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Complex graph neural networks for medication interaction verification
Publication . Westarb, Gustavo; Stefenon, Stefano Frizzo; Hoppe, Aurélio Faustino; Sartori, Andreza; Klaar, Anne Carolina Rodrigues; Leithardt, Valderi Reis Quietinho
This paper presents the development and application of graph neural networks to verify drug interactions, consisting of drug-protein networks. For this, the DrugBank databases were used, creating four complex networks of interactions: target proteins, transport proteins, carrier proteins, and enzymes. The Louvain and Girvan-Newman community detection algorithms were used to establish communities and validate the interactions between them. Positive results were obtained when checking the interactions of two sets of drugs for disease treatments: diabetes and anxiety; diabetes and antibiotics. There were found 371 interactions by the Girvan-Newman algorithm and 58 interactions via Louvain.
Prevalence of Lower Back Pain in Portuguese Equestrian Riders
Publication . Duarte, Carlota; Santos, R.; Fernandes, Orlando; Raimundo, Armando; Autor correspondente: Santos, R..
Lower back pain is prevalent in equestrian athletes, but its prevalence and associated factors
are unknown in the Portuguese equestrian population. A questionnaire regarding lower back pain
and possible associated factors was answered by 347 respondents. Of the respondents, 214 (61.7%)
stated having experienced lower back pain in the past 12 months and therefore completed the Roland
Morris disability questionnaire. Among the latter, 63.1% stated that lower back pain impaired their
performance. The probability of suffering from lower back pain was higher in individuals with
higher weekly riding workloads, who reported equestrianism as their main occupation, and who
performed daily stable duties. Considering a Roland Morris disability score of 4 as the cut-off
value for dysfunction, this sample had an average score of 5.39 ± 4.42. Individuals who stated
equestrianism was their main occupation showed a significantly higher risk (OR = 1.759, p = 0.041) of
exhibiting a score ≥ 4 than those who stated equestrianism as a hobby. Age (p = 0.029), body mass
index (p = 0.047), and daily performance of stable duties (p = 0.030) were also associated with a higher
Roland Morris disability score. Further research is needed to understand the full impacts of lower
back pain in Portuguese equestrian athletes.
Global Dynamics of Environmental Kuznets Curve: A Cross-Correlation Analysis of Income and CO2 Emissions
Publication . Almeida, Dora; Carvalho, Luísa; Ferreira, Paulo; Dionísio, Andreia; Haq, Inzamam Ul
The environmental Kuznets curve (EKC) hypothesis posits an inverted U-shaped relationship between economic growth and environmental degradation. However, there is no consensus
regarding the EKC hypothesis among countries and regions of different income groups. This study
revisits the EKC hypothesis by employing cross-correlation analysis to explore the income–CO2
emissions relationship across 158 countries and 44 regions from 1990 to 2020. The empirical method
utilizes a dynamic cross-correlation coefficient (CCC) approach, allowing for the assessment of
lead-lag dynamics between income and CO2 emissions over time. By categorizing nations into the
World Bank’s income classifications, we found a heterogeneous EKC pattern highlighting distinct
environmental–economic dynamics across different income groups. The findings indicate that highincome countries show a decoupling of economic growth from CO2 emissions; whereas, low-income
countries still exhibit a positive correlation between both variables. This underscores the necessity
for tailored policy interventions that promote carbon neutrality, while considering each country’s
unique development stage. Our research contributes to the ongoing issue of sustainable economic
development by providing empirical evidence of the different pathways nations follow in balancing
growth with environmental preservation.
COVID-19 Effects on the Relationship between Cryptocurrencies: Can It Be Contagion? Insights from Econophysics Approaches
Publication . Dora Almeida; Andreia Dionísio; Isabel Vieira; Paulo Ferreira
Cryptocurrencies are relatively new and innovative financial assets. They are a topic
of interest to investors and academics due to their distinctive features. Whether financial or not,
extraordinary events are one of the biggest challenges facing financial markets. The onset of the
COVID-19 pandemic crisis, considered by some authors a “black swan”, is one of these events.
In this study, we assess integration and contagion in the cryptocurrency market in the COVID-19
pandemic context, using two entropy-based measures: mutual information and transfer entropy. Both
methodologies reveal that cryptocurrencies exhibit mixed levels of integration before and after the
onset of the pandemic. Cryptocurrencies displaying higher integration before the event experienced
a decline in such link after the world became aware of the first cases of pneumonia in Wuhan city.
In what concerns contagion, mutual information provided evidence of its presence solely for the
Huobi Token, and the transfer entropy analysis pointed out Tether and Huobi Token as its main
source. As both analyses indicate no contagion from the pandemic turmoil to these financial assets,
cryptocurrencies may be good investment options in case of real global shocks, such as the one
provoked by the COVID-19 outbreak.
Quality Education for All: A Fuzzy Set Analysis of Sustainable Development Goal Compliance
Publication . Carvalho, Luisa; Almeida, Dora; Loures, Ana; Ferreira, Paulo; Rebola, Fernando
The relationship between education and societal development is unquestionable. Education
contributes to achieving both societies’ and individuals’ social and economic goals. Quality education
is recognized as one of the Sustainable Development Goals (SDGs), which, jointly with other behaviors
and attitudes, could impact the development of societies in other fields like health and well-being,
cultural preservation, environmental sustainability, and even peace and stability—all of them also
listed as SDGs. However, the capacity, or not, to reach higher levels of compliance with quality in
education (SDG 4) varies from country to country, according to the 2023 Sustainable Development
Report results. Thus, the present study aims to identify the sufficient conditions for achieving higher
levels of quality education (SDG 4) globally and to analyze how these conditions vary across different
world regions. Applying a fuzzy set qualitative comparative analysis and using data from the 2023
Sustainable Development Report, we focus our analysis on four SDG 4 indicators—early education,
primary education, lower secondary education, and literacy rate—across 117 countries, in order to
assess the conditions for attaining higher levels of quality education. The results reveal there are
specific and identifiable conditions that are sufficient for achieving higher levels of quality education
on a global scale, with significant regional variations. These insights contribute to understanding
the complex dynamics of educational quality and could be used as guidance for policymakers and
educators aiming to improve educational outcomes worldwide.
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Funders
Funding agency
Fundação para a Ciência e a Tecnologia
Funding programme
Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Base
Funding Award Number
UIDB/05064/2020