Since the introduction of glyphosate (N-(phosphomethyl) glycine) in 1974, it has been the most used nonselective and broad-spectrum herbicide around the world. The widespread use of glyphosate and glyphosate-based herbicides is due to their low-cost efficiency in killing weeds, their rapid absorption by plants, and the general mistaken perception of their low toxicity to the environment and living organisms. As a consequence of the intensive use and accumulation of glyphosate and its derivatives on environmental sources, major concerns about the harmful side effects of glyphosate and its metabolites on human, plant, and animal health, and for water and soil quality, are emerging. Glyphosate can reach water bodies by soil leaching, runoff, and sometimes by the direct application of some approved formulations. Moreover, glyphosate can reach nontarget plants by different mechanisms, such as spray application, release through the tissue of treated plants, and dead tissue from weeds. As a consequence of this nontarget exposure, glyphosate residues are being detected in the food chains of diverse products, such as bread, cereal products, wheat, vegetable oil, fruit juice, beer, wine, honey, eggs, and others. The World Health Organization reclassified glyphosate as probably carcinogenic to humans in 2015 by the IARC. Thus, many review articles concerning different glyphosate-related aspects have been published recently. The risks, disagreements, and concerns regarding glyphosate usage have led to a general controversy about whether glyphosate should be banned, restricted, or promoted. Thus, this review article makes an overview of the basis for scientists, regulatory agencies, and the public in general, with consideration to the facts on and recommendations for the future of glyphosate usage.

Currently, the design of power electronic converters (PECs) is in a stage which looks increasing its efficiency and reducing its dimensions from basic topologies through precise analysis of losses in each device that conforms. Although there have been important advances to improve the active components of PECs, passive components, particularly inductors, have changed very little since several decades ago, and those begin a limiting factor, when a high efficiency at very high power and switching frequency, are required. It is for the foregoing that this paper reviews new ferromagnetic materials to construct inductors and achieve a substantial increasing in efficiency through magnetic permeability and hysteresis improvements. Therefore, the main objective of this work is to position the reader in the state of the art of advanced ferromagnetic materials used in PECs. Details about how they are constructed and qualitative comparison of their dynamic behavior are provided. Also, estimation methods of energy losses, applications for different types of material, and its influence on the performance of some basic PECs are presented.

Power management strategies (PMS) are applied to keep a balance, between different energy sources (i.e. solar, wind, geothermal, hydro), storage units (i.e. fuel cell, batteries, fly wheel) and loads. Up to date, there has been reported several advance techniques to solve this task, for instance: Fuzzy Logic, Deep Learning, Droop Control, Bayesian Networks, among others. Nevertheless, some of those PMS are over simplified and others are too complex to be programmed in devices with limited resources. To solve these issues, this paper proposes a PMS based on Fuzzy Logic, which keeps a balance between those two goals. Characteristics of the proposed PMS are a small number of rules; fulfillment of the demanded power at every time; reducing use of the storage unit; and keeping a balance between the different sources, storage unit and loads. The proposed PMS is numerically evaluated by using SIMULINK-MATLAB®, in a 10kW residential DC Microgrid (MG), and validated by using a Hardware in the Loop platform (NI myRio-1900 and Typhoon HIL402). A comparison with three popular advance techniques demonstrates the feasibility of the proposed PMS.

Photosynthesis is a process that indicates the productivity of crops. The estimation of this variable can be achieved through methods based on mathematical models. Mathematical models are usually classified as empirical, mechanistic, and hybrid. To mathematically model photosynthesis, it is essential to know: the input/output variables and their units; the modeling to be used based on its classification (empirical, mechanistic, or hybrid); existing measurement methods and their invasiveness; the validation shapes and the plant species required for experimentation. Until now, a collection of such information in a single reference has not been found in the literature, so the objective of this manuscript is to analyze the most relevant mathematical models for the photosynthesis estimation and discuss their formulation, complexity, validation, number of samples, units of the input/output variables, and invasiveness in the estimation method. According to the state of the art reviewed here, 67% of the photosynthesis measurement models are mechanistic, 13% are empirical and 20% hybrid. These models estimate gross photosynthesis, net photosynthesis, photosynthesis rate, biomass, or carbon assimilation. Therefore, this review provides an update on the state of research and mathematical modeling of photosynthesis.

Impedance measuring acquisition systems focused on breast tumor detection, as well as image processing techniques for 3D imaging, are reviewed in this paper in order to define potential opportunity areas for future research. The description of reported works using electrical impedance tomography (EIT)-based techniques and methodologies for 3D bioimpedance imaging of breast tissues with tumors is presented. The review is based on searching and analyzing related works reported in the most important research databases and is structured according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) parameters and statements. Nineteen papers reporting breast tumor detection and location using EIT were systematically selected and analyzed in this review. Clinical trials in the experimental stage did not produce results in most of analyzed proposals (about 80%), wherein statistical criteria comparison was not possible, such as specificity, sensitivity and predictive values. A 3D representation of bioimpedance is a potential tool for medical applications in malignant breast tumors detection being capable to estimate an ap-proximate the tumor volume and geometric location, in contrast with a tumor area computing capacity, but not the tumor extension depth, in a 2D representation.

The ripening process in bananas causes the waste of a significant part of the production of this fruit. The aim of this research is to find a new technique useful for identifying, registering, and quantifying the ripening process of a banana (Musa AAB Simmonds) at the seventh stage of the growing process. This quantification is proposed with a nondestructive technique based on processing multispectral images. This experiment used a set of multispectral imagery registered in a range of 270-1000 nm (from UV to IR) with the aid of a monochromatic camera and a set of 10 optical filters. Multispectral images were analyzed with three different techniques: Fourier fractal analysis, Hotelling transform, and homogeneity texture analysis based on cooccurrence matrix. First, a characteristic index was computed for each technique for a daily set of multispectral imagery. These indexes are slope index, for Fourier fractals; the average of the computed eigenvalues, with Hotelling transform; and the texture homogeneity value. These indexes were evaluated using the behavior of the resulting graphs for a seven-day period, being preferred those graphs with a tendency of decreasing values. Finally, the repeatability of each technique was evaluated by reproducing similar values for each day during the evaluation period. These three methods will be compared in this article in order to select the one with the best performance for measuring the ripening process in bananas. The obtained results show that it is possible to effectively isolate the brown spots from the banana peel with the Hotelling transform by using only 2 optical filters: visible (410-690 nm) and Near-IR (820-910 nm). With the resulting spectral image fusion it was possible to effectively describe the evolution of the brown spots present in the ripening process through the texture homogeneity criteria.