Abstract
The National School Feeding Program - NSFP is the public health policy that guarantees the minimum supply of healthy food and offers space for the construction of healthy eating habits in Brazilian schools. The objective of the present study was to evaluate the presence of Food and Nutrition Education (FNE) actions within the framework of the NSFP to verify its adequacy toward the program's legislation and to investigate which parameters are predictors of running school gardens. This was a cross-sectional observational study using secondary data obtained from the database of the Efficient School Lunch Management Award for the year 2010, with a sample of 749 municipalities in Brazil. A binary logistic regression was performed, considering the running of school gardens as a dependent variable, and the FNE indicators and the demographic variables as independent. The model containing the presence of FNE in the school curriculum was significant (p<0.001). The presence of FNE in school curricula OR=2.406;95%CI=[1.725, 3.357] was the most significant predictor of running school gardens, followed by the use of food from family farms OR=2.049;95%CI=[1.477, 2.842] and the carrying out of culinary workshops OR=2.032;95%CI=[1.442; 2.863], considering p<0.05. The presence of FNE in the school curriculum was positively associated with growing vegetable gardens, showing that complex actions that require more resources can be stimulated from simpler measures, and the NSFP as a public health policy is an important tool to promote actions throughout the national territory.

Abstract
Background: Overweight and obesity in children and adolescents has become an important public health concern in the last decades. To study the way mothers and children’s behavioral factors interact with each other, influencing eating and body weight, may provide information to be used in preventive and treatment strategies.Goals: To study the association of mothers’ eating style on their feeding behavior and on their children’s eating behavior.Methods: Cross-sectional observational study with a non-probabilistic sample of mother and child dyads (from three schools). Mothers’ eating behavior (assessed with Dutch Eating Behavior Questionnaire scale; DEBQ) was classified and they were grouped into three eating styles: restrictive, emotional-external or neutral styles. Mothers’ feeding restriction, pressure to eat and concern about child’s weight were assessed (through the Child Feeding Questionnaire; CFQ). Finally, mothers classified their child’s appetite behaviors (with the Children’s Eating Behaviour Questionnaire; CEBQ).Results: Overall, participated 279 mothers, aged between 23 and 59 years (Mean= 38.03 years, SD=5.09) and respective children (n=279), aged between 6 and 13 years (Mean= 9.43 years, SD= 1.35), 140 of those were females (50.2 %). Associations between mothers’ eating style, their feeding behaviors and children’s appetite traits showed that restrictive and emotional-external eating mothers had higher scores of CFQ and CEBQ items related with obesity, when compared to neutral eating style mothers. Mothers’ feeding restriction and children’s weight concern associated positively with children’s food approach behaviors (enjoyment of food, food responsiveness, emotional over-eating), and negatively with food avoidance behaviors (satiety responsiveness and slowness in eating). On the contrary, pressure to eat associated positively with food avoidance behaviors and negatively with food approach behaviors. Mother´s concern about child weight and feeding restriction were positively associated with CEBQ subscales that reflect food approach and negatively associated with subscales that reflect food avoidance. Pressure to eat had the symmetric associations. Discussion: Results support the hypothesis of the transmission of eating behaviors that promote obesity from mothers to children, and have implications both for prevention and children and adolescents’ obesity treatment. Therefore, mothers should be a part of the intervention when treating their children obesity

Abstract

Abstract
This article addresses the problem of controlling a constrained, continuous-time, nonlinear system through Model Predictive Control (MPC). In particular, we focus on methods to efficiently and accurately solve the underlying optimal control problem (OCP). In the numerical solution of a nonlinear OCP, some form of discretization must be used at some stage. There are, however, benefits in postponing the discretization process and maintain a continuous-time model until a later stage. This is because that way we can exploit additional freedom to select the number and the location of the discretization node points. We propose an adaptive time-mesh refinement (AMR) algorithm that iteratively finds an adequate time-mesh satisfying a pre-defined bound on the local error estimate of the obtained trajectories. The algorithm provides a time-dependent stopping criterion, enabling us to impose higher accuracy in the initial parts of the receding horizon, which are more relevant to MPC. Additionally, we analyze the conditions to guarantee closed-loop stability of the MPC framework using the AMR algorithm. The numerical results show that the proposed AMR strategy can obtain solutions as fast as methods using a coarse equidistant-spaced mesh and, on the other hand, as accurate as methods using a fine equidistant-spaced mesh. Therefore, the OCP can be solved, and the MPC law obtained, faster and/or more accurately than with discrete-time MPC schemes using equidistant-spaced meshes.

Abstract
Radiotherapy planning is a crucial task in cancer patients’ management. This task is, however, very time consuming and prone to a high intra and inter subject variance and human errors. In this way, the present line of work aims at developing a tool to help the specialists in this task. The developed tool will consider the delimitation of anatomical regions of interest, since it is crucial to identify the organs at risk and minimize the exposure of these organs to the radiation. This paper, in particular, presents a lung segmentation algorithm, based on image processing techniques, such as intensity projection and region growing, for Computed Tomography volumes. Our pipeline consists in first separating two halves of the volume to isolate each lung. Then, three techniques for seed placement are developed. Finally, a traditional region growing algorithm has been changed in order to automatically derive the value of the threshold parameter. The results obtained for the three different techniques for seed placement were, respectively, 74%, 74% and 92% of DICE with the Iterative Region Growing algorithm. Although the presented results have as use case the Hodgkin Lymphoma, we believe that the developed method is generalizable to any other pathology. © 2019, Springer Nature Switzerland AG.

Abstract
It is common the use of the sonar technology in order acquire and posteriorly control the distance of an underwater vehicle towards an obstacle. Although this solution simplifies the problem and is effective in most cases, it might carry some disadvantages in certain underwater vehicles or conditions. In this work it is presented a system capable of controlling the altitude of an underwater vehicle using computer vision. The sensor capable of computing the distance is composed of a CCD camera and 2 green pointer lasers. Regarding the control of the vehicle, the solution used was based on the switching of two controllers, a velocity controller (based on a PI controller), and a position controller (based on a PD controller). The vehicle chosen to test the developed system was a profiler, which main task is the vertical navigation. The mathematical model was obtained and used in order to validate the controllers designed using the Simulink toolbox from Matlab. It was used a Kalman filter in order to have a better estimation of the state variables (altitude, depth, and velocity). The tests relative to the sensor developed responsible for the acquisition of the altitude showed an average relative error equal to 1 % in the range from 0 to 2.5 m. The UWsim underwater simulation environment was used in order to validate the integration of the system and its performance. © 2018 IEEE.