Improvement of surface water quality variables modelling that incorporates a hydro-meteorological factor: a state-space approach

In this work it is constructed a hydro-meteorological factor to improve the adjustment of statistical time series models, such as state space models, of water quality variables by observing hydrological series (recorded in time and space) in a River basin. The hydro-meteorological factor is incorporated as a covariate in multivariate state space models fitted to homogeneous groups of monitoring sites. Additionally, in the modelling process it is considered a latent variable that allows incorporating a structural component, such as seasonality, in a dynamic way

Application of Change-Point Detection to a Structural Component of Water Quality Variables

In this study, methodologies were developed in statistical time series models, such as multivariate state-space models, to be applied to water quality variables in a river basin. In the modelling process it is considered a latent variable that allows incorporating a structural component, such as seasonality, in a dynamic way and a change-point detection method is applied to the structural component in order to identify possible changes in the water quality variables in consideration

Using udometric network data to estimate an environmental covariate

Manyhydrologicalandecologicalstudiesrecognizetheimportanceofcharacterizingthetemporalandspatialvari- ability of precipitation. In this study, geostatistical methodologies were developed in order to estimate a hydro-meteorological factor by (re)building the space-time distribution of the precipitation associated to monthly averages in a certain hydrological river basin that will be used in the modelling of surface water quality. A hydro-meteorological factor is constructed for each water quality monitoring site (WQMS), based on the analysis of the space-time behaviour of the precipitation observed in an udometric network located in a Portuguese river basin

A state-space and clustering approach for analysing the water quality in a river basin

The aim of this contribution is to apply the state-space models to identify homogeneous groups of water quality monitoring sites based on compar- ison of temporal dynamics of the concentration of pollutants in the surface water of a river basin. This comparison is performed using the Kullback information, adapting the approach used in Bengtsson and Cavanaugh (2007). The purpose of our study is to identify spatial and temporal patterns

Spatio-temporal stochastic modelling (METMAVI)

Editorial letter for the Special Issue dedicated to the VI International Workshop on Spatio-temporal Modelling (METMAVI), which took place in Guimarães-Portugal from 12 to 14 September 2012. This SI summarizes the main contributions made at METMAVI, related to spatio-temporal methodology illustrated with environmental applications

Combining Statistical Methodologies in Water Quality Monitoring in a Hydrological Basin - Space and Time Approaches

In this work are discussed some statistical approaches that combine multivariate statistical techniques and time series analysis in order to describe and model spatial patterns and temporal evolution by observing hydrological series of water quality variables recorded in time and space. These approaches are illustrated with a data set collected in the River Ave hydrological basin located in the Northwest region of Portugal

Data clustering procedures: a general review

In the age of data science, the clustering of various types of objects (e.g., documents, genes, customers) has become a key activity and many high-quality computer implementations are provided for this purpose by many general software packages. Clustering consists of grouping a set of objects in such a way that objects which are similar to one another according to some metric belong to the same group, named a cluster. It is one of the most valuable and used tasks of exploratory data mining and can be applied to a wide variety of fields. Research on the problem of clustering tends to be fragmented across pattern recognition, database, data mining, and machine learning communities. This work discusses the common techniques that are used in cluster analysis. These methodologies will be applied to data analysis in the framework of polymer processing.A. Manuela Gonçalves was partially financed by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia) within the Projects UIDB/00013/2020 and UIDP/00013/2020 of CMAT-UMThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie SkłodowskaCurie grant agreement No. 734205 – H2020-MSCA-RISE-2016

Novas aplicações de métodos multivariados na análise da mortalidade : um estudo na região Norte de Portugal, 2001-2005

A análise da mortalidade é fundamental no processo de planeamento da saúde e dos serviços de saúde, sendo a taxa de mortalidade padronizada pela idade um dos principais indicadores utilizados. A aplicação da Análise em Componentes Principais e da Análise de Clusters surge, neste trabalho, com o objectivo de identificar conjuntos de causas de morte que possam estar mais correlacionadas entre si e de reunir Agrupamentos de Centros de Saúde (ACES) segundo perfis de mortalidade semelhantes

Outlook in tissue-engineered magnetic systems and biomagnetic control

The advancement of tissue engineering strategies has opened up new therapeutic avenues in the regeneration of many musculoskeletal tissues and cell niches. The burst of research in nanotechnology associated with tissue engineering brings inputs for the precise control of cells and cellular environments, that can play an important role in the development of these new therapies. Magnetic actuation, especially in combination with magnetic nanoparticles, may be a valuable tool in the interaction with living systems, such as stem cell guidance, retention, stimulation, and differentiation. Advances in the field of magnetic technology have also enabled the fabrication of increasingly complex systems such as cell sheets, organoids, or bioprinted scaffolds. Our Opinion article highlights this promising field of research and attempts to cover some of the most recent contributions to both tissue engineering and regenerative medicine. The advancement of tissue engineering strategies has opened up new therapeutic avenues in the regeneration of many musculoskeletal tissues and cell niches. The burst of research in nanotechnology associated with tissue engineering brings inputs for the precise control of cells and cellular environments, that can play an important role in the development of these new therapies. Magnetic actuation, especially in combination with magnetic nanoparticles, may be a valuable tool in the interaction with living systems, such as stem cell guidance, retention, stimula- tion, and differentiation. Advances in the field of magnetic technology have also enabled the fabrication of increasingly complex systems such as cell sheets, organoids, or bioprinted scaffolds. Our Opinion article highlights this promising field of research and attempts to cover some of the most recent con- tributions to both tissue engineering and regenerative medicine.Authors acknowledge the European Research Council COG MagTendon No. 772817, the H2020 Achilles Twinning project No. 810850, and the FCT e Fundação para a Ciência e a Tecnologia under the Scientific Employment Stimulus - Individual Call (CEEC Individual) - 2020.01157. CEECIND/CP1600/CT0024

Change-point analysis in environmental time series

Change-points are present in many environmental time series. Time variations in environmental data are complex and they can hinder the identification of the so-called change-points when traditional models are applied to this type of problems. In this study, it is proposed an alternative approach for the application of the change-point analysis by taking into account this data structure (seasonality and autocorrelation) based on the Schwarz Information Criterion (SIC). The approach was applied to time series of surface water quality variables measured at eight monitoring site