Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

Effects of the Anti-Tumorigenic Agent AT101 on Human Glioblastoma Cells in the Microenvironmental Glioma Stem Cell Niche

Glioblastoma (GBM) is a barely treatable disease due to its profound chemoresistance. A distinct inter- and intratumoral heterogeneity reflected by specialized microenvironmental niches and different tumor cell subpopulations allows GBMs to evade therapy regimens. Thus, there is an urgent need to develop alternative treatment strategies. A promising candidate for the treatment of GBMs is AT101, the R(-) enantiomer of gossypol. The present study evaluates the effects of AT101, alone or in combination with temozolomide (TMZ), in a microenvironmental glioma stem cell niche model of two GBM cell lines (U251MG and U87MG). AT101 was found to induce strong cytotoxic effects on U251MG and U87MG stem-like cells in comparison to the respective native cells. Moreover, a higher sensitivity against treatment with AT101 was observed upon incubation of native cells with a stem-like cell-conditioned medium. This higher sensitivity was reflected by a specific inhibitory influence on the p-p42/44 signaling pathway. Further, the expression of CXCR7 and the interleukin-6 receptor was significantly regulated upon these stimulatory conditions. Since tumor stem-like cells are known to mediate the development of tumor recurrences and were observed to strongly respond to the AT101 treatment, this might represent a promising approach to prevent the development of GBM recurrences.     

高岭土性质对催化裂化催化剂性能的影响

采用X射线荧光分析仪、X射线衍射仪、N2物理吸附仪、场发射扫描电子显微镜等仪器表征了苏州、广西和美国佐治亚州3个产地的高岭土，并以此3种高岭土为原料制备了模型催化裂化（FCC）催化剂，在ACE评价装置上对比了模型催化剂的反应性能。结果表明:苏州及广西高岭土主要组分为高岭石，佐治亚高岭土主要组分为地开石及珍珠陶土；苏州高岭土呈片状，还含有少量棒状颗粒；广西高岭土呈多层片状，晶粒粒径较大；佐治亚高岭土呈薄片状，晶粒粒径较小；3种高岭土制备的模型催化剂反应活性、Na2O及RE2O3质量分数相近；广西高岭土制备的模型催化剂具有最大的孔体积和磨损指数，但比表面积最小，具有较强的重油转化能力，其目标产物（液化气+汽油）和副产物（干气+焦炭）收率都高于苏州、佐治亚高岭土制备的催化剂的。     

Output feedback controller for polytopic systems exploiting the direct searching of the design space

This paper deals with the problem of designing a robust static output feedback controller for polytopic systems. The current research that tackled this problem is mainly based on LMI method, which is conservative by nature. In this paper, a novel approach is proposed, which considers the design space of the controller parameters and iteratively partitions the space to small simplexes. Then, by assessing the stability in each simplex, the solution space for design parameters is directly determined. It has been theoretically proved that, if there exists a feasible solution in the design space, the algorithm can find it. To validate the result of the proposed approach, comparative simulation examples are given to illustrate the performance of the design methodology as compared to those of previous approaches.     

SDN中基于KMOBPSO的高可靠性控制器部署算法

针对SDN中控制器系统的单节点故障问题,兼顾系统成本和系统时延,应用N+1冗余备份模型来提高SDN控制器部署的可靠性,并将其抽象为多目标优化问题.同时,提出了一种融合K-means聚类算法和遗传算子的多目标二进制粒子群算法——KMOBPSO算法,以求解SDN控制器高可靠性部署问题的解.仿真结果表明,所提算法具有求解精度高、分布均匀、沿Pareto前沿面覆盖广的特点,能够显著提高SDN中控制器部署的可靠性.     

Optimized PI+ load–frequency controller using BWNN approach for an interconnected reheat power system with RFB and hydrogen electrolyser units

This paper investigates a renewable energy resource’s application to the Load–Frequency Control of interconnected power system. The Proportional-Integral (PI) controllers are replaced with Proportional-Integral Plus (PI+) controllers in a two area interconnected thermal power system without/with the fast acting energy storage devices and are designed based on Control Performance Standards (CPS) using conventional/Beta Wavelet Neural Network (BWNN) approaches. The energy storing devices Hydrogen generative Aqua Electroliser (HAE) with Fuel cell and Redox Flow Battery (RFB) are incorporated to the two area interconnected thermal power system to efficiently damp out the electromechanical oscillations in the power system because of their inherent efficient storage capacity in addition to the kinetic energy of the generator rotor, which can share the sudden changes in power requirements. The system was simulated and the frequency deviations in area 1 and area 2 and tie-line power deviations for 5% step- load disturbance in area 1 are obtained. The comparison of frequency deviations and tie-line power deviations of the two area interconnected thermal power system with HAE and RFB designed with BWNN controller reveals that the PI+ controller designed using BWNN approach is found to be superior than that of output response obtained using PI+ controller. Moreover the BWNN based PI+ controller exhibits a better transient and steady state response for the interconnected power system with Hydrogen generative Aqua Electroliser (AE) unit than that of the system with Redox Flow Battery (RFB) unit.     

Direct Injection of CRISPR/Cas9-Related mRNA into Cytoplasm of Parthenogenetically Activated Porcine Oocytes Causes Frequent Mosaicism for Indel Mutations

Some reports demonstrated successful genome editing in pigs by one-step zygote microinjection of mRNA of CRISPR/Cas9-related components. Given the relatively long gestation periods and the high cost of housing, the establishment of a single blastocyst-based assay for rapid optimization of the above system is required. As a proof-of-concept, we attempted to disrupt a gene (GGTA1) encoding the α-1,3-galactosyltransferase that synthesizes the α-Gal epitope using parthenogenetically activated porcine oocytes. The lack of α-Gal epitope expression can be monitored by staining with fluorescently labeled isolectin BS-I-B₄ (IB4), which binds specifically to the α-Gal epitope. When oocytes were injected with guide RNA specific to GGTA1 together with enhanced green fluorescent protein (EGFP) and human Cas9 mRNAs, 65% (24/37) of the developing blastocysts exhibited green fluorescence, although almost all (96%, 23/24) showed a mosaic fluorescent pattern. Staining with IB4 revealed that the green fluorescent area often had a reduced binding activity to IB4. Of the 16 samples tested, six (five fluorescent and one non-fluorescent blastocysts) had indel mutations, suggesting a correlation between EGFP expression and mutation induction. Furthermore, it is suggested that zygote microinjection of mRNAs might lead to the production of piglets with cells harboring various mutation types.     

黑龙江省节水增粮行动(2012—2015年)实施方案

文章通过对黑龙江省高效节水现状,存在问题的分析,结合黑龙江省高效节水发展的支撑能力,阐述黑龙江省节水增粮目标、任务及总体布局,为黑龙江省2012—2015年节水增粮实施提供依据。     

A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.