies have failed at the analysis and interval prediction of carbon prices and are limited to point forecasts. Therefore, an improved carbon price analysis and forecasting system that consists of an analysis module and a forecasting module is established in this study; more importantly, the forecasting module includes point forecasting and interval forecasting as well. Aimed at investigating the characteristics of the carbon price series, a chaotic analysis based on the maximum Lyapunov exponent is performed, the determination of appropriate distribution functions based on our newly proposed hybrid optimization algorithm is conducted, and different distribution functions are effectively designed in the analysis module. Furthermore, in the point forecasting model, the phase space reconstruction technique is applied to reconstruct the sequences decomposed by variational mode decomposition due to the chaotic characteristics of the carbon price series, and the reconstructed sequences are considered as the optimal input–output variables of the forecasting model. Then, an adaptive neuro-fuzzy inference system model is trained by the newly proposed hybrid optimization algorithm, which is developed for the first time in the domain of carbon price point forecasting. Moreover, based on the results of point forecasting and the distribution function of the carbon price series determined by the analysis module, the interval forecasting results can be obtained and implemented to provide more reliable information for decision making. Empirical results based on the carbon price data of the European Union Emissions Trading System and Shenzhen of China demonstrate that the proposed system achieves better results than other benchmark models in point forecasting as well as interval forecasting.     

Effects of multi-frequency ultrasound on freezing rates and quality attributes of potatoes

The effects of multi-frequency ultrasound assisted freezing on the freezing rate, microstructure, quality properties (drip loss, firmness, total calcium content, l-ascorbic acid content and total phenol content) of potatoes were studied. The results indicated that the freezing effects of multi-frequency ultrasound was better than those of single-frequency ultrasound. Multi-frequency ultrasound could significantly increase the freezing rate and preserve the quality of frozen samples better. With increase in the number of ultrasonic frequencies, the freezing effect was more obvious. In addition, scan electron microscopy (SEM) images showed that the ice crystals formed by the multi-frequency ultrasonic treatment were fine and uniformly distributed, which caused less damage to the frozen potato samples. From the analysis of the quality attributes, the nutritional values of the samples after multi-frequency ultrasonic treatment was higher, but attention should be paid to the negative influence of the hydroxyl radical generated by the multi-frequency ultrasound.     

Three-level all-fiber laser at 915 nm based on polarization-maintaining Nd^3+-doped silica fiber

Nd3+-doped fiber lasers at around 900 nm based on the 4F3/2→4I9/2 transition have obtained much research attention since they can be used as the laser sources for generating pure blue fiber lasers through the frequency doubling.Here,an all-fiber laser at 915 nm was realized by polarization-maintaining Nd3+-doped silica fiber.A net gain per unit length of up to 1.0 dB/cm at 915 nm was obtained from a 4.5 cm fiber,which to our best knowledge is the highest gain coefficient reported in this kind of silica fiber.The optical-to-optical conversion efficiency varies with the active fiber length and the reflectivity of the output fiber Bragg grating(FBG),presenting an optimal value of 5.3%at 5.1 cm fiber length and 70%reflectivity of the low reflection FBG.Additionally,the linear distributed Bragg reflector short cavity was constructed to explore its potential in realizing single-frequency 915 nm fiber laser.The measurement result of longitudinal-mode properties shows it is still multi-longitudinal mode laser operation with 40 mm laser cavity.These results indicate that the Nd3+-doped silica fiber could be used to realize all-fiber laser at 915 nm,which presents potential to be the seed source of high-power fiber laser.     

Unlocking the Drug Potential of the Bryostatin Family: Recent Advances in Product Synthesis and Biomedical Applications

Bryostatins are a class of naturally occurring macrocyclic lactones with a unique fast developing portfolio of clinical applications, including treatment of AIDS, Alzheimer's disease, and cancer. This comprehensive account summarizes the recent progress (2014–present) in the development of bryostatins, including their total synthesis and biomedical applications. An emphasis is placed on the discussion of bryostatin 1 , the most-studied analogue to date. This review highlights the synthetic and biological challenges of bryostatins and provides an outlook on their future development.     

就单摆问题引入大学物理教学新模式

单摆教学的过程中引入MATLAB数值计算的教学新模式,可以有效地改善大学物理教学的枯燥方式,有助于提高学生对大学物理课中抽象的、复杂的物理现象和规律的理解,也有助于促进对所学数学知识的实际应用.这种新教学模式是深化高等工程教育改革、加快新工科建设、促进创新型工科人才培养的有效手段.