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- Advancing the understanding of pupil size variation in occupational safety and health: A systematic review and evaluation of open-source methodologiesPublication . Ferreira, Filipa; Ferreira, Simão; Mateus, Catarina; Rocha, Nuno; Coelho, Luís; Rodrigues, MatildePupil size can be used as an important biomarker for occupational risks. In recent years, there has been an increase in the development of open-source tools dedicated to obtaining and measuring pupil diameter. However, it remains undetermined determined whether these tools are suitable for use in occupational settings. This study explores the significance of pupil size variation as a biomarker for occupational risks and evaluates existing open-source methods for potential use in both research and occupational settings, with the goal of to prevent occupational accidents and improve the health and performance of workers. To this end, a two-phase systematic literature review was conducted in the Web of Science™, ScienceDirect®, and Scopus® databases. For the relevance of monitoring pupil size variation in occupational settings, 15 articles were included. The articles were divided into three groups: mental workload, occupational stress, and mental fatigue. In most cases, pupil dilation increased with workload enhancement and with higher levels of stress. Regarding fatigue, it was noted that an increase in this condition corresponded with a decrease in pupil size. With respect to the open-source methodologies, 16 articles were identified, which were categorized into two groups: algorithms and software. Convolutional neural networks (CNN)1 have exhibited superior performance among the various algorithmic approaches studied. Building on this insight, and considering the evaluations of software options, MEYE emerges as the premier open-source system for deployment in occupational settings due to its compatibility with a standard computer webcam. This feature positions MEYE as a particularly practical tool for workers in stable environments, like those of developers and administrators.
- Affinity coefficient for clustering autoregressive moving average modelsPublication . Nascimento, Ana Paula; Oliveira, Alexandra; Faria, Brígida Mónica; Pimenta, Rui; Vieira, Mónica; Prudêncio, Cristina; Nicolau, Helena BacelarIn various fields, such as economics, finance, bioinformatics, geology, and medicine, namely, in the cases of electroencephalogram, electrocardiogram, and biotechnology, cluster analysis of time series is necessary. The first step in cluster applications is to establish a similarity/dissimilarity coefficient between time series. This article introduces an extension of the affinity coefficient for the autoregressive expansions of the invertible autoregressive moving average models to measure their similarity between them. An application of the affinity coefficient between time series was developed and implemented in R. Cluster analysis is performed with the corresponding distance for the estimated simulated autoregressive moving average of order one. The primary findings indicate that processes with similar forecast functions are grouped (in the same cluster) as expected concerning the affinity coefficient. It was also possible to conclude that this affinity coefficient is very sensitive to the behavior changes of the forecast functions: processes with small different forecast functions appear to be well separated in different clusters. Moreover, if the two processes have at least an infinite number of π- weights with a symmetric signal, the affinity value is also symmetric.
- An integration of intelligent approaches and economic criteria for predictive analytics of occupational accidentsPublication . Gholamizadeh, Kamran; Zarei, Esmaeil; Yazdi, Mohammad; Rodrigues, Matilde A.; Shirmohammadi-Khorram, Nasrin; Mohammadfam, IrajOccupational accidents are a significant concern, resulting in human suffering, economic crises, and social issues. Despite ongoing efforts to comprehend their causes and predict their occurrences, the use of machine learning models in this domain remains limited. This study aims to address this gap by investigating intelligent approaches that incorporate economic criteria to predict occupational accidents. Four machine learning algorithms, Random Forest (RF), Support Vector Machine (SVM), Multivariate Adaptive Regression Spline (MARS), and M5 Tree Model (M5), were employed to predict occupational accidents, considering three economic criteria: basic income (BI), inflation index (II), and price index (PI). The study focuses on identifying the most suitable model for predicting the frequency of occupational accidents (FOA) and determining the economic criteria with the greatest influence. The results reveal that the RF model accurately predicts accidents across all income levels. Additionally, among the economic criteria, II had the most significant impact on accidents. The findings suggest that a reduction in FOA is unlikely in the coming years due to the increasing growth of II and PI, coupled with a slight annual increase in BI. Implementing appropriate countermeasures to enhance workers’ economic welfare, particularly for low-income employees, is crucial for reducing occupational accidents. This research underscores the potential of machine learning models in predicting and preventing occupational accidents while highlighting the critical role of economic factors. It contributes valuable insights for scholars, practitioners, and policymakers to develop effective strategies and interventions to improve workplace safety and workers’ economic well-being
- Application of CytoPath®easy vials in Cervical Cancer screening: Self‑sampling approachPublication . Fernandes, Sílvia P. M.; Vilarinho, Ana Sofia; Frutuoso, Amaro; Teixeira, Cidália; Silva, Regina Augusta A. P."CytoPath®Easy kit (DiaPath S.p.A.) offers a major advantage compared to other commercially available kits available for the screening of cervical cancer, as it does not require additional equipment for sample processing. Using this methodology, collected epithelial cells are immersed in a preservative liquid before setting as a thin layer on a slide via gravity sedimentation. Aims: To evaluate the suitability of the CytoPath®Easy kit for the processing of cervicalsamples, detection of pre‑neoplastic lesions, and nucleic preservation and extraction for HR‑HPV diagnosis. A total of 242 self‑sampled cervicalspecimens were utilized, with 192 collected in CytoPath®Easy vials and 50 collected and processed using the ThinPrepTM for comparative analysis. The samples underwent processing, Papanicolaou staining, and microscopic evaluation for morphological parameters. The extracted nucleic acids were assessed for purity and integrity, and the detection of high‑risk human papillomavirus (HR‑HPV) was carried out using the Alinitym HR HPV system kit (Abbott Laboratórios Lda). Both methods demonstrated effective performance, enabling the morphological assessment of the cervical epithelium. Statistical analysis indicated that ThinPrepTM yielded significantly better results in terms of cellularity. Conversely, CytoPath®Easy exhibited superior performance in terms of the quantity of extracted DNA and its degree of purification. Concerning the time consumed during processing, both methods were comparable, with the CytoPath®Easy methodology standing out for its cost‑effectiveness, as it does not necessitate additional instruments and consumables. The novel CytoPath®Easy methodology proves effective in preserving both nucleic acids and cell morphology characteristics, two crucial features for cervical cancer screening."
- Assessing work-related musculoskeletal disorders and psychosocial risks in bus drivers: Insights from a municipal company case study in PortugalPublication . Silva, Tânia T.; Mendes, Tatiana R.; Lapa, Inês; Carvalho, Paulo; Rodrigues, Matilde A.; Rodrigues, Matilde; Carvalho, PauloThe public transport sector plays a crucial role in society, oering essential services and providing employment to a significant number of drivers. Despite the importance of this sector, it is essential to recognize that drivers are exposed to various occupational risks inherent to their daily work, which can have serious implications for their health. This study aims to characterize and analyse Work-Related Musculoskeletal Disorders (WMSD) and psychosocial risks in a public transport company. In the initial phase of the study, a questionnaire was administered to assess musculoskeletal symptoms and psychosocial risks. In the second phase, an inertial motion capture system was used to evaluate the risk of developing WMSD. The results revealed a significant and concerning prevalence of burnout, with over 60% of workers reporting high or severe levels across all dimensions (i.e., personal, work-related, and client-related burnout). Depression, anxiety, and stress were within typical ranges, though a relevant percentage of participants exhibited severe and extremely severe levels of depression (7.2%), anxiety (12.2%), and stress (8%). Musculoskeletal discomfort was highly prevalent, particularly in the lower back (68.3%) and neck regions (57.2%), regarding pain over the last 12 months. Additionally, the risk of developing WMSDs was high across the various microtasks, which were analyzed across dierent bus lines and routes, with Rapid Upper Limb Assessment (RULA) scores ranging from 4 (Medium Risk) to 7 (Very High Risk). Based on the results, varying bus types and routes is recommended. Programs should enhance wellbeing, and studies should assess interventions on health, stress, and occupational risks focused on enhancing worker wellbeing should be implemented, and future studies should assess the impact of interventions targeting health, stress, and occupational risks.
- Betulinic acid for glioblastoma treatment: Reality, challenges and perspectivesPublication . Fernandes, Sílvia; Vieira, Mariana; Prudêncio, Cristina; Ferraz, RicardoBetulinic acid is a naturally occurring compound that can be obtained through methanolic or ethanolic extraction from plant sources, as well as through chemical synthesis or microbial biotransformation. Betulinic acid has been investigated for its potential therapeutic properties, and exhibits anti-inflammatory, antiviral, antimalarial, and antioxidant activities. Notably, its ability to cross the blood–brain barrier addresses a significant challenge in treating neurological pathologies. This review aims to compile information about the impact of betulinic acid as an antitumor agent, particularly in the context of glioblastoma. Importantly, betulinic acid demonstrates selective antitumor activity against glioblastoma cells by inhibiting proliferation and inducing apoptosis, consistent with observations in other cancer types. Compelling evidence published highlights the acid’s therapeutic action in suppressing the Akt/NFκB-p65 signaling cascade and enhancing the cytotoxic effects of the chemotherapeutic agent temozolomide. Interesting findings with betulinic acid also suggest a focus on researching the reduction of glioblastoma’s invasiveness and aggressiveness profile. This involves modulation of extracellular matrix components, remodeling of the cytoskeleton, and secretion of proteolytic proteins. Drawing from a comprehensive review, we conclude that betulinic acid formulations as nanoparticles and/or ionic liquids are promising drug delivery approaches with the potential for translation into clinical applications for the treatment and management of glioblastoma.
- Bioactive peptides from milk proteins with antioxidant, anti-inflammatory, and antihypertensive activitiesPublication . Borges, Thaís; Coelho, Pedro; Prudêncio, Cristina; Gomes, Ana; Gomes, Paula; Ferraz, Ricardo; Coelho, Pedro; Prudêncio, Cristina; Ferraz, RicardoPeptides from protein ingredients exhibit key biological activities, including antimicrobial, antihypertensive, antioxidant, anti-inflammatory, analgesic, and immunomodulatory effects. Aligning with the One Health approach, there is growing investment in promoting pet health and well-being. As a result, sustainable functional ingredients are increasingly essential for pet food development. In this work, peptides derived from lactoferrins of different mammalian species were synthesized and their antioxidant, anti-inflammatory, and antihypertensive activities were investigated. This study examined the antioxidant, anti-inflammatory, antihypertensive activities, and cytotoxicity of bioactive peptides derived from lactoferrins of various mammalian species through spectroscopical methods. The peptides were produced via chemical synthesis (bottom-up approach). Peptides derived from bovine lactoferrin showed the most promising antioxidant and anti-inflammatory activities, whereas those derived from human lactoferrin showed the highest antihypertensive effects and the lowest cytotoxicity. In short, milk-derived peptides with antioxidant, anti-inflammatory, and antihypertensive activity were identified. This motivates further studies to better characterize these peptides, including their properties and pharmacokinetics in vivo, to assess their true potential as nutraceutical agents.
- Challenges of learning human digital twin: case study of mental wellbeing: Using sensor data and machine learning to create HDTPublication . Vildjiounaite, Elena; Kallio, Johanna; Kantorovitch, Julia; Kinnula, Atte; Ferreira, Simão; Rodrigues, Matilde; Rocha, NunoHuman Digital Twin (HDT) is a powerful tool to create a virtual replica of a human, to be used for example for designing interactions with physical systems, preventing cognitive overload, managing human capital, and maintaining a healthy and motivated workforce. Building human twins is a challenging task due to the need to reliably represent each corresponding human being, and the fact that human beings notably differ from each other. Therefore, relying solely on expert knowledge is insufficient, and human twins must learn the specifics of each individual in order to accurately represent them. This paper focuses on AI methods for modelling the mental wellbeing of knowledge workers because the mounting cognitive demands of both white-collar and blue-collar work lead to employees’ stress, and stress leads to diminished creativity and motivation, increased sick leaves, and in severe cases, accidents, burnouts, and disabilities. This paper describes the main building blocks of AI-based detectors of mental stress and highlights the main challenges and future directions of research., which are expected to be relevant also for HDT learning in other domains because the high degree of individuality is ubiquitous in all human activities.
- Competências de escrita manual e processamento sensorial em crianças dos 6 aos 7 anos e 11 mesesPublication . Oliveira, Ana Sofia Sousa; Reis, Helena Silva; Reis, Claúdia Sofia Góis Ribeiro SilvaNeste estudo, investigou-se a relação entre o processamento sensorial e as competências de escrita manual em crianças de 6 a 7 anos e 11 meses, integradas no ensino regular. A amostra incluiu 191 crianças, avaliadas com o Questionário das Competências de Escrita Manual, desenvolvido e validado especificamente para este estudo, e a Sensory Processing Measure (SPM) – Forma Sala de Aula.
- Cone beam CT (CBCT) in radiotherapy: Assessment of doses using a pragmatic setup in an international settingPublication . Djukelic, Mario; Sá, Ana CravoThe imaging modality kV CBCT on linear accelerators (linacs) is utilised to verify positioning and anatomy in cancer patients undergoing radiotherapy treatment. There is a need for optimisation of radiological protection in kV CBCT imaging protocols to avoid unnecessarily high exposures to normal tissues surrounding the target. A network of ICRP mentees from 23 countries were surveyed for available dosimetry equipment. Standardised measurements on CBCT linac imaging systems were conducted using a cone beam dose index (CBDI) devised as a straightforward measurement for wide beam doses. Measurements were made with (a) 100 mm ionisation chambers or (b) 0.6 cc Farmer ionisation chambers and cylindrical CT PMMA phantoms, and (c) an alternative setup of Farmer chambers and cubical phantoms comprised of slabs of water equivalent material readily available in radiotherapy centres. The measurements were compared with Monte Carlo (MC) simulations. The survey showed limited availability for the reference setup using 100 mm chambers and CT phantoms. Correction factors were derived to convert normalised CBDI from alternative setups to the reference setup and are on average within 2% of MC simulations. The slab phantom in combination with a Farmer chamber provides an alternative to quantify CBCT radiation dose indices from linac-based image-guided radiotherapy using materials accessible in most centres worldwide. A method is presented to use correction factors for Varian Truebeam linacs if traditional 100 mm chambers and cylindrical CT phantoms are not available. This will enable most radiotherapy centres across the world to engage in meaningful imaging dose measurement and optimisation.