A simple test of muscle coactivation estimation using electromyography

In numerous motor tasks, muscles around a joint act coactively to generate opposite torques. A variety of indexes based on electromyography signals have been presented in the literature to quantify muscle coactivation. However, it is not known how to estimate it reliably using such indexes. The goal of this study was to test the reliability of the estimation of muscle coactivation using electromyography. Isometric coactivation was obtained at various muscle activation levels. For this task, any coactivation measurement/index should present the maximal score (100% of coactivation). Two coactivation indexes were applied. In the first, the antagonistic muscle activity (the lower electromyographic signal between two muscles that generate opposite joint torques) is divided by the mean between the agonistic and antagonistic muscle activations. In the second, the ratio between antagonistic and agonistic muscle activation is calculated. Moreover, we computed these indexes considering different electromyographic amplitude normalization procedures. It was found that the first algorithm, with all signals normalized by their respective maximal voluntary coactivation, generates the index closest to the true value (100%), reaching 92 ± 6%. In contrast, the coactivation index value was 82 ± 12% when the second algorithm was applied and the electromyographic signal was not normalized (P < 0.04). The new finding of the present study is that muscle coactivation is more reliably estimated if the EMG signals are normalized by their respective maximal voluntary contraction obtained during maximal coactivation prior to dividing the antagonistic muscle activity by the mean between the agonistic and antagonistic muscle activations.

Comparison of Model-Based Flow Rate Estimation Methods in Frequency-Converter-Driven Pumps and Fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To deliver the energy saving potential, there is a need for easily implementable methods to monitor the system output. This is because information is needed to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable speed drives have proven to be able to give information on the system output without additional metering; however, the current model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.

Stability studies and shelf life estimation of a soy-based dessert

This work is aimed at evaluating the physicochemical, physical, chromatic, microbiological, and sensorial stability of a non-dairy dessert elaborated with soy, guava juice, and oligofructose for 60 days at refrigerated storage as well as to estimate its shelf life time. The titrable acidity, pH, instrumental color, water activity, ascorbic acid, and physical stability were measured. Panelists (n = 50) from the campus community used a hedonic scale to assess the acceptance, purchase intent, creaminess, flavor, taste, acidity, color, and overall appearance of the dessert during 60 days. The data showed that the parameters differed significantly (p < 0.05) from the initial time, and they could be fitted in mathematical equations with coefficient of determination above 71%, aiming to consider them suitable for prediction purposes. Creaminess and acceptance did not differ statistically in the 60-day period; taste, flavor, and acidity kept a suitable hedonic score during storage. Notwithstanding, the sample showed good physical stability against gravity and presented more than 15% of the Brazilian Daily Recommended Value of copper, iron, and ascorbic acid. The product shelf life estimation found was 79 days considering the overall acceptance, acceptance index and purchase intent.

Psychophysical estimation of acid intensity and determination of sweet-acid interaction in a fish paste containing glycerol

In a fish paste made with cooked Brazilian flathead (Percophis brasiliensis), glycerol (17%), sodium chloride (1.5%) and potassium sorbate (0.1%) the following acid percentages: 0.2; 0.4; 0.6; 0.8, 1 and 1.5% w/w were incorporated to determine the relationship between added acetic acid and the sensorially perceived intensity, and the effects of the combination of sweet-acid tastes. Tests for paired comparison, ranking and structured verbal scales for sweet and acid attributes and psychophysical test were carried out. There was a perceptible difference among samples for differences of 0.4 units of acid concentration. Samples indicated as sweeter by 89.47% of the judges were those containing a lesser acid concentration. A reduction in glycerol sweetness when increasing acid levels was observed. Acetic acid reduced the sweetness of glycerol and inversely glycerol reduced the acidity of acetic acid. The data obtained with the magnitude estimation test agree with Steven's law.

Study of the volatile compounds from plum (Prunus domestica L. cv. Horvin) and estimation of their contribution to the fruit aroma

Simultaneous Distillation-Extraction (SDE) and headspace-solid phase microextraction (HS-SPME) combined with GC-FID and GC-MS were used to analyze volatile compounds from plum (Prunus domestica L. cv. Horvin) and to estimate the most odor-active compounds by application of the Odor Activity Values (OAV). The analyses led to the identification of 148 components, including 58 esters, 23 terpenoids, 14 aldehydes, 11 alcohols, 10 ketones, 9 alkanes, 7 acids, 4 lactones, 3 phenols, and other 9 compounds of different structures. According to the results of SDE-GC-MS, SPME-GC-MS and OAV, ethyl 2-methylbutanoate, hexyl acetate, (E)-2-nonenal, ethyl butanoate, (E)-2-decenal, ethyl hexanoate, nonanal, decanal, (E)-β-ionone, Γ-dodecalactone, (Z)-3-hexenyl acetate, pentyl acetate, linalool, Γ-decalactone, butyl acetate, limonene, propyl acetate, Δ-decalactone, diethyl sulfide, (E)-2-hexenyl acetate, ethyl heptanoate, (Z)-3-hexenol, (Z)-3-hexenyl hexanoate, eugenol, (E)-2-hexenal, ethyl pentanoate, hexyl 2-methylbutanoate, isopentyl hexanoate, 1-hexanol, Γ-nonalactone, myrcene, octyl acetate, phenylacetaldehyde, 1-butanol, isobutyl acetate, (E)-2-heptenal, octadecanal, and nerol are characteristic odor active compounds in fresh plums since they showed concentrations far above their odor thresholds.

Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network

In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulans from initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days), number of clusters (10, 30 and 50 clusters) and internal weight softening parameter (Sigma) (0.30, 0.45 and 0.60). These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A) and 18 (B) days of culture growth. The validations demonstrated that in long-term experiments (Validation A) the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B), Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth.

Rigid body dynamics and Kalman filtering

X-ray computed log tomography has always been applied for qualitative reconstructions. In most cases, a series of consecutive slices of the timber are scanned to estimate the 3D image reconstruction of the entire log. However, the unexpected movement of the timber under study influences the quality of image reconstruction since the position and orientation of some scanned slices can be incorrectly estimated. In addition, the reconstruction time remains a significant challenge for practical applications. The present study investigates the possibility to employ modern physics engines for the problem of estimating the position of a moving rigid body and its scanned slices which are subject to X-ray computed tomography. The current work includes implementations of the extended Kalman filter and an algebraic reconstruction method for fan-bean computer tomography. In addition, modern techniques such as NVidia PhysX and CUDA are used in current study. As the result, it is numerically shown that it is possible to apply the extended Kalman filter together with a real-time physics engine, known as PhysX, in order to determine the position of a moving object. It is shown that the position of the rigid body can be determined based only on reconstructions of its slices. However, the simulation of the body movement sometimes is subject to an error during Kalman filter employment as PhysX is not always able to continue simulating the movement properly because of incorrect state estimation.

Bayesian analysis of SEIR epidemic models

This thesis concerns the analysis of epidemic models. We adopt the Bayesian paradigm and develop suitable Markov Chain Monte Carlo (MCMC) algorithms. This is done by considering an Ebola outbreak in the Democratic Republic of Congo, former Zaïre, 1995 as a case of SEIR epidemic models. We model the Ebola epidemic deterministically using ODEs and stochastically through SDEs to take into account a possible bias in each compartment. Since the model has unknown parameters, we use different methods to estimate them such as least squares, maximum likelihood and MCMC. The motivation behind choosing MCMC over other existing methods in this thesis is that it has the ability to tackle complicated nonlinear problems with large number of parameters. First, in a deterministic Ebola model, we compute the likelihood function by sum of square of residuals method and estimate parameters using the LSQ and MCMC methods. We sample parameters and then use them to calculate the basic reproduction number and to study the disease-free equilibrium. From the sampled chain from the posterior, we test the convergence diagnostic and confirm the viability of the model. The results show that the Ebola model fits the observed onset data with high precision, and all the unknown model parameters are well identified. Second, we convert the ODE model into a SDE Ebola model. We compute the likelihood function using extended Kalman filter (EKF) and estimate parameters again. The motivation of using the SDE formulation here is to consider the impact of modelling errors. Moreover, the EKF approach allows us to formulate a filtered likelihood for the parameters of such a stochastic model. We use the MCMC procedure to attain the posterior distributions of the parameters of the SDE Ebola model drift and diffusion parts. In this thesis, we analyse two cases: (1) the model error covariance matrix of the dynamic noise is close to zero , i.e. only small stochasticity added into the model. The results are then similar to the ones got from deterministic Ebola model, even if methods of computing the likelihood function are different (2) the model error covariance matrix is different from zero, i.e. a considerable stochasticity is introduced into the Ebola model. This accounts for the situation where we would know that the model is not exact. As a results, we obtain parameter posteriors with larger variances. Consequently, the model predictions then show larger uncertainties, in accordance with the assumption of an incomplete model.

The industrial equilibrium exchange rate in Brazil: an estimation

This paper presents a methodology for calculating the industrial equilibrium exchange rate, which is defined as the one enabling exporters of state-of-the-art manufactured goods to be competitive abroad. The first section highlights the causes and problems of overvalued exchange rates, particularly the Dutch disease issue, which is neutralized when the exchange rate strikes the industrial equilibrium level. This level is defined by the ratio between the unit labor cost in the country under consideration and in competing countries. Finally, the evolution of this exchange rate in the Brazilian economy is estimated.

Overvaluation trend of the Brazilian currency in the 2000s: empirical estimation

The aim of this paper is to discuss the trend of overvaluation of the Brazilian currency in the 2000s, presenting an econometric model to estimate the real exchange rate (RER) and which should be a reference level of the RER to guide long-term economic policy. In the econometric model, we consider long-term structural and short-term components, both of which may be responsible for explaining overvaluation trend of the Brazilian currency. Our econometric exercise confirms that the Brazilian currency had been persistently overvalued throughout almost all of the period under analysis, and we suggest that the long-term reference level of the real exchange rate was reached in 2004. In July 2014, the average nominal exchange rate should have been around 2.90 Brazilian reais per dollar (against an observed nominal rate of 2.22 Brazilian reais per dollar) to achieve the 2004 real reference level (average of the year). That is, according to our estimates, in July 2014 the Brazilian real was overvalued at 30.6 per cent in real terms relative to the reference level. Based on these findings we conclude the paper suggesting a mix of policy instruments that should have been used in order to reverse the overvaluation trend of the Brazilian real exchange rate, including a target for reaching a real exchange rate in the medium and the long-run which would favor resource allocation toward more technological intensive sectors.

Parameter estimation for Chaotic or Stochastic Dynamics

Since its discovery, chaos has been a very interesting and challenging topic of research. Many great minds spent their entire lives trying to give some rules to it. Nowadays, thanks to the research of last century and the advent of computers, it is possible to predict chaotic phenomena of nature for a certain limited amount of time. The aim of this study is to present a recently discovered method for the parameter estimation of the chaotic dynamical system models via the correlation integral likelihood, and give some hints for a more optimized use of it, together with a possible application to the industry. The main part of our study concerned two chaotic attractors whose general behaviour is diff erent, in order to capture eventual di fferences in the results. In the various simulations that we performed, the initial conditions have been changed in a quite exhaustive way. The results obtained show that, under certain conditions, this method works very well in all the case. In particular, it came out that the most important aspect is to be very careful while creating the training set and the empirical likelihood, since a lack of information in this part of the procedure leads to low quality results.

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