Event-based H∞ consensus control of multi-agent systems with relative output feedback: The finite-horizon case

In this technical note, the H∞ consensus control problem is investigated over a finite horizon for general discrete time-varying multi-agent systems subject to energy-bounded external disturbances. A decentralized estimation-based output feedback control protocol is put forward via the relative output measurements. A novel event-based mechanism is proposed for each intelligent agent to utilize the available information in order to decide when to broadcast messages and update control input. The aim of the problem addressed is to co-design the time-varying controller and estimator parameters such that the controlled multi-agent systems achieve consensus with a disturbance attenuation level γ over a finite horizon [0,T]. A constrained recursive Riccati difference equation approach is developed to derive the sufficient conditions under which the H∞ consensus performance is guaranteed in the framework of event-based scheme. Furthermore, the desired controller and estimator parameters can be iteratively computed by resorting to the Moore-Penrose pseudo inverse. Finally, the effectiveness of the developed event-based H∞ consensus control strategy is demonstrated in the numerical simulation

Event-based recursive distributed filtering over wireless sensor networks

In this technical note, the distributed filtering problem is investigated for a class of discrete time-varying systems with an event-based communication mechanism. Each intelligent sensor node transmits the data to its neighbors only when the local innovation violates a predetermined Send-on-Delta (SoD) data transmission condition. The aim of the proposed problem is to construct a distributed filter for each sensor node subject to sporadic communications over wireless networks. In terms of an event indicator variable, the triggering information is utilized so as to reduce the conservatism in the filter analysis. An upper bound for the filtering error covariance is obtained in form of Riccati-like difference equations by utilizing the inductive method. Subsequently, such an upper bound is minimized by appropriately designing the filter parameters iteratively, where a novel matrix simplification technique is developed to handle the challenges resulting from the sparseness of the sensor network topology and filter structure preserving issues. The effectiveness of the proposed strategy is illustrated by a numerical simulation.This work is supported by National Basic Research Program of China (973 Program) under Grant 2010CB731800, National Natural Science Foundation of China under Grants 61210012, 61290324, 61473163 and 61273156, and Jiangsu Provincial Key Laboratory of E-business at Nanjing University of Jiangsu and Economics of China under Grant JSEB201301

Minimum-variance recursive filtering over sensor networks with stochastic sensor gain degradation: Algorithms and performance analysis

This paper is concerned with the minimum variance filtering problem for a class of time-varying systems with both additive and multiplicative stochastic noises through a sensor network with a given topology. The measurements collected via the sensor network are subject to stochastic sensor gain degradation, and the gain degradation phenomenon for each individual sensor occurs in a random way governed by a random variable distributed over the interval [0, 1]. The purpose of the addressed problem is to design a distributed filter for each sensor such that the overall estimation error variance is minimized at each time step via a novel recursive algorithm. By solving a set of Riccati-like matrix equations, the parameters of the desired filters are calculated recursively. The performance of the designed filters is analyzed in terms of the boundedness and monotonicity. Specifically, sufficient conditions are obtained under which the estimation error is exponentially bounded in mean square. Moreover, the monotonicity property for the error variance with respect to the sensor gain degradation is thoroughly discussed. Numerical simulations are exploited to illustrate the effectiveness of the proposed filtering algorithm and the performance of the developed filter.This work was supported by the National Natural Science Foundation of China under Grants 61490701, 61210012, 61290324, 61473163, 61522309, and 61273156; in part by the Tsinghua University Initiative Scientific Research Program; and in part by the Jiangsu Provincial Key Laboratory of E-business at Nanjing University of Finance and Economics of China under Grant JSEB201301; and in part by the Research Fund for the Taishan Scholar Project of Shandong Province of China

Computational modelling of double focus in American English

This study investigated how double focus in English statements and questions can be computationally modelled. PENTAtrainer2 was used to learn syllable-sized multi-functional targets from a corpus of 1960 English utterances, with controlled variations in lexical stress, focus, modality, and sentence length. The results showed that the learned targets could generate F0 contours close to the original. In particular, the asymmetry in the interaction between focus and modality was effectively simulated

A Serratia marcescens PigP Homolog Controls Prodigiosin Biosynthesis, Swarming Motility and Hemolysis and Is Regulated by cAMP-CRP and HexS

Swarming motility and hemolysis are virulence-associated determinants for a wide array of pathogenic bacteria. The broad host-range opportunistic pathogen Serratia marcescens produces serratamolide, a small cyclic amino-lipid, that promotes swarming motility and hemolysis. Serratamolide is negatively regulated by the transcription factors HexS and CRP. Positive regulators of serratamolide production are unknown. Similar to serratamolide, the antibiotic pigment, prodigiosin, is regulated by temperature, growth phase, HexS, and CRP. Because of this co-regulation, we tested the hypothesis that a homolog of the PigP transcription factor of the atypical Serratia species ATCC 39006, which positively regulates prodigiosin biosynthesis, is also a positive regulator of serratamolide production in S. marcescens. Mutation of pigP in clinical, environmental, and laboratory strains of S. marcescens conferred pleiotropic phenotypes including the loss of swarming motility, hemolysis, and severely reduced prodigiosin and serratamolide synthesis. Transcriptional analysis and electrophoretic mobility shift assays place PigP in a regulatory pathway with upstream regulators CRP and HexS. The data from this study identifies a positive regulator of serratamolide production, describes novel roles for the PigP transcription factor, shows for the first time that PigP directly regulates the pigment biosynthetic operon, and identifies upstream regulators of pigP. This study suggests that PigP is important for the ability of S. marcescens to compete in the environment. © 2013 Shanks et al

Telomerase activity in gestational trophoblastic disease

Aims - To investigate the pattern of telomerase activity in hydatidiform mole as compared with normal placenta and choriocarcinoma, and to determine the prognostic significance of telomerase activity in hydatidiform mole. Methods - Telomerase activity in 35 cases of hydatidiform mole, 35 normal placentas, one choriocarcinoma sample, and two choriocarcinoma cell lines (JAR, JEG3) was determined using the sensitive polymerase chain reaction based telomeric repeat amplification protocol (TRAP) assay. Two cases of breast carcinoma and two cases of ovarian carcinoma were also included as positive controls in the telomerase assay. Results - Telomerase activity was detected in 11 of 30 early placentas (36.7%), one of five term placentas (20%), five of 27 hydatidiform moles which regressed spontaneously (18.5%), and six of eight hydatidiform moles which developed persistent trophoblastic disease (75%) (including three which developed metastases). Hydatidiform moles which subsequently developed persistent disease, especially those which metastasised, were more likely to express telomerase activity (p < 0.01). However, there was no significant difference in the frequency of telomerase activity between early placentas and hydatidiform mole. Strong telomerase activity was observed in choriocarcinoma tissue, choriocarcinoma cell lines, and ovarian and breast carcinomas. Conclusions - Telomerase activation occurs in hydatidiform mole with a similar incidence to early normal placentas. This supports the concept that hydatidiform mole is essentially an abnormal conceptus. There is an association between telomerase activation and the development of persistent trophoblastic disease. Further study is warrant to confirm the prognostic significance of telomerase activity in hydatidiform mole.published_or_final_versio

Ultrahigh power and energy density in partially ordered lithium-ion cathode materials

The rapid market growth of rechargeable batteries requires electrode materials that combine high power and energy and are made from earth-abundant elements. Here we show that combining a partial spinel-like cation order and substantial lithium excess enables both dense and fast energy storage. Cation overstoichiometry and the resulting partial order is used to eliminate the phase transitions typical of ordered spinels and enable a larger practical capacity, while lithium excess is synergistically used with fluorine substitution to create a high lithium mobility. With this strategy, we achieved specific energies greater than 1,100 Wh kg–1 and discharge rates up to 20 A g–1. Remarkably, the cathode materials thus obtained from inexpensive manganese present a rare case wherein an excellent rate capability coexists with a reversible oxygen redox activity. Our work shows the potential for designing cathode materials in the vast space between fully ordered and disordered compounds

Effects of ceftiofur sodium liposomes on free radical formation in mice

To examine the effects of ceftiofur sodium liposomes on the free radical formation in liver of mice, 24 mice were assigned randomly into three groups, i.e., 1) ceftiofur sodium; 2) ceftiofur sodium liposomes and 3) physiological saline. Treatments were applied via intraperitoneal injections for 7 days. At the end of the treatment period, animals were euthanized and liver collected for analysis of superoxide dismutase (SOD) activity and malondialdehyde (MDA) contents and the ability of liver tissue to suppress hydroxyl radical formation. Ceftiofur sodium liposomes-treated mice had higher activity of SOD than ceftiofur sodium- and saline-treated mice; however, MDA content and the ability of liver tissue to suppress hydroxyl radical formation did not reach statistical significance among groups. It was concluded that ceftiofur sodium liposomes can improve the SOD activity compared to ceftiofur alone in mice

Interactions in vivo between the Vif protein of HIV-1 and the precursor (Pr55GAG) of the virion nucleocapsid proteins

The abnormality of viral core structure seen in vif-defective HIV-1 grown in PBMCs has suggested a role for Vif in viral morphogenesis. Using an in vivo mammalian two-hybrid assay, the interaction between Vif and the precursor (Pr55GAG) of the virion nucleocapsid proteins has been analysed. This revealed the amino-terminal (aa 1–22) and central (aa 70–100) regions of Vif to be essential for its interaction with Pr55GAG, but deletion of the carboxy-terminal (aa 158–192) region of the protein had only a minor effect on its interaction. Initial deletion studies carried out on Pr55GAG showed that a 35-amino-acid region of the protein bridging the MA(p17)–CA(p24) junction was essential for its ability to interact with Vif. Site-directed mutagenesis of a conserved tryptophan (Trp21) near the amino terminus of Vif showed it to be important for the interaction with Pr55GAG. By contrast, mutagenesis of the highly conserved YLAL residues forming part of the BC-box motif, shown to be important in Vif promoting degradation of APOBEC3G/3F, had little or no effect on the Vif–Pr55GAG interaction

Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data.

PublishedEvaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov'tRecently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data.National Key Basic Research Program of China [2012CB316503]; National High-Tech Research and Development Program of China [2014AA021103]; National Natural Science Foundation of China [31271402]; Tsinghua University Initiative Scientific Research Program [2014z21045]; Hong Kong Research Grants Council Early Career Scheme [419612 to K.Y.]; National Science Foundation [1339282 to D.H.M.]; Computing Platform of the National Protein Facilities (Tsinghua University). Funding for open access charge: National Natural Science Foundation of China [31271402]