Inadequate disposal of Municipal Solid Waste (MSW) is one of the greatest environmental issues confronted nowadays. One of the techniques used for its final disposal is incineration, otherwise known as mass burning. Although this procedure remains very controversial in Brazil, some recent studies published in Europe reveal a large amount of misinformation about it. It has been widely used in European countries, Japan, and a few U.S. cities and has been increasingly and significantly adopted in China. Therefore, this article aims to carry out a literature review on the evolution of waste-to-energy recovery from Municipal Solid Waste (MSW) worldwide and the progress of mass-burning technologies, particularly in the Brazilian context. For such a purpose, global scientific databases were selected and some of their results allowed us to present how the main WtE recovery technologies function, as well as their benefits and impacts. Moreover, it was possible to systematize the main regulatory frameworks on the theme in Brazil and to reveal the country’s electricity generation capacity, in addition to depicting the progress of Waste-to-Energy Plants (WtEPs) undergoing licensing processes in the state of São Paulo.

The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.

Climate change is causing an increase in dry spells, altering rainfall patterns and soil moisture, and affecting water and nutrient plant uptake, which inevitably affects vegetable production. To mitigate this issue, some technologies that allow the maintenance of the ideal soil moisture for the uptake process are being investigated. Considering this, we hypothesize that the use of water treated with a magnetic field can increase water use efficiency in lettuce crop production. Thus, the present study aimed to evaluate the effect of the irrigation rate of magnetically treated water on biomass accumulation and nutrient uptake by lettuce plants. An experiment was conducted in a randomized block design with a 2 × 5 factorial arrangement of two water sources (conventional water and magnetically treated water) and five irrigation application rates to replace crop evaporation: 25, 50, 75, 100, and 125%, with five replicates. The use of magnetically treated water increased the concentrations of nitrogen and phosphorus in leaves, meaning that it induced higher nitrogen assimilation, leading to increases in agronomical characteristics (leaf number, fresh and dry shoot weight, fresh and dry root weight). The conclusions of this study showcase that magnetically treated water has beneficial effects on lettuce plants, improving their nutritional status and yield. Moreover, the results presented can lead to an increase in water use efficiency, thus optimizing irrigation management.

In agriculture with 4.0 technologies, developing a decision model with a 0.0 cost is attractive to small farmers. In water management, if this approach could be used to promote sustainability and optimization, it could become a pathway to reach the sustainable development goal in 2030. The core of this work is the development of a 4.0 mathematical model (based on fuzzy concepts) to verify the benefits of the production of lettuce irrigated with magnetically treated water at different replacement rates. This approach is achieved using computational 4.0 software and manual methods. The aim of mathematical modeling is to understand or explain a natural phenomenon associated with a given area of knowledge, and fuzzy-rule-based systems have been widely used in different types of in-depth research.

The rural electrification is characterized by geographical dispersion of the population, low consumption, high investment by consumers and high cost. Moreover, solar radiation constitutes an inexhaustible source of energy and in its conversion into electricity photovoltaic panels are used. In this study, equations were adjusted to field conditions presented by the manufacturer for current and power of small photovoltaic systems. The mathematical analysis was performed on the photovoltaic rural system I-100 from ISOFOTON, with power 300 Wp, located at the Experimental Farm Lageado of FCA/UNESP. For the development of such equations, the circuitry of photovoltaic cells has been studied to apply iterative numerical methods for the determination of electrical parameters and possible errors in the appropriate equations in the literature to reality. Therefore, a simulation of a photovoltaic panel was proposed through mathematical equations that were adjusted according to the data of local radiation. The results have presented equations that provide real answers to the user and may assist in the design of these systems, once calculated that the maximum power limit ensures a supply of energy generated. This real sizing helps establishing the possible applications of solar energy to the rural producer and informing the real possibilities of generating electricity from the sun.