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Chestnut burrs as a sustainable source of cellulose for Pickering emulsion stabilisers
No full textAs the global population grows, increasing food consumption drives a significant rise in agri-food waste. In the northern Tras-os-Montes region of Portugal, one of the world's largest chestnut producers, this waste includes valuable by-products such as chestnut burrs, which are composed of 63% cellulose. This study aims to valorise chestnut burrs by extracting compounds for incorporation into high-added-value products. Cellulose was extracted through physical and chemical pre-treatments, alkali hydrolysis and bleaching. The process parameters were adjusted to enhance the extracted cellulose content and purity. Extracts were characterised by thermogravimetry and Fourier Transform Infrared Spectroscopy, and parameters such as particle size, zeta potential and wettability were also assessed and compared with commercial microcrystalline cellulose. Temperature was identified as the key parameter in alkali hydrolysis, with optimal conditions obtained for 10% NaOH at 100 degrees C for 1 h and a biomass-to-solvent ratio of 1:20 g/mL. Bleaching under optimal conditions (2% NaClO at 35 degrees C) removed an additional 7% lignin and enhanced the whiteness of the final product. The cellulose obtained has a purity of 72%, with a particle size of 55 mu m, a negative surface charge, hydrophilic behaviour, an estimated molecular weight of 13.2 kDa, and a crystallinity of 56.5%. When applied at 0.8 wt% of the aqueous phase in 20:80 oil-in-water emulsions, these particles stabilise Pickering emulsions with a 12 mm average droplet size, remaining stable for at least 30 days. These findings demonstrate that chestnut burrs are a viable and sustainable source of cellulose with high potential as a natural Pickering emulsion stabiliser for use in food, cosmetics, and pharmaceuticals.This work is financially supported by the Promove Programme through Fundação “La Caixa”, in collaboration with the BPI and Fundação para a Ciência e a Tecnologia (FCT), under the project CyChest - Gestão integrada do ciclo do castanheiro no Parque Natural de Montesinho. This work was also financially supported by Fundação para a Ciência e a Tecnologia, I.P. /MCTES through national funds: LSRE-LCM, UID/50020/2025; and ALiCE, LA/P/0045/2020 (DOI: 10.54499/LA/P/0045/2020); CIMO, UIDB/00690/2020 (DOI: 10.54499/UIDB/00690/2020) and UIDP/00690/2020 (DOI: 10.54499/UIDP/00690/2020) and LA SusTEC, LA/P/0007/2021 (DOI:10.54499/LA/P/0007/2020). Andreia Ribeiro acknowledges the FCT for their research contract through the individual CEEC – Stimulus of Scientific Employment (DOI: 10.54499/2022.00798.CEECIND/CP1733/CT0009)
Benefits and Ethical Implications of Using Generative AI in PhD Students' Research Activities
Full text linkHigher education is going through a phase of constant transformation, especially in the use of generative AI by its students from the most varied study cycles. This has brought several benefits, but also ethical implications, particularly in research activities. Thus, with the development of the research we intend to obtain answers to the following research question: What are the benefits and ethical implications of using generative AI in the research activities of doctoral students? To answer this question, we conducted exploratory and descriptive research, as we explored the use of AI and described its impact on the research activities of doctoral students at a university in Mozambique. As a data collection tool, we applied a questionnaire survey to all the students in the two postgraduate courses at the respective university. A total of 117 students from both courses responded to the study, 61 of which were validated, which shows that the response rate was more than half, at 52.16% of the total sample. The results show that there are several benefits, but also ethical implications that must be considered in the research activities of doctoral students and which are crucial to guarantee the quality, transparency, and fairness of the teaching-learning process.This work has been supported by FCT\u2014Funda\u00E7\u00E3o para a Ci\u00EAncia e Tecnologia within the Project Scope: UIDB/05777/2020 (https://doi.org/10.54499/UIDB/05777/2020)
A deep learning approach for average height estimation in oak colony using rgb images
Full text linkMany strategies have been developed to monitor the volume of volume of Above Ground Biomass (AGB) in forest areas as a fundamental step for managing carbon concentration. This study explores the use of use of Light Detection and Ranging (LiDAR) data obtained through Unmanned Aerial Vehicles (UAVs) to estimate height values in a vegetation colony composed of oaks (Quercus pyrenaica Willd.) in northern Portugal. The extraction of pertinent information from LiDAR data was facilitated by using the LAStools extension within the Quantum Geographic Information System (QGIS) software framework. The generated raster and image information were used to calculate the height values of the vegetation. Following this extraction, the information was meticulously organized into datasets, which were then employed in Deep Learning (DL) algorithms. The VGG16 model was selected as the underlying framework for the present study. Height predictions were made using dimensions of 16× 16, 32× 32, and 64 × 64 pixels for the Red, Green and Blue (RGB) images. The data was estimated and compared using both the standard format of the VGG16 model and a superficially adapted version of its convolution layers. The algorithm’s efficacy was validated by comparing the forecast results with the data obtained from QGIS, which revealed minimal discrepancies. It was observed that using 64× 64 pixel scale images yielded enhanced accuracy, resulting in reduced values for the Mean Absolute Error (MAE). The study demonstrates the viability of applying DL techniques to accurately capture information about a forest area using RGB images.This study was funded by iCarbono project Fundação La Caixa (PL23-00038) and LIFE SILFORE project (LIFE21-CCA-ES-LIFE). The authors are also grateful to CeDRI (UID/05757), SusTEC (LA/P/0007/2021), CIMO (UIDP/00690/2020), CEFET-MG and the National Council for Scientific and Technological Development – CNPq, related to project 442696/2023-0
Percepciones de los docentes universitarios sobre la enseñanza- aprendizaje de una lengua extranjera durante el confinamiento
Full text linkLa pandemia provocada por el COVID-19 en marzo del 2020, tuvo un impacto significativo en la sociedad, viéndose alterada la vida de la población en los ámbitos familiar, profesional, académico y social. En Portugal, como en muchos otros países del mundo, las medidas de contención implementadas para disminuir la propagación del virus y reducir los niveles de contagio se centraron en restringir el contacto comunitario a través del confinamento obligatorio y el aislamiento social.info:eu-repo/semantics/publishedVersio
A perspetiva dos alunos do ensino superior sobre a IA na pesquisa
Full text linkActualmente, a inteligência artificial (IA) apresenta um crescimento acelerado em todo o mundo, impactando diversos sectores da sociedade — incluindo, de forma marcante, o
sector da educação. Em particular, destaca-se o avanço da IA generativa, caracterizada pela capacidade de criar conteúdos, como textos, imagens, música, áudio e vídeos. Esta
investigação tem como objectivo principal analisar o nível de utilização da IA por parte dos estudantes de doutoramento da Faculdade de Educação e Comunicação da Universidade Católica de Moçambique. A partir desta análise, procura-se compreender os impactos concretos da IA no contexto académico moçambicano, especialmente no que diz respeito à produtividade científica e ao desenvolvimento de competências investigativas. Para a obtenção de respostas ao objectivo definido adotou-se a metodologia de estudo de caso. A investigação é de natureza mista – quantitativa e qualitativa – e os dados foram recolhidos na comunidade académica através da aplicação de um inquérito por questionário aos alunos do terceiro ciclo de estudo da instituição. Os resultados sugerem que os alunos apresentam níveis de utilização de um conjunto de ferramentas de IA generativa no desenvolvimento das suas aprendizagens, pelo que se evidencia que existe de facto um impacto crescente do uso destas ferramentas em contexto académico, em diferentes dimensões do processo de ensino-aprendizagem.Currently, artificial intelligence (AI) is experiencing rapid growth worldwide, impacting various sectors of society, including, notably, the education sector. In particular, the advancement of generative AI stands out, characterized by its ability to create content such as text, images, music, audio, and videos. The main objective of this research is to analyze the level of AI use by doctoral students at the Faculty of Education and Communication of the Catholic University of Mozambique. Based on this analysis, we seek to understand the concrete impacts of AI in the Mozambican academic context, especially on scientific productivity and the development of research skills. To obtain answers to the defined objective, a case study methodology was adopted. The research is mixed in nature—quantitative and qualitative— and data will be collected in the academic community through a questionnaire survey of students from 3rd study cycle at the institution. Preliminary results suggest that students use a set of generative AI tools in their learning, showing that there is indeed a growing impact of the use of these tools in the academic context, in different dimensions of the teachinglearning
process
Literacia, qualidade de vida e saúde oral do idoso
No full textO envelhecimento populacional carateriza a demografia das nações, constituindo-se como uma realidade que requer a organização e a intervenção estratégica dos
governos e das entidades de saúde, por forma a responder aos desafios que este fenómeno significa (WHO, 2017). Ainda que a um ritmo mais lento e de forma desigual
entre países, a população mundial continua a crescer.Contudo, a quase totalidade das
nações conhece o envelhecimento populacional que caminha a par com a diminuição
da taxa de fertilidade, pelo que num futuro próximo haverá uma inversão da curva
populacional global (United Nations - Department of Economic and Social Affairs
Population Division, 2019a). Portugal assiste a mudanças na estrutura populacional,
sendo estas a objetivação da redução das taxas de natalidade e de fecundidade e do
prolongamento da vida dosidososresultante dos progressos científicos e tecnológicos
do mundo moderno (WHO, 2015). No entanto, ainda que o envelhecimento represente o enriquecimento do indivíduo e da sociedade, é imperioso garantir a melhor
saúde possível na velhice por forma a alcançar o desenvolvimento sustentável e a oferecer aos idosos a qualidade de vida que lhes é devida (WHO, 2017).info:eu-repo/semantics/publishedVersio
A cloud-driven support layer for enhancing distributed IDS in IoT networks
No full textThe exponential growth of connected devices, including sensors, mobile equipment, and various Internet of Things (IoT) nodes, has significantly increased the volume of data generated at the edge. Traditionally, data analysis tasks are offloaded to centralized cloud servers, resulting in increased latency, bandwidth bottlenecks and privacy concerns. While edge computing addresses these limitations by enabling local processing, it also faces challenges related to limited computational capacity and isolated decision-making. In this context, Multi-Agent Systems provide a promising solution by enabling collaboration among edge nodes for distributed machine learning-based intrusion detection. This work extends previous research by introducing a hierarchical approach within the edge-cloud continuum, where agents deployed in the cloud continuously monitor edge-level behaviour and employ reinforcement learning techniques to suggest dynamic updates to decision parameters of edge agents. This feedback-driven mechanism allows agents to adapt their behaviour over time, improving detection accuracy and collaboration efficiency while keeping communication overhead under control. The proposed architecture balances decentralisation and adaptability, offering a scalable and privacy-preserving solution for intrusion detection in dynamic and resource-constrained IoT environments.Open access funding provided by FCT|FCCN (b-on). This work has been supported by national funds through FCT/MCTES (PIDDAC): CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499/UIDP/05757/2020); and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020). This work has been also supported and received funding from “CyberPRAISE - Cybersecurity research for PRivAte, Intelligent and truStablE solutions” - NORTE2030-FEDER-01820300. The author Gustavo Funchal thanks the FCT Portugal for the PhD Grant 2022.13712.BD
The dark side of technology when addressing overtourism: A critical overview
No full textThis chapter aims to provide an overview on the relationship between overtourism and technology, shedding light on the perverse effects of technology when addressing overtourism. An exploratory study was adopted because one should move away from the formal testing of hypotheses and attempt to analyse the key issues around the core concepts we are concerned with, i.e., the dark side of technology when addressing overtourism and its links to theory. The aim of this chapter is, therefore, to take a broader look at this thematic, and thus broaden the discussion around this topic. Results point out the fact that, although technology can be used to better manage overtourism, it is also linked to fashion trends, and several tourism destinations find themselves promptly overbooked in result. The originality of this chapter lies in the fact that unlike other studies, this research focuses on uncovering the dark side of technology, which has generally been promoted as the ideal tool to mitigate the impacts of overtourism. This critical overview might help both scholars and practitioners to reflect on and/or rethink how technology is really helping the destinations to overcome the challenges that come with overtourism
Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis
No full textIt is well known that the fastest elite marathon runners come from East African countries such as Ethiopia and Kenya. However, to date, there is no information available on the origin of the fastest age group (master) marathoners. This study aimed to determine the countries of origin of the fastest age group marathoners who have participated in the 'New York City Marathon' over the past several decades. Race data from 1,009,839 runners (626,183 male and 383,656 female finishers) who completed the 'New York City Marathon' between 1999 and 2024 were analyzed. Participants were categorized into five-year age groups: <20, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, and 75 + years. The data were stratified by sex (male and female) and country of origin. The dataset was organized into five performance-based subgroups: (i) the entire dataset, including all finishers by age group and nationality; (ii) the top 100 finishers per age group; (iii) the top 30 finishers per age group; (iv) the top 10 finishers per age group; and (v) the top individual from each country within each age group. Regression analyses were conducted to explore demographic predictors of marathon performance. Participation generally increased over the study period, with temporary declines during the COVID-19 pandemic; male participation consistently outnumbered female participation, the 40-44 years age group was the most represented for both sexes, and participation was lowest in the youngest (< 20 years) and oldest (75 + years) age groups. Crucially, analyses focusing on the fastest age-group marathoners revealed clear nationality-based performance patterns. In younger adult age groups (20-39 years), the fastest average race times were predominantly achieved by female and male runners from Kenya and Ethiopia. The < 20 years age category showed comparatively stronger performances from European runners, including those from Poland, Switzerland and Italy. In the 50 years and older age groups, the best average times were increasingly recorded by runners from the United States of America, Japan, Germany and Switzerland. This shift highlights a regional transition in peak marathon performance with increasing age, from East African to European, North American, and East Asian dominance
Fire resistance of protected glued laminated timber columns: geometry, load and cladding effect
No full textTimber, as a sustainable and renewable building material, is becoming increasingly popular in modern architecture due to its aesthetic appeal, low environmental footprint, and structural ability. Glued-laminated timber (GLT) is commonly used for columns and beams in mid to high-rise buildings due to its strength and spanning ability. However, concerns about timber's combustibility raise safety concerns that demand the use of effective fire protection materials. One such method is the application of gypsum cladding, which provides thermal insulation and delays heat transfer to the timber, thus enhancing fire resistance. This study investigates the fire resistance of gypsum-protected GLT columns, focusing on the effects of geometry, load level, and cladding configuration. The European Charring Model (ECM) and the effective cross-section design method are used alongside with three experimental tests, full three-dimensional computational model and a parametric study. The results provide valuable insights into the thermal insulation performance of gypsum cladding, the charring behaviour of timber under fire, and the influence of different protection layers and load levels on overall fire performance. Under 36 % load level, doubling the protection layer, increases the fire resistance up to 95 %. Changing the material grade from GL24h to GL28h, increases the fire resistance, from 2 % to 12 %, depending on the slenderness of the column, while increasing the load level from 6 % to 36 % reduces the fire resistance up to 47 %. This research contributes to fire safety and supports the expanded use of engineered timber in sustainable building designs by improving knowledge of its fire performance characteristics.None