2024
Authors
Figueiredo, AMS; Figueiredo, FO;
Publication
Research in Statistics
Abstract
Abstract.: We consider the headline indicators of the Europe 2020 agenda for the European Union countries for several years of the period 2010–2019 and their own national targets for these indicators. The indicators belong to five thematic areas: employment; education; research, development, and innovation; poverty and social exclusion; climate change; and energy. The main objective of this article is to analyze the dynamics and evolution of the EU countries and the Agenda Europe 2020 indicators over the period, taking into account the relations between the indicators for the EU countries along the years. In order to analyze the different data tables, we have used a three-way data methodology, the STATIS methodology. The results obtained show that the countries of the European Union as a whole have made progress towards the global targets set for the different indicators, with some countries making more significant progress than others. The indicators related to research, development, and innovation, as well as climate change and energy, are the ones where the most improvement is needed. The targets set individually for each country, less demanding for some and more daring for others, were generally already achieved in 2019 or are very close to being achieved. © 2025 Elsevier B.V., All rights reserved.
2024
Authors
Carvalho, M; Borges, A; Gavina, A; Duarte, L; Leite, J; Polidoro, MJ; Aleixo, SM; Dias, S;
Publication
Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2024, Volume 1: KDIR, Porto, Portugal, November 17-19, 2024.
Abstract
The textile industry, a vital sector in global production, relies heavily on dyeing processes to meet stringent quality and consistency standards. This study addresses the challenge of identifying and mitigating non-conformities in dyeing patterns, such as stains, fading and coloration issues, through advanced data analysis and machine learning techniques. The authors applied Random Forest and Gradient Boosted Trees algorithms to a dataset provided by a Portuguese textile company, identifying key factors influencing dyeing non-conformities. Our models highlight critical features impacting non-conformities, offering predictive capabilities that allow for preemptive adjustments to the dyeing process. The results demonstrate significant potential for reducing non-conformities, improving efficiency and enhancing overall product quality.
2024
Authors
Soeiro, R; David, G; Neves, A;
Publication
Journal on Teaching Engineering
Abstract
2024
Authors
Monteiro, M; Pereira, F; Gaspar, M; Jorge, I; Poínhos, R; Oliveira, BM; Rodrigues, S; Afonso, C;
Publication
Acta Portuguesa de Nutrição
Abstract
2024
Authors
Kindlovits, R; Sousa, AC; Viana, JL; Milheiro, J; Oliveira, BMPM; Marques, F; Santos, A; Teixeira, VH;
Publication
NUTRIENTS
Abstract
In the original publication [1], there was a minor error in Figure 1 and Table 6. Unfortunately, Figure 1 presented a smaller text size than appropriate, making it difficult for the reader, in addition to the abbreviation “FiO2” instead of “FiO2”. Then, in Table 6, the basal lactate values between the groups were corrected and the lactate peak values were included. The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated. © 2024 by the authors.
2024
Authors
Sampaio, J; Pizarro, A; Pinto, J; Oliveira, B; Moreira, A; Padrao, P; de Pinho, PG; Moreira, P; Barros, R; Carvalho, J;
Publication
NUTRIENTS
Abstract
Background: Diet and exercise interventions have been associated with improved body composition and physical fitness. However, evidence regarding their combined effects in older adults is scarce. This study aimed to investigate the impact of a combined 12-week Mediterranean diet-based sustainable healthy diet (SHD) and multicomponent training (MT) intervention on body composition, anthropometry, and physical fitness in older adults. Methods: Diet intervention groups received a weekly SHD food supply and four sessions, including a SHD culinary practical workshop. The exercise program included MT 50 min group session, three times a week, on non-consecutive days. Body composition and physical fitness variables were assessed through dual X-ray absorptiometry, anthropometric measurements, and senior fitness tests. Repeated measures ANOVA, with terms for group, time, and interaction, was performed. Results: Our results showed that a combined intervention significantly lowered BMI and total fat. Also, significant differences between assessments in all physical fitness tests, except for aerobic endurance, were observed. Adjusted models show significant differences in BMI (p = 0.049) and WHR (p = 0.037) between groups and in total fat (p = 0.030) for the interaction term. Body strength (p < 0.001), balance tests (p < 0.001), and aerobic endurance (p = 0.005) had significant differences amongst groups. Considering the interaction term, differences were observed for upper body strength (p = 0.046) and flexibility tests (p = 0.004 sit and reach, p = 0.048 back scratch). Conclusions: Our intervention study demonstrates the potential of implementing healthy lifestyle and sustainable models to promote healthy and active aging.
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