Nonparametric nonlinear model predictive control

Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impeded by linear models due to the lack of a similarly accepted nonlinear modeling or databased technique. Aimed at solving this problem, the paper addresses three issues: (i) extending second-order Volterra nonlinear MPC (NMPC) to higher-order for improved prediction and control; (ii) formulating NMPC directly with plant data without needing for parametric modeling, which has hindered the progress of NMPC; and (iii) incorporating an error estimator directly in the formulation and hence eliminating the need for a nonlinear state observer. Following analysis of NMPC objectives and existing solutions, nonparametric NMPC is derived in discrete-time using multidimensional convolution between plant data and Volterra kernel measurements. This approach is validated against the benchmark van de Vusse nonlinear process control problem and is applied to an industrial polymerization process by using Volterra kernels of up to the third order. Results show that the nonparametric approach is very efficient and effective and considerably outperforms existing methods, while retaining the original data-based spirit and characteristics of linear MPC

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

Active Galactic Nuclei at the Crossroads of Astrophysics

Over the last five decades, AGN studies have produced a number of spectacular examples of synergies and multifaceted approaches in astrophysics. The field of AGN research now spans the entire spectral range and covers more than twelve orders of magnitude in the spatial and temporal domains. The next generation of astrophysical facilities will open up new possibilities for AGN studies, especially in the areas of high-resolution and high-fidelity imaging and spectroscopy of nuclear regions in the X-ray, optical, and radio bands. These studies will address in detail a number of critical issues in AGN research such as processes in the immediate vicinity of supermassive black holes, physical conditions of broad-line and narrow-line regions, formation and evolution of accretion disks and relativistic outflows, and the connection between nuclear activity and galaxy evolution.Comment: 16 pages, 5 figures; review contribution; "Exploring the Cosmic Frontier: Astrophysical Instruments for the 21st Century", ESO Astrophysical Symposia Serie

The PHENIX Experiment at RHIC

The physics emphases of the PHENIX collaboration and the design and current status of the PHENIX detector are discussed. The plan of the collaboration for making the most effective use of the available luminosity in the first years of RHIC operation is also presented.Comment: 5 pages, 1 figure. Further details of the PHENIX physics program available at http://www.rhic.bnl.gov/phenix

[10]-gingerol induces apoptosis and inhibits metastatic dissemination of triple negative breast cancer in vivo

There is increasing interest in the use of non-toxic natural products for the treatment of various pathologies, including cancer. In particular, biologically active constituents of the ginger oleoresin (Zingiber officinale Roscoe) have been shown to mediate anti-tumour activity and to contribute to the anti-inflammatory, antioxidant, antimicrobial, and antiemetic properties of ginger. Here we report on the inhibitory properties of [10]-gingerol against metastatic triple negative breast cancer (TNBC) in vitro and in vivo. We show that [10]-gingerol concentration-dependently induces apoptotic death in mouse and human TNBC cell lines in vitro. In addition, [10]-gingerol is well tolerated in vivo, induces a marked increase in caspase-3 activation and inhibits orthotopic tumour growth in a syngeneic mouse model of spontaneous breast cancer metastasis. Importantly, using both spontaneous and experimental metastasis assays, we show for the first time that [10]-gingerol significantly inhibits metastasis to multiple organs including lung, bone and brain. Remarkably, inhibition of brain metastasis was observed even when treatment was initiated after surgical removal of the primary tumour. Taken together, these results indicate that [10]-gingerol may be a safe and useful complementary therapy for the treatment of metastatic breast cancer and warrant further investigation of its efficacy, either alone or in combination with standard systemic therapies, in pre-clinical models of metastatic breast cancer and in patients

Planck early results. VI. The High Frequency Instrument data processing

We describe the processing of the 336 billion raw data samples from the High Frequency Instrument (HFI) which we performed to produce six temperature maps from the first 295 days of Planck-HFI survey data. These maps provide an accurate rendition of the sky emission at 100, 143, 217, 353, 545 and 857GHz with an angular resolution ranging from 9.9 to 4.4 . The white noise level is around 1.5 μK degree or less in the 3 main CMB channels (100–217 GHz). The photometric accuracy is better than 2% at frequencies between 100 and 353 GHz and around 7% at the two highest frequencies. The maps created by the HFI Data Processing Centre reach our goals in terms of sensitivity, resolution, and photometric accuracy. They are already sufficiently accurate and well-characterised to allow scientific analyses which are presented in an accompanying series of early papers. At this stage, HFI data appears to be of high quality and we expect that with further refinements of the data processing we should be able to achieve, or exceed, the science goals of the Planck project