• Covilhã, Portugal
Recent publications
Two common defects in induction machines (IMs) are eccentricity and interturn faults, which should be diagnosed to prevent performance degradation and further damage. A popular fault-detection approach is the current signature analysis (CSA), because of its simplicity and non-intrusiveness. Under closed-loop control, it is combined with analogous voltage-reference (VR) signature analysis (VRSA). However, by using these methods in three-phase IMs it is difficult to discriminate between these faults, which cause similar symptoms. Multiphase machines provide remarkable advantages such as inherent tolerance to open-phase faults. Six-phase IMs are particularly attractive since they allow adopting three-phase converters. Among them, those with symmetrical spatial arrangement of the stator phases offer superior fault tolerance. Nonetheless, the distinction between eccentricity and interturn failures in these IMs has not been addressed so far. This paper studies the discrimination between eccentricity and interturn faults in symmetrical six-phase (S6) IMs by CSA or VRSA. It is shown that, conversely to three-phase IMs and most other multiphase IMs, in S6 ones these two types of failures can be easily distinguished: interturn faults considerably alter the currents or VRs in the so-called $\bm {x}$ - $\bm {y}$ plane, whereas eccentricity leads to current/voltage symptoms only in the $\bm {\alpha _{1}}$ - $\bm {\beta _{1}}$ plane. Experimental results confirm the theory.
Objective To describe the quality of clinical records of deliveries and births by quantitative assessing the unfilled variables in birth data collection forms and their implications at Maternity Hospital, in the municipality of Lubango, Angola. Method The study was conducted from January to August 2018. It adopted a quantitative research design, analysed variables not filled in a total of 202 birth record forms collected for 3 months (secondary data). Results The findings revealed that 80% of the sections of the entire set of information about obstetrical history were not filled in. This occurred with a relatively high frequency resulting in some of the relevant variables being left blank, such as antenatal diagnosis (94%) and the number of last menstruation (91%). Conclusions The rate of missing fundamental information from the clinical birth record are high. This result has important implications in evaluating the quality of data and may, consequently, jeopardize: 1) the evaluation of the prenatal assistance, 2) the clinical assistance at delivery, and 3) decision-making for preventive and intervening procedures.
The Earth is a dynamic planet, where earthquakes and volcanoes are among some of its most outstanding expressions. Just like our planet as a whole is subject to lunisolar gravitational tides, seismic and volcanic activity are also influenced by the relative motion of the Sun and Moon. This tidal influence takes different forms, spanning different spatial and temporal scales, from quasiperiodic patterns with semidiurnal to multiannual periods to the triggering of earthquakes and volcanic eruptions. Tidal stresses have been primarily evoked as driving forces, although they are 3–5 orders of magnitude smaller than tectonic stresses, which makes cause-effect relationships elusive. This chapter reviews the different observations of tidal influence in geophysical and geochemical data acquired in tectonic and volcanic settings, as well as the methods that have been developed to detect it. Using case studies, we provide some insights on the sensitivity of geological systems to tidal stresses.
One of the earliest signs of diabetic retinopathy is the appearance of small and round red dots in retinal fundus images, known as microaneurysms. Microaneurysms automatic detection is a challenging task due to their small and subtle nature. In this paper, a new multi-scale algorithm developed for the automatic detection of microaneurysms in retinal fundus images is proposed. The proposed method is divided into three stages, namely, image pre-processing, microaneurysm candidates detection and retinal vessels detection, and labelling of the microaneurysm candidates. Apart the initial image pre-processing, all stages of the algorithm are designed using a multi-scale framework, providing the mechanism for the effective microaneurysms detection. Four publicly available databases are used for performance evaluation. The proposed method proves to be competitive against other state-of-the-art approaches in microaneurysms detection and diabetic retinopathy detection.
The combination between online social networks (OSN) and decision processes provides a favorable social data analysis paradigm for efficient decision support and business-processes integration. This paper presents a framework for handling OSN’s contents, providing a simpler and effective approach for information retrieval and processing. The objective is to address a decision-making problem, by using that framework to extract, process, structure and analyze the OSN’s data. The decision process is not only guided by OSN data, but also by social network analysis methodology and is entirely based on the communications among social media users. Our framework combines two different, though complementary, perspectives: the analysis of the interactions among users and the semantic analysis of their discourses. In addition, it aims to bridge technology and manual-based approaches, thus enhancing the possibilities for making a better use of an OSN, using free-available software. The case study, herein, aims to estimate customers’ requests, solely based on their Facebook posts, showing that the unstructured data of the web’s discourse can be used to support this kind of decision processes.
Online social networking platforms allow people to freely express their ideas, opinions, and emotions negatively or positively. Previous studies have examined sentiments on these platforms to study their behavior in different contexts and purposes. The mechanism of collecting public opinion information has attracted researchers to automatically classify the polarity of public opinions based on the use of concise language in messages, such as tweets, by analyzing social media data. In this paper, we extend the preceding work where an unsupervised approach to automatically detect extreme opinions/posts in social networks is proposed. The performance of the proposed approach is evaluated on five different social network and media datasets. In this work, we use a semi-supervised approach known as BERT to reevaluate the accuracy of our prior approach and the obtained classified dataset. The experiment proves that in these datasets, posts that were previously classified as negative or positive extreme are extremely negative or positive in many cases while using BERT. Furthermore, BERT shows the capability to classify the extreme sentiments when fine-tuned with an appropriate extreme sentiments dataset.
Background Sustainable production and consumption are two important issues, which mutually interact. Whereas individuals have little direct influence on the former, they can play a key role on the latter. This paper describes the subject matter of sustainable consumption and outlines its key features. It also describes some international initiatives in this field. Results By means of an international survey, the study explores the emphasis given to sustainable consumption during the second wave of the COVID-19 pandemic, and the degree of preparedness in individuals to engage in the purchase of green and sustainably manufactured products. The main results indicate that the pandemic offered an opportunity to promote sustainable consumption; nevertheless, the pandemic alone cannot be regarded as a ‘game changer’ in this topic. Conclusions Apart from an online survey with responses from 31 countries, which makes it one of the most representative studies on the topic, a logit model was used to analyse the main variables that affect the probability of pro-environmental consumption behaviour because of the COVID-19 pandemic. The paper lists some of the technological and social innovations that may be needed, so as to guide more sustainable consumption patterns in a post-pandemic world.
Plant-based diets are often promoted as healthier and more sustainable and thus as a mechanism to achieve the targets proposed to mitigate climate change and noncommunicable diseases. However, plant-based diets can be perceived as more expensive than the common omnivorous diets, when considering the expensive novel meat substitutes and also the higher costs of fruits and vegetables, whose consumption is perceived to increase. Therefore, the present study assesses the question: Do plant-based consumers spend more on food compared to omnivorous consumers? Based on primary data ( n = 1040) collected through an online survey, representative of the Portuguese population, through logistic regressions, it was possible to conclude that plant-based consumers, particularly vegan, are associated with lower food expenditures compared to omnivorous consumers. In fact, plant-based consumers are shown to spend less than all other consumers assessed. Food policies aligning healthiness and sustainability with affordability can deliver a major boost for the promotion of plant-based diets and help achieve the mitigation targets proposed.
Background This paper presents a review of the literature and trends related to social values and sustainable development and describes a set of case studies from a variety of community-based projects which illustrate the advantages that social values bring about as part of efforts to promote sustainability. Three approaches were used to develop this study: a bibliometric analysis of the topic “social values and sustainable development”, an analysis of case studies that concretely present community projects addressing social values and sustainability, and the development of a framework linking up bibliometric clusters and the cases studies. Results While the bibliometric analysis revealed clusters where social values are strongly connected with sustainable development, the case studies indicated the lack of a common terminology and understanding of the relation between social values, sustainable development, and community-based projects. Conclusions The study concludes by suggesting a set of measures that could be deployed to better take social values into account when planning policies or making decisions related to community projects.
Rapid population growth and urbanization have a strong impact on individuals' well-being. These trends are currently important topics in city management. As a significant driver of digitalization, technological development has been found to have great potential as a mitigator of a wide range of issues that cities face. To ensure the available technologies are being correctly used, municipalities need to measure their degree of digitalization. This assessment is also important to improve city officials' understanding of areas that need interventions so that cities can be managed better and provide their residents with a better quality of life. This study applies the baseline principles of the multiple-criteria decision analysis (MCDA) approach to develop a decision-support system that facilitates urban digitalization evaluations. The results rely on insights provided by a panel of experts in this area, who used cognitive mapping and the best worst method (BWM) to identify important evaluation criteria within urban digitalization and to analyze their cause-and-effect relationships. The final outcomes were validated by the panel members and representatives of the Associação Nacional de Municípios Portugueses (i.e., National Association of Portuguese Municipalities) and the Agência National de Inovação (i.e., National Innovation Agency). These specialists confirmed that the evaluation system developed facilitates city differentiation in key areas of urban digitalization. The advantages and limitations of the proposed procedures are also discussed.
In this paper, we consider switched systems that allow discontinuous jumps in the state when switching occurs. In particular we analyze the case where these jumps are dictated by a state reset rule. We show that it is possible to study the state trajectories of a switched system with state reset by means of some switched systems without state resets, i.e., with continuous state trajectories. We establish some sufficient conditions for stability of switched systems with state reset using the associated systems without reset. The obtained results are used in numerical examples to show the effectiveness of the proposed approach.
Background Cataracts are lens opacifications that are responsible for more than half of blindness cases worldwide, and the only treatment is surgical intervention. Phacoemulsification surgery, the most frequently performed cataract surgery in developed countries, has associated risks, some of which are related to excessive phacoemulsification energy levels and times. The protocol proposed in herein will be used to evaluate the feasibility of a new experimental medical device, the Eye Scan Ultrasound System (ESUS), for the automatic classification of cataract type and severity and quantitative estimation of the optimal phacoemulsification energy. Methods The pilot study protocol will be used to evaluate the feasibility and safety of the ESUS in clinical practice. The study will be conducted in subjects with age-related cataracts and on healthy subjects as controls. The procedures include data acquisition with the experimental ESUS, classification based on the Lens Opacity Classification System III (LOCS III, comparator) using a slit lamp, contrast sensitivity test, optical coherence tomography, specular microscopy and surgical parameters. ESUS works in A-scan pulse-echo mode, with a central frequency of 20 MHz. From the collected signals, acoustic parameters will be extracted and used for automatic cataract characterization and optimal phacoemulsification energy estimation. The study includes two phases. The data collected in the first phase (40 patients, 2 eyes per patient) will be used to train the ESUS algorithms, while the data collected in the second phase (10 patients, 2 eyes per patient) will be used to assess the classification performance. System safety will be monitored during the study. Discussion The present pilot study protocol will evaluate the feasibility and safety of the ESUS for use in clinical practice, and the results will support a larger clinical study for the efficacy assessment of the ESUS as a diagnostic tool. Ultimately, the ESUS is expected to represent a valuable tool for surgical planning by reducing complications associated with excessive levels of phacoemulsification energy and surgical times, which will have a positive impact on healthcare systems and society. The study is not yet recruiting. Trial registration ClinicalTrials.gov identifier NCT04461912, registered on July 8, 2020.
The aim of this study was to: (i) characterise the stroke kinematics’ stability of the male swimmers competing in the four 50 m events at the 2021 European Championships, and; (ii) understand the speed–time relationship in the four race events. All male swimmers who participated in the 50 m events (backstroke: 78 swimmers; breaststroke: 79 swimmers; butterfly: 89 swimmers; freestyle: 95 swimmers) were evaluated. In each swimming stroke swimmers were split in two groups (better and poorer performances). Significant variances (p < 0.05) were observed in both groups in all variables and for all swimming strokes. Swimming speed was the variable with the highest variance in both groups and strokes. Overall, better swimmers presented a low to high normative stability, and poorer swimmers a moderate-to-high. Speed–time curve fitting for all swimming strokes and groups suggested a cubic relationship. It can be considered that elite male swimmers racing 50 m sprint events at major competitions present an all-out trend. The present data provide coaches with substantial information about the main trend in the 50 m sprint events, specifically in each section of the race.
Apart from the many social and health problems it has caused, the COVID-19 pandemic has had a severe impact on most sectors of the economy worldwide. One of the areas where such impact is noticeable is the textile, apparel, and fashion (TAF) industry. The lockdowns and limited access to retailer outlets resulted in a considerable drop in consumption, creating problems related to the excess of stock, the decrease of sales, and the disposal of non-used items. This paper outlines the implications of the COVID-19 on the TAF sectors and European retailers. It analyzes how the current supply chains exacerbated stock control problems, and it reports on the changes in consumption during the pandemic. The worldwide restrictive measures implemented to cope with the COVID-19 pandemic were responsible for significant profit losses. Also, the decrease in consumption, caused by several geographically wide lockdowns, prompted a subsequent reduction in orders and sales, resulting in a significant number of constraints. The implementation of more environmentally friendly processes, including sustainable circularity as a competitiveness source to keep the TAF sectors in the loop and reduce greenhouse gas emissions, may help address the problems associated with the COVID-19 pandemic in the sustainability context, as reported in this paper.
With the advancement of technology, different approaches to make teachers’ tasks more interactive and improve teacher teaching methodologies are becoming more and more common. Additionally, students must feel motivated and positively interact with these new methodologies. To understand these new initiatives, this paper aims to identify the adoption model of a game-focused student response system. To do so, the theoretical framework of the hedonic-motivation system adoption model was applied to Kahoot! which turns the classroom into a game show. For this purpose, a survey was designed, supported by a questionnaire administered to 214 students, applying a non-probabilistic convenience sampling to the students who decided to be evaluated by this method, together with the classic paper tests and the electronic tests on an e-learning platform. The results showed that the application of the hedonic motivation system adoption model is adequate for the adoption of a game-based student response system tool, and all relationships were significant except those related to the Temporal Dissociation variable. The results of this research can help the education sector to have a better acceptance of these kinds of tools in the classroom, and a better understanding of their functionalities. In general, the results of the present study contributed to the literature by identifying the important role of a game-based student response system tool in education.
Rink hockey is a highly specialized and physiological demanding sport with sparse research regarding the game and athletes' characteristics. A cross-sectional study was developed to characterize the body composition and grip strength of elite male rink hockey players and to establish the relationship between ethnicity on body composition and grip strength. A sample of 100 elite rink-hockey athletes aged 26.59 ± 6.02 participated in the study, comprised of 69 Caucasian male adults aged 27.58 ± 6.44 years and 31 Black African male adults aged 24.39 ± 4.27. Body composition was assessed by anthropometric measurements. Static grip strength was assessed with an adjustable dynamometer. Multiple regression analysis was applied to understand which variables constraints body fat percentage (BF) and grip strength. Body mass showed an average of 76.36 ± 9.18 kg for 175.80 ± 5.87 cm of height and BF% of 10.82 ± 5.07%. Maximal right grip strength was 50.91 ± 6.26 kg and 50.27 ± 6.23 kg for left grip strength. Four predictors accounted for 70.01% of the variance of BF%: abdominal circumference (p < 0.001), right thigh circumference (p < 0.001), right calf circumference (p = 0.001) and ethnicity (p = 0.016). Three predictors accounted for 13.1% of the variance of right grip strength: ethnicity (p = 0.013), chronological age (p = 0.024) and right distal thigh circumference (p = 0.014). Results suggest that elite rink hockey athletes have a specific anthropometric identity, which at the elite level may lead to reduced body fat and greater handgrip strength. Ethnicity seems to predict body fat and grip strength in elite rink hockey athletes.
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