Optimal reactive power dispatch using stochastic chance-constrained programming

Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage stochastic optimization model is first formulated under the presumption that the load demand can be modeled as specified random parameters. A second stochastic chance-constrained model is presented considering uncertainty on the demand and the equivalent availability of shunt reactive power compensators. Simulations on six-bus and 30-bus test systems are used to illustrate the validity and essential features of the proposed models. This simulations shows that the proposed models can prevent to the power system operator about of the deficit of reactive power in the power system and suggest that shunt reactive sourses must be dispatched against the unavailability of any reactive source. © 2012 IEEE.

Cooperative RNA Polymerase Molecules Behavior on a Stochastic Sequence-Dependent Model for Transcription Elongation

The transcription process is crucial to life and the enzyme RNA polymerase (RNAP) is the major component of the transcription machinery. The development of single-molecule techniques, such as magnetic and optical tweezers, atomic-force microscopy and single-molecule fluorescence, increased our understanding of the transcription process and complements traditional biochemical studies. Based on these studies, theoretical models have been proposed to explain and predict the kinetics of the RNAP during the polymerization, highlighting the results achieved by models based on the thermodynamic stability of the transcription elongation complex. However, experiments showed that if more than one RNAP initiates from the same promoter, the transcription behavior slightly changes and new phenomenona are observed. We proposed and implemented a theoretical model that considers collisions between RNAPs and predicts their cooperative behavior during multi-round transcription generalizing the Bai et al. stochastic sequence-dependent model. In our approach, collisions between elongating enzymes modify their transcription rate values. We performed the simulations in Mathematica® and compared the results of the single and the multiple-molecule transcription with experimental results and other theoretical models. Our multi-round approach can recover several expected behaviors, showing that the transcription process for the studied sequences can be accelerated up to 48% when collisions are allowed: the dwell times on pause sites are reduced as well as the distance that the RNAPs backtracked from backtracking sites. © 2013 Costa et al.

Ergodic crossover in partially self-avoiding stochastic walks

Consider a one-dimensional environment with N randomly distributed sites. An agent explores this random medium moving deterministically with a spatial memory μ. A crossover from local to global exploration occurs in one dimension at a well-defined memory value μ1=log2N. In its stochastic version, the dynamics is ruled by the memory and by temperature T, which affects the hopping displacement. This dynamics also shows a crossover in one dimension, obtained computationally, between exploration schemes, characterized yet by the trajectory size (Np) (aging effect). In this paper we provide an analytical approach considering the modified stochastic version where the parameter T plays the role of a maximum hopping distance. This modification allows us to obtain a general analytical expression for the crossover, as a function of the parameters μ, T, and Np. Differently from what has been proposed by previous studies, we find that the crossover occurs in any dimension d. These results have been validated by numerical experiments and may be of great value for fixing optimal parameters in search algorithms. © 2013 American Physical Society.

Label free redox capacitive biosensing

A surface confined redox group contributes to an interfacial charging (quantifiable by redox capacitance) that can be sensitively probed by impedance derived capacitance spectroscopy. In generating mixed molecular films comprising such redox groups, together with specific recognition elements (here antibodies), this charging signal is able to sensitively transduce the recognition and binding of specific analytes. This novel transduction method, exemplified here with C-reactive protein, an important biomarker of cardiac status and general trauma, is equally applicable to any suitably prepared interfacial combination of redox reporter and receptor. The assays are label free, ultrasensitive, highly specific and accompanied by a good linear range. © 2013 Elsevier B.V.

SPECTRUM OF STOCHASTIC ADDING MACHINES AND FIBERED JULIA SETS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparing label free electrochemical impedimetric and capacitive biosensing architectures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Markovian versus non-Markovian stochastic quantization of a complex-action model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Multi-Stage Stochastic Non-Linear Model for Reactive Power Planning Under Contingencies

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Improved Upper Limits on the Stochastic Gravitational-Wave Background from 2009-2010 LIGO and Virgo Data

Gravitational waves from a variety of sources are predicted to superpose to create a stochastic background. This background is expected to contain unique information from throughout the history of the Universe that is unavailable through standard electromagnetic observations, making its study of fundamental importance to understanding the evolution of the Universe. We carry out a search for the stochastic background with the latest data from the LIGO and Virgo detectors. Consistent with predictions from most stochastic gravitational-wave background models, the data display no evidence of a stochastic gravitational-wave signal. Assuming a gravitational-wave spectrum of Omega(GW)(f) = Omega(alpha)(f/f(ref))(alpha), we place 95% confidence level upper limits on the energy density of the background in each of four frequency bands spanning 41.5-1726 Hz. In the frequency band of 41.5-169.25 Hz for a spectral index of alpha = 0, we constrain the energy density of the stochastic background to be Omega(GW)(f) < 5.6 x 10(-6). For the 600-1000 Hz band, Omega(GW)(f) < 0.14(f/900 Hz)(3), a factor of 2.5 lower than the best previously reported upper limits. We find Omega(GW)(f) < 1.8 x 10(-4) using a spectral index of zero for 170-600 Hz and Omega(GW)(f) < 1.0(f/1300 Hz)(3) for 1000-1726 Hz, bands in which no previous direct limits have been placed. The limits in these four bands are the lowest direct measurements to date on the stochastic background. We discuss the implications of these results in light of the recent claim by the BICEP2 experiment of the possible evidence for inflationary gravitational waves.

Systemic risk in dynamical networks with stochastic failure criterion

Complex non-linear interactions between banks and assets we model by two time-dependent Erdos-Renyi network models where each node, representing a bank, can invest either to a single asset (model I) or multiple assets (model II). We use a dynamical network approach to evaluate the collective financial failure -systemic risk- quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided into sub-periods, where within each sub-period banks may contiguously fail due to links to either i) assets or ii) other banks, controlled by two parameters, probability of internal failure p and threshold T-h ("solvency" parameter). The systemic risk decreases with the average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can sustain (smaller T-h), the smaller the systemic risk -for some Th values in I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic ii) controlled by probability p(2) -a condition for the bank to be solvent (active) is stochasticthe- systemic risk decreases with decreasing p(2). We analyse the asset allocation for the U.S. banks. Copyright (C) EPLA, 2014

STOCHASTIC ADDING MACHINE AND 2-DIMENSIONAL JULIA SETS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Transport and dynamical properties for a bouncing ball model with regular and stochastic perturbations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Renewable nanocomposite layer-by-layer assembled catalytic interfaces for biosensing applications

A novel, easily renewable nanocomposite interface based on layer-by-layer (LbL) assembled cationic/anionic layers of carbon nanotubes customized with biopolymers is reported. A simple approach is proposed to fabricate a nanoscale structure composed of alternating layers of oxidized multiwalled carbon nanotubes upon which is immobilized either the cationic enzyme organophosphorus hydrolase (OPH; MWNT−OPH) or the anionic DNA (MWNT−DNA). The presence of carbon nanotubes with large surface area, high aspect ratio and excellent conductivity provides reliable immobilization of enzyme at the interface and promotes better electron transfer rates. The oxidized MWNTs were characterized by thermogravimetric analysis and Raman spectroscopy. Fourier transform infrared spectroscopy showed the surface functionalization of the MWNTs and successful immobilization of OPH on the MWNTs. Scanning electron microscopy images revealed that MWNTs were shortened during sonication and that LbL of the MWNT/biopolymer conjugates resulted in a continuous surface with a layered structure. The catalytic activity of the biopolymer layers was characterized using absorption spectroscopy and electrochemical analysis. Experimental results show that this approach yields an easily fabricated catalytic multilayer with well-defined structures and properties for biosensing applications whose interface can be reactivated via a simple procedure. In addition, this approach results in a biosensor with excellent sensitivity, a reliable calibration profile, and stable electrochemical response.