Wf-4r pdf

When the same product was sold in packages of different sizes, it was counted only once. This resulted in a total of labels that were sorted into the different food categories as defined in the HBS.

In this study, only the categories with food products that contained the artificial food colours mentioned above were considered in the calculation, thus yielding more precise values. The survey of products was carried out to select the food categories to be used in the intake estimate. In these surveys, a representative sample of households in the country is visited, and residents over 10 years of age report their food consumption at home and out on two non-consecutive days.

The HBS classifies food into categories around , which have undergone minor modifications from one survey to another. For each of these categories, it was checked whether there was any product containing any of the dyes Azorubine, Erythrosine, Indigotine, and Ponceau 4R in its formulation.

In addition, all food products were considered to contain the highest concentration permitted by legislation. There are different approaches to estimating the probable daily dietary exposure to food additives. The TMDI is calculated by multiplying the average daily intake of food by the maximum amount of the additive permitted by legal regulation.

The mean TMDI per capita was obtained for each of the food colours by adding up their quantities in all food products. In this study we also present the TMDI considering the prevalence of food consumption PFC , recalculating the TMDI by redistributing the total amount consumed only among interviewees who reported consuming the food products under investigation eaters only.

This work also presents the values obtained using this approach in the results section. It is worth noting that the HBS only studies the food consumption of Brazilians older than 10 years; therefore, there are no data for children younger than that age.

Still, the HBS considers that adolescents are people aged between 10 and 18 years old, adults between 19 and 54, and seniors over 55 years old.

Thus, the ADI calculations in this study are based on the average weights presented in the oldest research. Thus, the values for Erythrosine are much lower because the ADI of this food colour is about 45 times smaller than that of the other food colours. The labels studied were sorted into approximately food categories present in the HBS.

Two of these categories comprised products whose formulation contained Azorubine; one had Erythrosine, three had Indigotine, and three had Ponceau 4R. Table 2 lists these categories, the number of products within the category available at the supermarket chain website, and the number and percentage of products containing the food colours in the ingredient list.

Considering the total number of products assessed in this study , there is a very low incidence of the presence of these food colours: six products 0. It is, therefore, the food colour with the highest percentage within a category. Ahmed et al. Dietary intake of artificial food color addtives containing food products by school-going children.

Saudi Journal of Biological Sciences, 28 1 , The value of mean food consumption was used to obtain results for the mean intake of Azorubine, Erythrosine, Indigotine, and Ponceau 4R, i. In addition to the consumption per capita, the HBS also provides data on the percentage of the population that claimed to have consumed a certain food product.

With this percentage, it is possible to recalculate the TMDI by redistributing the total amount consumed only among interviewees who reported consuming the food products under investigation eaters only. Thus, it is more suitable to consider this percentage, i. The range of ADI values for each food colour Table 1 is presented to facilitate comparison.

It should be noted that TMDI totals represent the sum of the values for food products within the categories. This study assumes that all food colours were used at their maximum concentrations permitted by legislation.

For the other food colours, TMDI corresponds to 1. For this reason, mean TMDI is the same or slightly higher for women for all food colours evaluated. Ansari et al. Relationships between food consumption and living arrangements among university students in four European countries: a cross-sectional study.

Nutrition Journal, 11, For each food colour, the values closest to the ADI represent 7. It should be noted that, in this study, a low incidence of Erythrosine was observed on the labels analysed, so the values used for the calculations come from a single source a strawberry-flavoured ice cream topping sauce.

In most cases, the values are higher in the South Region and lower in the North Region. When comparing with the ADI, the maximum value is observed for Erythrosine, reaching There were decreases in the average consumption of all dyes and in all regions over the period of about 10 years between the two HBS used in this study. In general, considering all regions, the greatest reductions in the period studied are observed for the intake of Indigotine and Erythrosine.

This reduction is due to a reduction in consumption of all foods in the categories containing Indigotine yoghurts, chocolates, and other sweets. In a study conducted in the United States, Bastaki et al.

In a study conducted in Iran, Zahedi et al. Egyptian Journal of Veterinary Science, 51 1 , However, the average consumption decreased to 0. Feitosa et al. The intake of Indigotine by adolescents However, as previously mentioned, the intake of Erythrosine is based on a single product that had the colour in its ingredient list. However, given that the mean consumption and the prevalence of consumption are low in this category, individual levels are high, since the amount of food is redistributed only among people who stated they had consumed the product.

There was a decrease in the consumption of foods that contribute to the intake of dyes. Some changes in consumption were observed between the two HBS.

There was a decrease in the consumption of soft drinks which would imply healthier habits , but at the same time, a reduction in the consumption of the traditional Brazilian diet rice and beans and an increase in the consumption of preparations including sandwiches and ready-to-eat foods. However, it should be taken into account that there has been a change in the procedure for collecting food consumption data in the HBS, as mentioned above.

These differences in procedures may influence the results for ingestion. As it is shown in Fig. In such experiment, the robot was able to improve the learners' performances by providing verbal and graphical feedback to the students Figure 2.

Thus, we should take into account both shape and mobility of the human and versatility of the human senses to enable the robot to act as a human does. Therefore, in this paper, the improvement of the mechanical design and the interaction system with humans is presented. Firstly, the mechanical design of the arm mechanism to improve the flute position accuracy will be described.

Then, the introduction to the new transfer skill system architecture will be given, which is based on the addition of some basic cognitive functions. Finally, the implementation and evaluation of a melody recognition system based on the Hidden Markov Models HMM is detailed described. Figure 1. The WF-4 and a professional flutist player transferring basic skills to a beginner flutist player. The addition of the arm mechanism enabled to enhance the accuracy of the flute positioning maximum error position of 0.

In [12], the previous version of the flutist robot, the WF-4, has been. Page used as a teaching tool to improve the sound quality of beginner flutist players.

An experimental setup was done designed to compare the added value of using the flutist robot for teaching to beginner students against the conventional way of teaching. The results demonstrated that the performance of pupils were better when the robot was used. The anthropomorphic flutist robot WF-4R. However, the interaction between the flutist robot and the learner was in still in some way restricted. The robot's operator pre-programmed the sequence of the experiment so that learners could not decide by themselves which melody they wish to play.

Therefore, it becomes necessary to add further cognitive functionalities to the robot so that the robot can interact with humans at the same logical perceptual level. In Fig. Due to the complexity of the system, as a first approach, the implementation of a music recognition system using the auditory system is presented. The idea of implementing a melody recognition system is based on the idea of rendering a more natural interaction between the robot and the student. Figure 3. Proposed automated transfer skill system.

Even that we have demonstrated the improvement of learners using these steps, the score played by the robot to demonstrate the correct way of playing was preprogrammed. Therefore, we aim that the robot should be able of determining which score was played by the learner without pre-programming the score to be played by the robot and without requiring further information from the learner.

In order to verify the effectiveness of the recognition system, an experimental setup was designed with flutist beginners. Modeling human skills is a difficult task due to the stochastic nature of human performance as none can repeat a task exactly in the same way. Inside this stochastic process, human actions are considered as the measurable stochastic process and the knowledge or strategy behind it as the underlying stochastic process.

In the particular case of music, the Music Information Retrieval MIR has been presented as a tool to perform the named Query-By-Humming; where at least three different algorithms have been investigated [1]: note-interval using the Dynamic Programming search [7], melodic-contour using the Dynamic Time Warping search [4], and Hidden Markov Model Matching [5].

Even though the Dynamic Programming and Dynamic Time Warping algorithms demonstrated to be better for doing the musical recognition compared with the Hidden Markov Models [1], the first two algorithms present the following constraints [8]: do not generalize; both are player dependent oriented; need examples s for each melody from each subject; and become computationally expensive for large amount of music data. You need to adjust the image file to the size of the paper. If your application has margin settings, make sure they are set to zero before printing.

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