Liouville–Green (WKB) asymptotics for almost-diagonal linear second-order matrix difference equations

A Liouville–Green (or WKB) asymptotic approximation theory is developed for a class of almost-diagonal (‘asymptotically diagonal’) linear second-order matrix difference equations. Rigorous and explicitly computable bounds for the error terms are obtained, the asymptotics being made with respect to both, the index and some parameter affecting the equation. The case of the associated inhomogeneous equations is also considered in detail. Some examples and a number of applications are presented for the purpose of illustration.     

Efficient computation of operator‐type response sensitivities for uncertainty quantification and predictive modeling: illustrative application to a spent nuclear fuel dissolver model

This work honors the 75th birthday of Professor Ionel Michael Navon by presenting original results highlighting the computational efficiency of the adjoint sensitivity analysis methodology for function‐valued operator responses by means of an illustrative paradigm dissolver model. The dissolver model analyzed in this work has been selected because of its applicability to material separations and its potential role in diversion activities associated with proliferation and international safeguards. This dissolver model comprises eight active compartments in which the 16 time‐dependent nonlinear differential equations modeling the physical and chemical processes comprise 619 scalar and time‐dependent model parameters, related to the model's equation of state and inflow conditions. The most important response for the dissolver model is the time‐dependent nitric acid in the compartment furthest away from the inlet, where measurements are available at 307 time instances over the transient's duration of 10.5 h. The sensitivities to all model parameters of the acid concentrations at each of these instances in time are computed efficiently by applying the adjoint sensitivity analysis methodology for operator‐valued responses. The uncertainties in the model parameters are propagated using the above‐mentioned sensitivities to compute the uncertainties in the computed responses. A predictive modeling formalism is subsequently used to combine the computational results with the experimental information measured in the compartment furthest from the inlet and then predict optimal values and uncertainties throughout the dissolver. This predictive modeling methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution for the a priori known mean values and uncertainties characterizing the model parameters and the computed and experimentally measured model responses. This approximate a priori distribution is subsequently combined using Bayes' theorem with the “likelihood” provided by the multi‐physics computational models. Finally, the posterior distribution is evaluated using the saddle‐point method to obtain analytical expressions for the optimally predicted values for the parameters and responses of both multi‐physics models, along with corresponding reduced uncertainties. This work shows that even though the experimental data pertains solely to the compartment furthest from the inlet (where the data were measured), the predictive modeling procedure used herein actually improves the predictions and reduces the predicted uncertainties for the entire dissolver, including the compartment furthest from the measurements, because this predictive modeling methodology combines and transmits information simultaneously over the entire phase‐space, comprising all time steps and spatial locations. Copyright © 2016 John Wiley & Sons, Ltd.     

Synthesis and properties of sulfur‐contained poly(silylene arylacetylene)s

Poly(silylene arylacetylene) (PSA) is a kind of poly(arylacetylene) silicon‐containing resins with excellent heat resistance and good mechanical performances. In this article, the sulfur atom is introduced into the main chain of the PSA molecule to obtain a sulfur‐containing poly(silylene arylacetylene), named S‐PSA. By Williamson and Sonogashira reactions, bis(4‐ethynylphenyl)sulfide and bis(4‐ethynylphenyl)sulfone were synthesized. Thereafter, through Grignard reagent way, the poly(silylene ethynylene phenylene sulfide phenylene ethynylene) (PSESE) and poly(silylene ethynylene phenylene sulfone phenylene ethynylene) (PSESO₂E) were synthesized from bis(4‐ethynylphenyl)sulfide, bis(4‐ethynylphenyl)sulfone, and methylphenyl dichlorosilane. Poly(silylene ethynylene phenylene sulfoxide phenylene ethynylene) (PSESOE) was synthesized by the oxidation of PSESE. The structures and properties of these resins were characterized and the mechanical properties of the T300 reinforced composites were tested. The results show that the novel S‐PSA resins have excellent heat resistance and good mechanical properties, and could be used as resin matrices for high‐performance composites in high‐tech fields. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019, 57, 2324–2332     

Pathwise superhedging for time-dependent barrier options on càdlàg paths—Finite or infinite tradeable European,One-Touch,lookback or forward starting options

We establish pathwise duality using simple predictable trading strategies for the robust hedging problem associated with a barrier option whose payoff depends on the terminal level and the infimum of a càdlàg strictly positive stock price process, given tradeable European options at all strikes at a single maturity. The result allows for a significant dimension reduction in the computation of the superhedging cost, via an alternate lower-dimensional formulation of the primal problem as a convex optimization problem, which is qualitatively similar to the duality which was formally sketched using linear programming arguments in Duembgen and Rogers [10] for the case where we only consider continuous sample paths. The proof exploits a simplification of a classical result by Rogers (1993) which characterizes the attainable joint laws for the supremum and the drawdown of a uniformly integrable martingale (not necessarily continuous), combined with classical convex duality results from Rockefellar (1974) using paired spaces with compatible locally convex topologies and the Hahn–Banach theorem. We later adapt this result to include additional tradeable One-Touch options using the Kertz and Rösler (1990) condition. We also compute the superhedging cost when in the more realistic situation where there is only finite tradeable European options; for this case we obtain the full duality in the sense of quantile hedging as in Soner (2015), where the superhedge works with probability $1?\epsilon$ where $\epsilon$ can be arbitrarily small), and we obtain an upper bound for the true pathwise superhedging cost. In Section 5, we extend our analysis to include time-dependent barrier options using martingale coupling arguments, where we now have tradeable European options at both maturities at all strikes and tradeable forward starting options at all strikes. This set up is designed to approximate the more realistic situation where we have a finite number of tradeable Europeans at both maturities plus a finite number of tradeable forward starting options.¹     

[2]Pseudorotaxane-Based Supramolecular Optical Indicator for the Visual Detection of Cellular Cyanide Excretion

Cyanide is extremely hazardous to living organisms and the environment. Owing to its wide range of applications and high toxicity, the development of functional materials for cyanide detection and sensing is highly desirable. Host–guest complexation between bis(p-phenylene)-34-crown-10 H and N-methylacridinium salt G remarkably decreases the detection limit for cyanide anions compared with that of the guest itself. The [2]pseudorotaxane selectively recognizes the cyanide anion with high optical sensitivity as a result of the nucleophilic addition of the cyanide anion at the 9-position of G . The host–guest complexation is further incorporated into supramolecular materials for the visual detection of cyanide anions, especially the detection of cellular cyanide excretion with a detection limit of 0.6 μm . This supramolecular method provides an extremely distinct strategy for the visual detection of cyanide anions.     

Thermoresponsive polymersome from a double hydrophilic block copolymer

The article describes synthesis and thermally triggered self‐assembly of a Poly (ethylene oxide)‐block‐poly (N‐insopropylacrylamide) (PEO‐b‐PNIPAm) in aqueous medium. At rt, the polymer remains as unimer, however, at lower critical solution temperature (LCST) of PNIPAm (32 °C), it forms a rather large undefined aggregate which at slightly elevated temperature (～40 °C) converges to well defined polymersome structure (Critical aggregation concentration = 0.45 mg/mL) with hydrodynamic diameter of 40–50 nm. By lowering the temperature, initial swelling of the compact vesicle followed by reversible disassembly to unimer was noticed. The polymersome exhibits encapsulation ability to a hydrophilic dye Calcein which can be spontaneously released by lowering the temperature below cloud point. Likewise a hydrophobic dye namely 8‐Anilino‐1‐naphthalenesulfonic acid (ANS) can also be encapsulated and released by thermal trigger. Detail photoluminescence studies reveal ANS dye can be used as a generalized probe molecule for detecting LCST of a thermoresponsive polymer by “fluorescence on” above LCST even by cursory observation. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2015 , 53, 2444–2451     

On the Motion of Substance in a Channel of a Network: Extended Model and New Classes of Probability Distributions

We discuss the motion of substance in a channel containing nodes of a network. Each node of the channel can exchange substance with: (i) neighboring nodes of the channel, (ii) network nodes which do not belong to the channel, and (iii) environment of the network. The new point in this study is that we assume possibility for exchange of substance among flows of substance between nodes of the channel and: (i) nodes that belong to the network but do not belong to the channel and (ii) environment of the network. This leads to an extension of the model of motion of substance and the extended model contains previous models as particular cases. We use a discrete-time model of motion of substance and consider a stationary regime of motion of substance in a channel containing a finite number of nodes. As results of the study, we obtain a class of probability distributions connected to the amount of substance in nodes of the channel. We prove that the obtained class of distributions contains all truncated discrete probability distributions of discrete random variable ω which can take values 0,1,⋯,N. Theory for the case of a channel containing infinite number of nodes is presented in Appendix A. The continuous version of the discussed discrete probability distributions is described in Appendix B. The discussed extended model and obtained results can be used for the study of phenomena that can be modeled by flows in networks: motion of resources, traffic flows, motion of migrants, etc.     

中国进口食品安全风险评估的统计学方法

近年来,随着对外贸易的快速发展和人民生活水平的不断提高,我国已经成为食品进口大国。运用科学的方法优化检验资源配置,强化对进口食品安全的风险管理,是一个关系到人民福社的重大问题。国际上通行的做法是对不同种类的食品和检测项目的潜在风险进行评估,并根据评估结果制定有针对性的监督抽检计划,使得更多的检验资源可以投入到对高风险产品和项目的监管中去。我国在这方面的管理实践才刚刚起步,急需建立一套符合我国食品进口自身特点和管理需求的风险评价模型和相应的估计方法。本文借鉴了其它国家的相关做法,并结合我国进口食品的管理需求和历史检测数据的特点,制定了一套完整的风险评价和估计方法。     

地下水脆弱性风险预警和评估的区间三角模糊多属性决策模型

应用基于逼近理想解排序法的区间三角模糊多属性决策模型,对三江平原六大分区地下水脆弱性进行了风险预警和评估.评估结果与前人吻合,可为有关决策部门采取相应降低环境风险的措施提供参考.实例验证表明,模型具有更高的计算精度和更好的评价效果,为有关环境风险决策部门对地下水风险预警和评估提供了新的思路和方法.