Cycloparaphenylene and their radicals anchored to a metal−organic framework

Cycloparaphenylene (CPP) shows modulated photophysical and electronic properties due to its strained structure and radially oriented π-electron system. Incorporation of CPP into metal-organic frameworks (MOFs) could transfer its extensive properties in solution to porous solids. Moreover, with the unique arrangement of the macrocycles and their interactions with the framework, emerging characteristics are anticipated. As an example of “robust dynamics”, we synthesized the first MOF structure (FDM-1001) with CPP precisely anchored to the ordered framework by employing a [8]CPP-containing linear dicarboxylate linker. Metric relationship between the dynamic macrocycles and the robust backbone creates ideal π-π interactions between them, which leads to an essentially directional arrangement of [8]CPP in the three-dimensional space. Furthermore, the MOF with [8]CPP could be successfully oxidized to generate an infinite array of radicals that show enhanced air stability compared to its molecular analogue.     

The cut condition for robust network design

We consider the Robust Network Design problem, i.e. the problem of dimensioning the capacities on the edges of a graph to serve point-to-point traffic demands subject to uncertainty. The scope of the paper is to investigate when the cut condition is sufficient to guarantee the feasibility for such problem.     

Phase unwrapping by accumulation of residual maps

We present a path independent (global) algorithm for phase unwrapping based on the minimisation of a robust cost function. The algorithm incorporates an outlier rejection mechanism making it robust to large inconsistencies and discontinuities. The proposal consists on an iterative incremental scheme that unwraps a sub-estimation of the residual phase at each iteration. The sub-estimation degree is controlled by an algorithm׳s parameter. We present an efficiently computational multigrid implementation based on a nested strategy: the process is iterated by using multiple resolutions. The proposal׳s performance is demonstrated by experiments with synthetic and real data, and successfully compared with algorithms of the state of the art.     

Robust stabilization of a class of state-dependent jump linear systems

In this article, we consider a continuous-time state-dependent jump linear system (SDJLS), a kind of stochastic hybrid system, with the presence of uncertainties in system parameters. In SDJLS, we consider that the transition rates of the underlying random jump process depend on the state variable. In particular, we assume the transition rates to have different values across suitably defined sets to which the state of the system belongs, and address a problem of robust stability and stabilization analysis. We obtain sufficient conditions for robust stability and state-feedback stabilization in terms of linear matrix inequalities (LMIs). We validate the obtained sufficient robust stability and stabilization conditions with numerical examples.     

基于LPV的航空发动机鲁棒变增益控制

随着我国现代化进程的不断加快,航天航空技术标准越来越高,对于航空发动机运转工况的鲁棒性和适应性提出了更高的要求。传统的航空发动机变增益设计步骤繁琐,不能将发动机置于整个航空器的运转去考虑设计,使发动机变增益缺乏相应的稳定性和适应性,易出现系统问题。为此,提出一般基于LPV的航空发动机鲁棒变增益控制系统,依据航空发动机结构参数,考虑到航空器在空中负载特性,计算出新的约束极点 模糊变增益,在航空器发动机工作范围连续增益,避免了传统增益切换情况,在转速控制上确定误差等因素,将非线性控制设计分解为多个线性子问题,使航空器控制系统能够沿着LPV参数轨迹保持良好的运转,保持稳定性能。仿真实验证明,提出的基于LPV的航空发动机鲁棒变增益控制系统控制效果优于传统方法,在航空器发动机转速改变时,控制精度能够满足要求 ,改变航空器负载时,有效对目标进行变增益控制。提出的控制方法对航空发动机鲁棒变增益控制问题提供了新的解决办法,具有较大应用价值。     

光学移相干涉仪抗振系统的鲁棒控制系统仿真分析

将被动抗振和主动抗振相结合的混合控制技术应用于解决光学移相干涉仪抗振系统的不确定性问题,其中主动抗振采用鲁棒控制策略.该方法克服了由模型和干扰所引起的不确定性,使得控制系统能够有效地抑制抗振模型的不确定性和外部振动的干扰.仿真结果表明,该方法使光学移相干涉仪在振动的干扰下具有较好的鲁棒稳定性和控制准确度.     

Two-stage minimax regret robust uncapacitated lot-sizing problems with demand uncertainty

In this paper, we consider the two-stage minimax robust uncapacitated lot-sizing problem with interval uncertain demands. A mixed integer programming formulation is proposed. Even though the robust uncapacitated lot-sizing problem with discrete scenarios is an NP-hard problem, we show that it is polynomial solvable under the interval uncertain demand set.     

Direct synthesis of porous NiO nanowall arrays on conductive substrates for supercapacitor application

Porous NiO nanowall arrays (NWAs) grown on flexible Fe-Co-Ni alloy have been successfully synthesized by using nullaginite (Ni₂(OH)₂CO₃) as precursor and investigated as supercapacitor electrodes. In details, we adopted a simple hydrothermal method to realize Ni₂(OH)₂CO₃ NWAs and examined their robust mechanical adhesion to substrate via a long-time ultrasonication test. Porous NiO NWAs were then obtained by a post-calcination towards precursors at 500 °C in nitrogen atmosphere. Electrochemical properties of as-synthesized NiO NWAs were evaluated by cyclic voltammetry and galvanostatic charge/discharge; porous NiO NWAs electrode delivered a specific capacitance of 270 F/g (0.67 A/g); even at high current densities, the electrode could still deliver a high capacitance up to 236 F/g (13.35 A/g). Meanwhile, it exhibited excellent cycle lifetime with ∼93% specific capacitance kept after 4000 cycles. These results suggest that as-made porous NiO NWAs electrode is a promising candidate for future thin-film supercapacitors and other microelectronic systems.     

Robust and accurate inference for generalized linear models

In the framework of generalized linear models, the nonrobustness of classical estimators and tests for the parameters is a well known problem, and alternative methods have been proposed in the literature. These methods are robust and can cope with deviations from the assumed distribution. However, they are based on first order asymptotic theory, and their accuracy in moderate to small samples is still an open question. In this paper, we propose a test statistic which combines robustness and good accuracy for moderate to small sample sizes. We combine results from Cantoni and Ronchetti [E. Cantoni, E. Ronchetti, Robust inference for generalized linear models, Journal of the American Statistical Association 96 (2001) 1022–1030] and Robinson, Ronchetti and Young [J. Robinson, E. Ronchetti, G.A. Young, Saddlepoint approximations and tests based on multivariate M-estimators, The Annals of Statistics 31 (2003) 1154–1169] to obtain a robust test statistic for hypothesis testing and variable selection, which is asymptotically χ²-distributed as the three classical tests but with a relative error of order O(n⁻¹). This leads to reliable inference in the presence of small deviations from the assumed model distribution, and to accurate testing and variable selection, even in moderate to small samples.     

Relaxed robust second-order-cone programming

In this paper, we propose an approximate optimization model for the robust second-order-cone programming problem with a single-ellipsoid uncertainty set for which the computational complexity is not known yet. We prove that this approximate robust model can be equivalently reformulated as a finite convex optimization problem.