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The purpose of this paper is to propose a web‐based tool that enables the development and provision of learning designs and its reuse and re‐contextualization as generative learning objects, aimed at developing educational materials.

The use of learning objects can facilitate the process of production and delivering of educational material and their reuse and re‐contextualization in different scenarios – such process is due to the current development stage of information and communication technologies (ICTs), which allow easy access to products and services related to them. ICTs combined with instructional design theories, lead to the emergence of new generations of distance learning, which add educational content to web‐based services. From this combination rises a hybrid mode of education, which combines tools for face‐to‐face and distance learning (blended learning).

The use of the web as a platform for production and management of learning objects comes as a solution for storage and sharing. The utilization of objects is justified when its reusability is facilitated. This gives rise to possibilities in a client‐server environment, where information is centralized and available anywhere in the network.

The combination of ICT and instructional design theories has potential and could result in hybrids which are yet to be fully understood and explored. This can enhance blended learning provision.

The paper presents a tool in which the learning designs work as structures built on XML, based on concept maps, which act as an interaction layer between the learning objects, organizing the content to be available.

The purpose of this paper is to present the development of a software for stereo visualization of geometric solids, applied to the teaching/learning of Descriptive Geometry.

The paper presents the traditional method commonly used in computer graphic stereoscopic vision (implemented in C language) and the proposed method (implemented in GeoGebra software). The proposed method is a new methodology for stereo spatial visualization. It uses the orthogonal axonometric perspective obtained from the mongean projections of the object, both concepts studied in Descriptive Geometry course.

The use of stereoscopic techniques has great potential for the improvement of spatial visualization ability, because they allow the understanding of spatial situations presented in complex exercises. The students who tested the proposed method said that it offered a superior stereo vision depth in relation to the traditional matrix method.

For future work, the paper suggests to carry out a statistical study to evaluate the educational benefit of the tool, and to investigate the proposed method using the conical axonometric perspective.

Create a virtual environment to support the process of teaching/learning Descriptive Geometry and contribute to the development of students ' spatial visualization skills. The software will be available on the Internet, in the GeoGebra libraries. The objective is to increase e-learning, where a greater number of students will study.

The current goal in Brazil universities is to greatly increase the number of poor students entering as a social inclusion strategy. University courses need more efficient teaching techniques to attend the students, so the e-learning techniques are recommended.

This paper’s innovative characteristic comes from the implementation of stereoscopic vision from traditional methods used in Descriptive Geometry, so the proposed method improves both the visualization ability and the Descriptive Geometry basic concepts, which points out to its educational role.

Emotional competence supports preschoolers’ social relationships and school success. Parents’ emotions and reactions to preschoolers’ emotions can help them become emotionally competent, but scant research corroborates this role for preschool teachers. Expected outcomes included: teachers’ emotion socialization behaviors functioning most often like parents’ in contributing to emotional competence, with potential moderation by socioeconomic risk. This paper aims to discuss this issue.

Participants included 80 teachers and 312 preschoolers experiencing either little economic difficulty or socioeconomic risk. Children’s emotionally negative/dysregulated, emotionally regulated/productive and emotionally positive/prosocial behaviors were observed, and their emotion knowledge was assessed in Fall and Spring. Teachers’ emotions and supportive, nonsupportive and positively emotionally responsive reactions to children’s emotions were observed during Winter. Hierarchical linear models used teacher emotions or teacher reactions, risk and their interactions as predictors, controlling for child age, gender and premeasures.

Some results resembled those parents’: positive emotional environments supported children’s emotion knowledge; lack of nonsupportive reactions facilitated positivity/prosociality. Others were unique to preschool classroom environments (e.g. teachers’ anger contributed to children’s emotion regulation/productive involvement; nonsupportiveness predicted less emotional negativity/dysregulation). Finally, several were specific to children experiencing socioeconomic risk: supportive and nonsupportive reactions, as well as tender emotions, had unique, but culturally/contextually explainable, meanings in their classrooms.

Applications to teacher professional development, and both limitations and suggestions for future research are considered.

This study is among the first to examine how teachers contribute to the development of preschoolers’ emotional competence, a crucial set of skills for life success.

To describe water absorption by the rice grains over time, diffusion and empirical models were used. Also, an optimization software was developed in this study to determine parameters and their uncertainties for the diffusion models (LS Optimizer, for partial differential equations). Parameters (and their uncertainties) for empirical models were determined by LAB Fit Curve Fitting Software.

Heat and mass diffusion phenomena are found in various processes of technological interest, including pasteurization, drying and water immersion of agricultural products, among others. The objective of this work was to study the process of water absorption by rice grains with and without husk, using diffusion and empirical models to describe the absorption kinetics. Rice grains were immersed (approximately 10 g for each experiment) in drinking water maintained at constant temperatures of 28, 40 and 50 C. In the experiments, the water contents absorbed by rice grains over time were obtained by the gravimetric method.

Among empirical models, Peleg was the most satisfactory to describe the kinetics of water absorption by rice without husk, while the Silva et alii model had the best statistical indicators for rice with husk. It was also verified that a diffusion model with boundary condition of the first kind showed the best (or equivalent) results in the description of all processes of kinetics of water absorption by rice grains, with and without husk. For grains without husk, the effective mass diffusivities were (1.186 ± 0.045) × 10⁻⁹, (1.312 ± 0.024) × 10⁻⁹ and (2.133 ± 0.028) × 10⁻⁹ m² min⁻¹, for the immersion temperatures of 28, 40 and 50C, respectively. For grains with husk, diffusivities were (0.675 ± 0.011) × 10⁻⁹ and (1.269 ± 0.017) × 10⁻⁹ m² min⁻¹, for temperatures of 28 and 50 C, respectively.

This work developed a solver for the diffusion equation in cylindrical geometry and presented the LS Optimizer software developed to determine differential equation parameters through experimental data sets.

This study deals with the computational simulation and inverse analysis of the cooling treatment of the hypoxic-ischemic encephalopathy in neonates. A reduced-order model is implemented for real-time monitoring of the internal body temperatures. The purpose of this study is to sequentially estimate the transient temperatures of the brain and other body regions with reduced uncertainties.

Pennes’ model was applied in each body element, and Fiala’s blood pool concept was used for the solution of the forward bioheat transfer problem. A state estimation problem was solved with the Sampling Importance Resampling (SIR) algorithm of the particle filter method.

The particle filter method was stable and accurate for the estimation of the internal body temperatures, even in situations involving large modeling and measurement uncertainties.

The proposed reduced-order model was verified with the results of a high-fidelity model available in the literature. Validation of the proposed model and of the solution of the state estimation problem shall be pursued in the future.

The solution of the state estimation problem with the reduced-order model presented in this paper has great potential to perform as an observer of the brain temperature of neonates, for the analysis and control of the systemic cooling treatment of neonatal hypoxic-ischemic encephalopathy.

The main treatment for hypoxic-ischemic encephalopathy in neonates is the cooling of affected regions. Accurate and fast models might allow the development of individualized protocols, as well as control strategies for the cooling treatment.

This paper presents the application of the SIR algorithm for the solution of a state problem during the systemic cooling of a neonate for the treatment of the hypoxic-ischemic encephalopathy.

The authors explore the hypothesis that some movements in commodity prices are anticipated (news shocks) and can trigger aggregate fluctuations in small open emerging economies. This paper aims to discuss the aforementioned objective.

The authors build a multi-sector dynamic stochastic general equilibrium model with endogenous commodity production. There are five exogenous processes: a country-specific interest rate shock that responds to commodity price fluctuations, a productivity (TFP) shock for each sector and a commodity price shock. Both TFP and commodity price shocks are composed of unanticipated and anticipated components.

The authors show that news shocks to commodity prices lead to higher output, investment and consumption, and a countercyclical movement in the trade-balance-to-output ratio. The authors also show that commodity price news shocks explain about 24% of output aggregate fluctuations in the small open economy.

Given the importance of both anticipated and unanticipated commodity price shocks, policymakers should pay attention to developments in commodity markets when designing policies to attenuate the business cycles. Future research should investigate the design of optimal fiscal and monetary policies in SOE subject to news shocks in commodity prices.

This paper contributes to the knowledge of the sources of fluctuations in emerging economies highlighting the importance of a new source: news shocks in commodity prices.

In recent years, housing prices in Brazil have shown a surprising growth. An important issue is trying to understand what elements can explain this behavior. This study aims to investigate the hypothesis that a generalized optimism associated with government policies directed to the housing sector may be behind the behavior of real estate prices. This study develops a dynamic stochastic general equilibrium (DSGE) model to investigate these issues. The results showed that subsidies combined with the easing of credit conditions were able to positively influence real estate prices. Moreover, unanticipated shocks had a greater impact on housing prices than anticipated shocks.

The DSGE model was developed to analyze the relationship between economic agents’ expectations about future economic developments, also known in the literature as “news shocks,” expansionary fiscal policy and housing prices in Brazil. The economy is composed of families, entrepreneurs, final goods firms, a financial sector and a fiscal authority. Families are divided into two groups: patients or savers and impatient or debtors. They differ in terms of their intertemporal discount factors. Both provide labor for firms producing non-durable goods. Impatient families are restricted in the amount of borrowing they can take. The production side of economy model is given by the consumer goods production sector. The financial sector is composed of a representative bank that pays the deposits made by patient families and channels resources for the granting of housing loans with the accumulation of assets subject to regulatory restrictions.

The results show that both price subsidies and subsidized interest rates exerted a positive influence on housing prices in Brazil. In response to a housing demand shock, housing prices display a greater increase the greater are the subsidies to low income families. The authors show that anticipated shocks have a larger impact on housing prices than unexpected shocks. Therefore, the results support the idea that the wave of good news, optimistic behavior and government policies aimed at the housing sector were behind the behavior of housing prices in Brazil.

There are some studies applied to the Brazilian economy that mention some of these stimuli. In this study, the authors focused on studies proposed by Mendonça et al. (2011), Mendonça (2013), Silva et al. (2014) and Besarria et al. (2016). In general, the authors show that there is a negative relationship between monetary policy instruments and real estate prices. This paper differs from these authors by considering the effects of government subsidies, subsidized interest rates and anticipated shocks from a DSGE model, thus explicitly addressing their effects on housing prices in Brazil.

The purpose of this paper is to quantify the relative importance of the multiphase model for the simulation of a gas bubble impacted by a normal shock wave in water. Both the free-field case and the collapse near a wall are investigated. Simulations are performed on both two- and three-dimensional configurations. The main phenomena involved in the bubble collapse are illustrated. A focus on the maximum pressure reached during the collapse is proposed.

Simulations are performed using an inviscid compressible homogeneous solver based on different systems of equations. It consists in solving different mixture or phasic conservation laws and a transport-equation for the gas volume fraction. Three-dimensional configurations are considered for which an efficient massively parallel strategy was developed. The code is based on a finite volume discretization for which numerical fluxes are computed with a Harten, Lax, Van Leer, Contact (HLLC) scheme.

The comparison of three multiphase models is proposed. It is shown that a simple four-equation model is well-suited to simulate such strong shock-bubble interaction. The three-dimensional collapse near a wall is investigated. It is shown that the intensity of pressure peaks on the wall is drastically increased (more than 200 per cent) in comparison with the cylindrical case.

The study of bubble collapse is a key point to understand the physical mechanism involved in cavitation erosion. The bubble collapse close to the wall has been addressed as the fundamental mechanism producing damage. Its general behavior is characterized by the formation of a water jet that penetrates through the bubble and the generation of a blast wave during the induced collapse. Both the jet and the blast wave are possible damaging mechanisms. However, the high-speed dynamics, the small spatio-temporal scales and the complicated physics involved in these processes make any theoretical and experimental approach a challenge.

Cavitation erosion is a major problem for hydraulic and marine applications. It is a limiting point for the conception and design of such components.

Such a comparison of multiphase models in the case of a strong shock-induced bubble collapse is clearly original. Usually models are tested separately leading to a large dispersion of results. Moreover, simulations of a three-dimensional bubble collapse are scarce in the literature using such fine grids.

The purpose of this paper is to develop a monitoring multiple-stream processes control chart with a finite mixture of probability distributions in the manufacture industry.

Data were collected during production of a wheat-based dough in a food industry and the control charts were developed with these steps: to collect the master sample from different production batches; to verify, by graphical methods, the quantity and the characterization of the number of mixing probability distributions in the production batch; to adjust the theoretical model of probability distribution of each subpopulation in the production batch; to make a statistical model considering the mixture distribution of probability and assuming that the statistical parameters are unknown; to determine control limits; and to compare the mixture chart with traditional control chart.

A graph was developed for monitoring a multi-stream process composed by some parameters considered in its calculation with similar efficiency to the traditional control chart.

The control chart can be an efficient tool for customers that receive product batches continuously from a supplier and need to monitor statistically the critical quality parameters.