Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

Estimating Relative Risk Aversion, Risk-Neutral and Real-World Densities using Brazilian Real Currency Options

Building Risk-Neutral Densities (RND) from options data can provide market-implied expectations about the future behavior of a financial variable. And market expectations on financial variables may influence macroeconomic policy decisions. It can be useful also for corporate and financial institutions decision making. This paper uses the Liu et all (2007) approach to estimate the option-implied Risk-neutral densities from the Brazilian Real/US Dollar exchange rate distribution. We then compare the RND with actual exchange rates, on a monthly basis, in order to estimate the relative risk-aversion of investors and also obtain a Real-world density for the exchange rate. We are the first to calculate relative risk-aversion and the option-implied Real World Density for an emerging market currency. Our empirical application uses a sample of Brazilian Real/US Dollar options traded at BM&F-Bovespa from 1999 to 2011. The RND is estimated using a Mixture of Two Log-Normals distribution and then the real-world density is obtained by means of the Liu et al. (2007) parametric risktransformations. The relative risk aversion is calculated for the full sample. Our estimated value of the relative risk aversion parameter is around 2.7, which is in line with other articles that have estimated this parameter for the Brazilian Economy, such as Araújo (2005) and Issler and Piqueira (2000). Our out-of-sample evaluation results showed that the RND has some ability to forecast the Brazilian Real exchange rate. Abe et all (2007) found also mixed results in the out-of-sample analysis of the RND forecast ability for exchange rate options. However, when we incorporate the risk aversion into RND in order to obtain a Real-world density, the out-of-sample performance improves substantially, with satisfactory results in both Kolmogorov and Berkowitz tests. Therefore, we would suggest not using the “pure” RND, but rather taking into account risk aversion in order to forecast the Brazilian Real exchange rate.

Non-durable consumption and real-estate prices in Brazil: panel-data analysis at the state level

Housing is an important component of wealth for a typical household in many countries. The objective of this paper is to investigate the effect of real-estate price variation on welfare, trying to close a gap between the welfare literature in Brazil and that in the U.S., the U.K., and other developed countries. Our first motivation relates to the fact that real estate is probably more important here than elsewhere as a proportion of wealth, which potentially makes the impact of a price change bigger here. Our second motivation relates to the fact that real-estate prices boomed in Brazil in the last five years. Prime real estate in Rio de Janeiro and São Paulo have tripled in value in that period, and a smaller but generalized increase has been observed throughout the country. Third, we have also seen a recent consumption boom in Brazil in the last five years. Indeed, the recent rise of some of the poor to middle-income status is well documented not only for Brazil but for other emerging countries as well. Regarding consumption and real-estate prices in Brazil, one cannot imply causality from correlation, but one can do causal inference with an appropriate structural model and proper inference, or with a proper inference in a reduced-form setup. Our last motivation is related to the complete absence of studies of this kind in Brazil, which makes ours a pioneering study. We assemble a panel-data set for the determinants of non-durable consumption growth by Brazilian states, merging the techniques and ideas in Campbell and Cocco (2007) and in Case, Quigley and Shiller (2005). With appropriate controls, and panel-data methods, we investigate whether house-price variation has a positive effect on non-durable consumption. The results show a non-negligible significant impact of the change in the price of real estate on welfare consumption), although smaller then what Campbell and Cocco have found. Our findings support the view that the channel through which house prices affect consumption is a financial one.

Identification of sexually dimorphic gene expression in brain tissue of the fish Leporinus macrocephalus through mRNA differential display and real time PCR analyses

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

Anti-poliovirus activity of Baccharis dracunculifolia and propolis by cell viability determination and real-time PCR

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Polymerase chain reaction and real-time PCR for diagnosing of Leishmania infantum chagasi in dogs

A importância do cão como reservatório de L. infantum chagasi no meio urbano tem estimulado a realização de inúmeros trabalhos de avaliação de técnicas de diagnóstico, uma vez que este procedimento, quando realizado corretamente, torna-se um importante passo na prevenção da doença em humanos. Dentre os métodos de diagnóstico, as técnicas moleculares têm adquirido destaque. Objetivou-se neste trabalho verificar o desempenho da Reação em Cadeia da Polimerase (PCR) e da PCR em tempo real (qPCR) para diagnóstico da Leishmaniose Visceral Canina (LVC) utilizando diferentes amostras biológicas. Para tanto foram utilizados 35 cães provenientes de uma área endêmica para LVC, onde foram utilizados para o diagnóstico molecular, aspirado de medula óssea, fragmentos de linfonodo e baço. Neste estudo a qPCR foi capaz de detectar um maior número de animais positivos quando comparada com a PCR. Já entre as diferentes amostras biológicas utilizadas não foi observada diferença significativa na detecção de DNA de L. infantumchagasi por meio da PCR e qPCR. Mesmo assim, considerando a facilidade de obtenção, o linfonodo pode ser considerada como a melhor amostra para diagnóstico molecular da infecção por L. infantum chagasi.

Periodontal status in smokers and never-smokers: Clinical findings and real-time polymerase chain reaction quantification of putative periodontal pathogens

Background: Smoking is a well-known risk factor for destructive periodontal disease, but its relationship with periodontal status and subgingival microbiota remains unclear. Inherent limitations of microbiological methods previously used may partly explain these mixed results, and real-time polymerase chain reaction (PCR) has been presented as a valid alternative. The aim of the present study was to investigate the clinical condition and microbiological profile of patients with chronic periodontitis as related to the habit of smoking.Methods: Fifty patients (33 to 59 years old), 25 smokers and 25 never-smokers, constituted the sample. The visible plaque index (VPI), gingival bleeding index (GBI), bleeding on probing (BOP), periodontal probing depth (PD), clinical attachment loss (CAL), and gingival crevicular fluid (GCF) volume were recorded. Real-time PCR quantified Porphyromonas gingivalis, Micromonas micros, Dialister pneumosintes, Actinobacillus actinomycetemcomitans and total bacteria in subgingival samples.Results: Smokers and never-smokers showed similar values for VPI, GBI, and BOP. Smokers had deeper PD in buccal/lingual sites and higher CAL independently of the tooth surface. The GCF volume was smaller in smokers, independent of the PD. Similar amounts of total bacteria and P. gingivalis were observed for both groups. Significantly higher numbers of D. pneumosintes and M. micros were present in smokers and associated with moderate and deep pockets. When heavy smokers were considered, higher counts of total bacteria, M. micros, and D. pneumosintes were observed.Conclusions: Smoking seems to have a detrimental impact on the periodontal status and microbiological profile of patients with periodontitis. Compared to never-smokers, smokers had deeper pockets, greater periodontal destruction, and higher counts of some putative periodontal pathogens.

Genetic Algorithms (Binary and Real Codes) for the Optimisation of a Fermentation Process for Butanol Production

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

The monetary and real effects of the financial opening up of national economies to the exterior: the case of Chile 1975-1978

Includes bibliography

False dilemmas and real options in current Latin American debate

Includes bibliography

Monetary and real repercussions of financial opening-up to the exterior: the case of Chile: 1975-1978

Includes bibliography

Onboard and real-time artificial satellite orbit determination using GPS

An algorithm for real-time and onboard orbit determination applying the Extended Kalman Filter (EKF) method is developed. Aiming at a very simple and still fairly accurate orbit determination, an analysis is performed to ascertain an adequacy of modeling complexity versus accuracy. The minimum set of to-be-estimated states to reach the level of accuracy of tens of meters is found to have at least the position, velocity, and user clock offset components. The dynamical model is assessed through several tests, covering force model, numerical integration scheme and step size, and simplified variational equations. The measurement model includes only relevant effects to the order of meters. The EKF method is chosen to be the simplest real-time estimation algorithm with adequate tuning of its parameters. In the developed procedure, the obtained position and velocity errors along a day vary from 15 to 20 m and from 0.014 to 0.018 m/s, respectively, with standard deviation from 6 to 10 m and from 0.006 to 0.008 m/s, respectively, with the SA either on or off. The results, as well as analysis of the final adopted models used, are presented in this work. © 2013 Ana Paula Marins Chiaradia et al.

Economic growth and real volatility: The case of Latin America and the Caribbean

Using a new database of quarterly data for 21 countries of Latin America and the Caribbean for the 1990-2012 period, this document shows that the duration of GDP contractions appears to be a rather robust indicator of real volatility, and is negatively correlated with long run growth in Latin America and the Caribbean during the period. These results are consistent with different theoretical hypotheses in the literature that relate the duration of GDP contractions with economic growth. They also show that the relationship between real volatility and economic growth in the region is robust to the inclusion of external variables that control for external uncertainty and volatility.

Discovery of a new antiviral protein isolated Lonomia obliqua analysed by bioinformatics and real-time approaches

This study presents a new recombinant protein that acts as a powerful antiviral (rAVLO—recombinant Antiviral protein of Lonomia obliqua). It was able to reduce the replication by 106 fold for herpes virus and by 104 fold for rubella virus. RT-PCR of viral RNA rAVLO treated infected cells also showed similar rate of inhibition in replication. The analysis of this protein by bioinformatics suggests that this protein is globular, secreted with a signal peptide and has the ability to bind to MHC class I. It was found that there are several protein binding sites with various HLA and a prevalence of α-helices in the N-terminal region (overall classified as a α/β protein type). BLAST similarity sequence search for corresponding cDNA did not reveal a similar sequence in Genbank, suggesting that it is from a novel protein family. In this study we have observed that this recombinant protein and hemolymph has a potent antiviral action. This protein was produced in a baculovirus/Sf-9 system. Therefore, these analyses suggest that this novel polypeptide is a candidate as a broad spectrum antiviral.