Modelling environmental monitoring data coming from different surveys

With this work we propose a spatio-temporal model for Gaussian data collected in a small number of surveys. We assume the spatial correlation structure to be the same in all surveys. In the application concerning heavy metal concentrations in mosses, the data set is dense in the spatial dimension but sparse in the temporal one, thus our model-based approach corresponds to a correlation model depending on survey orders. One advantage of this approach is its computational simplicity. An interpretation for the space-time covariance function, decomposing the overall variance of the process as the product of the spatial component variance by the temporal component variance, is introduced. A simulation study, aiming to validate the model, provided better results in terms of accuracy with the novel covariance function. Maps of predicted heavy metal concentrations and of interpolation error, for the most recent survey, are presented.Data of this kind is recurrent in environmental sciences, which is why we argue that this will be a practical tool to be used very often

The Determination of Cannabinoids in Urine Samples Using Microextraction by Packed Sorbent and Gas Chromatography-Mass Spectrometry

Cannabis is the most consumed illicit drug worldwide, and its legal status is a source of concern. This study proposes a rapid procedure for the simultaneous quantification of Δ9-tetrahydrocannabinol (THC), 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH), cannabidiol (CBD), and cannabinol (CBN) in urine samples. Microextraction by packed sorbent (MEPS) was used to pre-concentrate the analytes, which were detected by gas chromatography–mass spectrometry. The procedure was previously optimized, and the final conditions were: conditioning with 50 µL methanol and 50 µL of water, sample load with two draw–eject cycles, and washing with 310 µL of 0.1% formic acid in water with 5% isopropanol; the elution was made with 35 µL of 0.1% ammonium hydroxide in methanol. This fast extraction procedure allowed quantification in the ranges of 1–400 ng/mL for THC and CBD, 5–400 ng/mL for CBN and 11-OH-THC, and 10–400 ng/mL for THC-COOH with coefficients of determination higher than 0.99. The limits of quantification and detection were between 1 and 10 ng/mL using 0.25 mL of sample. The extraction efficiencies varied between 26 and 85%. This analytical method is the first allowing the for determination of cannabinoids in urine samples using MEPS, a fast, simple, and low-cost alternative to conventional techniquesinfo:eu-repo/semantics/publishedVersio

Mitigation of urban heat island effects by thermochromic asphalt pavement

Asphalt road pavements are usually dark and, consequently, have a low albedo. Therefore, they absorb energy as heat, increasing the Urban Heat Island (UHI) effect, which impacts the environment, energy consumption, and human health. Through the functionalization with thermochromic materials (TM), this work aims to develop a smart asphalt pavement able to change its surface color, increasing the reflectance, and thus mitigate this phenomenon. To achieve this goal, asphalt substrates were functionalized by a surface spray coating of a thermochromic solution (TS) containing aqueous solution of thermochromic microcapsules (thermocapsules), dye, and epoxy resin. To evaluate the functionalization features, Fourier Transform Infrared Spectroscopy (FTIR), and Thermal Differential test (TDT) with cyclic temperature variation were performed in the functionalized asphalt binder. Moreover, Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectrometry (EDS), a Quick Ultraviolet Accelerated Weathering Test (QUV) with Colorimetry test, and an adaptation of the Accelerated Polishing Test (APT) were performed on the functionalized asphalt mixture. The results indicate that the functionalization of asphalt substrates with TS exhibits a reversible color-change ability, higher luminosity values when subjected to temperatures above 30 C, and wear resistance

Desenvolvimento e validação de um método para a determinação de canabinóides em urina por microextracção em seringa empacotada e GC-MS

Resumo de poster apresentado em: 20º Congresso Nacional de Medicina Legal e Ciências Forenses/5ª Reunião da Rede de Serviços Médico-Legais e Forenses de Países de Língua PortuguesaDe acordo com o Observatório Europeu da Droga e da Toxicodependência, no último ano (dados de junho de 2022), existiam aproximadamente 22,2 milhões consumidores de canábis na Europa. A urina é uma das amostras mais utilizadas para a deteção e quantificação de canabinóides. (...)N/

Modelação espaço-temporal de dados ambientais

Programa Doutoral em Matemática e Aplicações.Environmental monitoring may be defined as a description of processes and activities performed to characterize and monitor the quality of the environment. Monitoring schemes may differ greatly in their spatial and temporal extent, but as an outcome of any environmental monitoring process, data are gathered exhibiting both a spatial and a temporal dimension. With this work, we aim to analyze the predictive accuracy when characterizing the spatio-temporal patterns of heavy metal deposition in mainland Portugal. The data set in use consists of measurements of heavy metal deposition in mosses, resulting from three nationwide surveys performed in 1992, 1996 and 2002. Firstly, we begin with an exploratory descriptive analysis and an exploratory spatial analysis of the data, using well known techniques of spatial interpolation. After, we propose to make a spatio-temporal prediction of heavy metal concentration for the most recent survey, allowing to incorporate georeferenced explanatory covariates of the process under observation, calling on an existing spatio-temporal prediction model. This model focuses on the spatial dimension by defining random fields for the mean, the scale and the residuals components, and incorporates the time dimension by means of strictly temporal random fields, which work as corrections for the temporal evolution of the process. Motivated by the fact that the data set in use in dense in the spatial dimension but sparse in the temporal one, a novel model-based approach is proposed for Gaussian data, corresponding to a saturated correlation model in the time dimension. The proposed model is derived in order to accommodate not exclusively geo-referenced covariates, but also covariates associated to the temporal behavior of the process. Regarding the results obtained in terms of predictive accuracy, a comparison of predictions from a purely spatial model with the ones from a spatiotemporal model showed that the latter improve the accuracy of predicted value. Moreover, if the comparison is restricted to the two spatio-temporal models, the new model proposal provides better results.Por monitorização ambiental entende-se uma descrição dos processos e atividades realizadas para caracterizar e monitorizar a qualidade do meio ambiente. Apesar de diferentes estudos de monitorização ambiental poderem diferir em termos de extensão espacial e temporal, de qualquer processo de monitorização resultam dados que apresentam tanto uma dimensão espacial como uma dimensão temporal. Com este trabalho, pretende-se analisar a precisão das predições efetuadas ao caracterizar os padrões espaço-temporais de deposição de metais pesados em Portugal continental. A base de dados utilizada neste estudo consiste em medidas de deposição de metais pesados em musgos, resultante de três campanhas de amostragem a nível nacional, realizados em 1992, 1996 e 2002. Inicialmente será efetuada uma análise exploratória descritiva e uma análise exploratória espacial dos dados, utilizando técnicas bem conhecidas de interpolação espacial. De seguida, será desenvolvida uma previsão espaço-temporal da concentração de metais pesados para a campanha mais recente, permitindo incorporar variáveis geo-referenciadas explicativas do processo sob observação. Para isso, iremos recorrer a um modelo de previsão espaço-temporal existente. Este modelo incide sobre a dimensão espacial do processo através da definição de campos aleatórios para a média, para a escala e para os resíduos, e incorporando a dimensão temporal por meio de campos aleatórios estritamente temporais, que funcionam como correções para a evolução temporal do processo. Motivados pelo fato de o conjunto de dados em uso ser denso na dimensão espacial, mas escasso em termos temporais, é proposta uma abordagem model-based para dados Gaussianos, e que corresponde a um modelo de correlação saturado na dimensão temporal. O modelo proposto é deduzido de forma a acomodar não somente covariáveis geo-referenciadas, mas também covariáveis associadas ao comportamento temporal do processo. No que respeita à precisão dos valores de concentração de metais pesados, a comparação das previsões obtidas por meio de modelos puramente espaciais com as obtidas por modelos espaço-temporais revelou um melhor desempenho por parte destes últimos. É de realçar ainda que, se a comparação for restringida aos dois modelos espaço-temporais, a abordagem model-based proporciona melhores resultados.Fundação para a Ciência e a Tecnologia (FCT) PTDC/MAT/112338/2009

Predicting motor oil condition using artificial neural networks and principal component analysis

The safety and performance of engines such as Diesel, gas or even wind turbines depends on the quality and condition of the lubricant oil. Assessment of engine oil condition is done based on more than twenty variables that have, individually, variations that depend on the engines’ behaviour, type and other factors. The present paper describes a model to automatically classify the oil condition, using Artificial Neural Networks and Principal Component Analysis. The study was done using data obtained from two passenger bus companies in a country of Southern Europe. The results show the importance of each variable monitored for determining the ideal time to change oil. In many cases, it may be possible to enlarge intervals between maintenance interventions, while in other cases the oil passed the ideal change point.Bezpieczeństwo i wydajność silników takich, jak silniki Diesla czy gazowe, a nawet turbiny wiatrowe, zależą od jakości i stanu oleju smarowego. Stanu oleju silnikowego ocenia się na podstawie ponad dwudziestu zmiennych, z których każda ulega wahaniom w zależności od typu i zachowania silnika oraz innych czynników. W niniejszym artykule opisano model, który pozwala na automatyczną klasyfikację stanu oleju, z wykorzystaniem sztucznych sieci neuronowych i analizy składowych głównych. Badania przeprowadzono na podstawie danych uzyskanych od dwóch przewoźników pasażerskich działających na terenie jednego z krajów położonych na południu Europy. Wyniki pokazują, że każda z monitorowanych zmiennych ma znaczenie dla określenia idealnego czasu na wymianę oleju. Podczas gdy w wielu przypadkach w badanych przedsiębiorstwach możliwe było zwiększenie odstępów czasowych między działaniami konserwacyjnymi, w innych, idealny moment wymiany oleju został przekroczony

Monitoring NO3 contamination of aquifer system of Bacia do Cávado/Ribeiras Costeiras

Groundwater quality is subject to law 2006/118/CE, related to protection against pollution. In Portugal, law 306/2007 establishes conditions for human consumption. Aquifers are subject to several pollutants, namely chemicals used for agricultural purposes. The aim of this work is to present a stochastic model for the concentration of NO3 over the aquifer of the so-called vulnerable zone number 1, Esposende-Vila do Conde, on the northern region of Portugal. The model proposed was fitted to four time periods, independently of each other, being spring and fall of 2008 and 2009.The second and third authors acknowledge financial support from the projects PTDC/MAT/104879/2008 (FEDER support included) of the Portuguese Ministry of Science, Technology and Higher Education

Development of a Dynamic Hands-Free Door Opener to Prevent COVID-19 Pandemic Spreading

The situation caused by COVID-19 has shown several vulnerabilities in the attitudes and habits of modern society, inducing the need to adopt new behaviors that will directly impact daily activities. The quickly spreading virus contaminates the surfaces of handles and objects, and subsequent contact with the eyes, nose, or mouth is one of the main contagion factors. There is an urgent need to rethink how we interact with the most-touched surfaces, such as door handles in public places with a high flux of people. A revision was performed of the most-used door handles to develop a proposal that could be applied to already existing models, thus avoiding the need for their total replacement. Through interaction between engineering, design, and ergonomics, an auxiliary hands-free door opener device was developed, following iteration improvement from an initial static geometry and culminating in a dynamic system aiming to provide greater ergonomic comfort in its use. The development followed a methodology using 3D modelling supported by 3D printing of the various components to accurately understand their functioning. In addition, the finite element method supported the prediction of the structural behavior of the developed systems. The final models were produced through CNC machining and submitted to functional validation tests with volunteers. The developed HFDO demonstrated relevant differentiation from the existing models on the market: for its geometry and material, but mainly for its strong emphasis on the interaction between the object and the user, resulting from the dynamic component in its use/manipulation

Mitigation of Urban Heat Island Effects by Thermochromic Asphalt Pavement

Asphalt road pavements are usually dark and, consequently, have a low albedo. Therefore, they absorb energy as heat, increasing the Urban Heat Island (UHI) effect, which impacts the environment, energy consumption, and human health. Through the functionalization with thermochromic materials (TM), this work aims to develop a smart asphalt pavement able to change its surface color, increasing the reflectance, and thus mitigate this phenomenon. To achieve this goal, asphalt substrates were functionalized by a surface spray coating of a thermochromic solution (TS) containing aqueous solution of thermochromic microcapsules (thermocapsules), dye, and epoxy resin. To evaluate the functionalization features, Fourier Transform Infrared Spectroscopy (FTIR), and Thermal Differential test (TDT) with cyclic temperature variation were performed in the functionalized asphalt binder. Moreover, Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectrometry (EDS), a Quick Ultraviolet Accelerated Weathering Test (QUV) with Colorimetry test, and an adaptation of the Accelerated Polishing Test (APT) were performed on the functionalized asphalt mixture. The results indicate that the functionalization of asphalt substrates with TS exhibits a reversible color-change ability, higher luminosity values when subjected to temperatures above 30 °C, and wear resistance