A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.Acknowledgments This work has been supported by FCT (Funda¸c˜ao para a Ciˆencia e Tecnologia, Portugal) in the scope of the project PEst-UID/CEC/00319/2013

Exposure of the Portuguese adult population to arsenic: preliminary results of a human biomonitoring study

Abstract publicado em: Environ Health Perspect. 2021;1. https://ehp.niehs.nih.gov/doi/abs/10.1289/isee.2021.P-062BACKGROUND AND AIM:Although arsenic is an element naturally present in the environment, it is highly toxic in its inorganic forms. Exposure can occur through consumption of drinking water and contaminated food. Long-term exposure was shown to be associated with negative health outcomes. Nevertheless, data on the Portuguese population’s exposure to arsenic is scarce. As such, the aim of this work was to assess the exposure to Arsenic in the Portuguese population using samples collected in the study "Exposure of the Portuguese Population to Environmental Chemicals: a study nested in INSEF 2015" (INSEF-ExpoQuim), developed as an aligned study of the European Human Biomonitoring Initiative (HBM4EU). METHODS: INSEF-ExpoQuim was an epidemiologic study nested in INSEF 2015 including 270 participants aged 28-39 years,living in Portugal for more than 12 months and able to follow an interview in Portuguese. Fieldwork was developed between June 2019 and February 2020. First morning urine samples were collected along with data on socio-demographic characteristics, living conditions and residential history, habits/lifestyle, nutrition, health, occupation and substance specific information covering nearly all exposure pathways. Procedures followed the guidelines of the HBM4EU project. Total urinary arsenic is currently being determined by inductively coupled plasma mass spectrometry. RESULTS:Preliminary results for 38 samples yielded total urinary arsenic concentrations ranging from 11 to 462 μg/L with an average of 86 ± 94 μg/L. After completion of the determination of the urinary arsenic levels for all the samples a complete analysis of the data will be performed. CONCLUSIONS:Results from this study will contribute to the knowledge on the Portuguese population’s exposure to arsenic and may support the development and implementation of policy measures aimed at minimizing exposure to this chemical and improving the health of the population.HBM4EU is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 733032.info:eu-repo/semantics/publishedVersio

Growing knowledge: an overview of Seed Plant diversity in Brazil

Abstract An updated inventory of Brazilian seed plants is presented and offers important insights into the country's biodiversity. This work started in 2010, with the publication of the Plants and Fungi Catalogue, and has been updated since by more than 430 specialists working online. Brazil is home to 32,086 native Angiosperms and 23 native Gymnosperms, showing an increase of 3% in its species richness in relation to 2010. The Amazon Rainforest is the richest Brazilian biome for Gymnosperms, while the Atlantic Rainforest is the richest one for Angiosperms. There was a considerable increment in the number of species and endemism rates for biomes, except for the Amazon that showed a decrease of 2.5% of recorded endemics. However, well over half of Brazillian seed plant species (57.4%) is endemic to this territory. The proportion of life-forms varies among different biomes: trees are more expressive in the Amazon and Atlantic Rainforest biomes while herbs predominate in the Pampa, and lianas are more expressive in the Amazon, Atlantic Rainforest, and Pantanal. This compilation serves not only to quantify Brazilian biodiversity, but also to highlight areas where there information is lacking and to provide a framework for the challenge faced in conserving Brazil's unique and diverse flora