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Considering the context of functional data analysis, we developed and applied a new Bayesian approach via the Gibbs sampler to select basis functions for a finite representation of functional data. The proposed methodology uses Bernoulli latent variables to assign zero to some of the basis function coefficients with a positive probability. This procedure allows for an adaptive basis selection since it can determine the number of bases and which ones should be selected to represent functional data. Moreover, the proposed procedure measures the uncertainty of the selection process and can be applied to multiple curves simultaneously. The methodology developed can deal with observed curves that may differ due to experimental error and random individual differences between subjects, which one can observe in a real dataset application involving daily numbers of COVID-19 cases in Brazil. Simulation studies show the main properties of the proposed method, such as its accuracy in estimating the coefficients and the strength of the procedure to find the true set of basis functions. Despite having been developed in the context of functional data analysis, we also compared the proposed model via simulation with the well-established LASSO and Bayesian LASSO, which are methods developed for non-functional data. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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This article aims to identify the perception of a group of incubated projects about the importance of entrepreneurship as alternative to face the economic crisis due to the new coronavirus pandemic. Entrepreneurship is a transversal subject to many areas of research and has been the object of study within themes such as economic, technological and innovation. The crisis in several sectors caused by the pandemic of the new coronavirus, raised other research possibilities. With a qualitative approach and through the case study method, using a structured questionnaire, it sought to investigate a group of companies/projects incubated ina technology-based business incubator, in the municipality of Mossoro in the state of Rio Grande do Norte. With the results, it was possible to verify that incubated have a positive perception about the importance of entrepreneurship in facing the crisis, thus pointing out that it is an alternative for the post-pandemic crisis period.
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All over the world, especially in Brazil, the Covid-19 propagation crisis forced the Brazilian educational system to suspend classroom activities as one of the measures to prevent the new Coronavirus. In this sense, New Digital Information and Communication Technologies (NTDIC) such as the WhatsApp application have become a field of study as a didactic and accessible tool in the teaching-learning process. This article brings as an experience report the use of this application, in the realization by high school students integrated to the technical courses of Agribusiness, Electrotechnks and Mechatronics of the Federal Institute of Tocantins, about the evaluation activities through the shared production of dialogued audios. As a result, it was found that most students had satisfactory performance, above the minimum average of 6.0 (six) required by the institution, reinforcing the potential use of this application in the development of teaching and learning practices, even if still with some challenges and limitations during the process.
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In this paper, our goal is to analyze and compare cellular network usage data from Rio de Janeiro from pre-lockdown, during lockdown, and post-lockdown phases surrounding the COVID-19 pandemic to understand and model human mobility patterns during the pandemic, and to evaluate the effect of lockdowns on mobility. Our analysis reveals that human mobility increases significantly even before lockdown restrictions are eased, with the trend continuing in the post-lockdown period. We also observe that the day of week has a significant impact on mobility of individuals, with the overall mobility on Fridays increasing over time possibly due to people self-relaxing restrictions and engaging in social activities on Friday evenings. We also design an interactive tool that showcases mobility patterns in different granularities and can potentially help people and government officials understand the mobility of individuals and the number of COVID-19 cases in a particular neighborhood.
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The present study aimed to compare the impact of the COVID-19 pandemic among Physical Education professionals in the Northeast and South of Brazil. This is a cross-sectional study. Data collection took place digitally. Through Google® Forms, a questionnaire was created, with multiple choice questions disseminated through the social networks Whatsapp®, Instagram@ and Facebook@. A total of 746 participants answered the questionnaire, 50.8% from the South Region and 49.2% from the Northeast Region. Regarding education and professional activity, most had graduated for up to 10 years (59.5%), had a full degree or both (61.3%) and worked in the private/liberal professional sector (52%). Considering financial and health planning issues, most participants were the main household income provider (64.9%), had no financial reserve (75.9%), nor had a health plan (58.6 %) or retirement plan (67%). Regarding attitudes and risks in the face of the pandemic, 94.5% of Physical Education professionals said they were in isolation. It can be concluded that the effects of the Covid-19 pandemic had an impact on Physical Education professionals. The ban on professional practice caused by social isolation demonstrated a profession with little planning and a vulnerable financial situation regardless of the Brazilian region. © 2022 University of Beira Interior. All rights reserved.
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The virus responsible for the current COVID -19 pandemic is SARS-CoV-2, which has caused >400 million infections and >5 million deaths (as of February 2022). Despite vaccination efforts, there is still an urgent need to develop strategies to control infection and treat patients. One of the proteins bound to the viral membrane is the spike (S) protein, which consists of two subunits: S1, which contains a receptor-binding domain (RBD) responsible for binding to the host cell receptor, and S2, which facilitates membrane fusion between the viral and host cell membranes, previously published in: Jackson CB et al. (2018) Nat Rev Mol Cell Biol 23, 3-20. Thus, this protein is primarily responsible for the ability of the virus to enter host cells, making it one of the most promising therapeutic targets of coronavirus, previously published in: Cao L et al. (2020) Science 6515, 426- 431. The aim of this work was to design and produce antiviral proteins that could prevent the interaction between the two proteins and thus block infection by binding to the RBD region and blocking its interaction with the host receptor, angiotensin converting enzyme-2 (ACE2) protein. First, several antiviral proteins were computationally designed using the Rosetta program based on the interactions between ACE2 and the RBD. Next, six molecular dynamics simulations (MD) of 1 ls of three candidates were performed to test their interaction with the RBD. This was followed by experimental validation after expression and purification of the three candidates. The secondary structure and thermostability of these proteins were tested by far-UV circular dichroism spectropolarimetry. Surface plasmon resonance was used to evaluate the affinity of each candidate for RBD. Neutralization assays were performed to investigate the neutralization ability of the proteins. The experimental results show that one of the developed proteins is a promising therapeutic approach that will be further improved in the future.
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Introduction: Due to the covid-19 outbreak, cardiac rehabilitation programs (CRP) underwent most needed adaptions to stay operative. To face all the requests and guarantee sanitary measures, we reduced the duration of the program from about 12 weeks to about 8 weeks, so we could have smaller groups but still respond to all patients who had been referred. However, it is still unclear whether less hours of contact and exercise sessions can achieve the same results as traditional CRP. Objective: To analyse the effectiveness of shorter duration CRP on risk factor control and exercise tolerance after concluding the program. Methods: Observational single center study including two groups of patients who underwent CRP: one group who had been in 12 weeks-CRP before the pandemic sprout and another group enrolled in an 8-week program after April 2021. Albeit differences in their duration, both CRP had the same structure: observation by cardiologist, physiatrist, specialist nurse, exercise (aerobic and strength exercises) and educational sessions, as well as nutrition and psychologist consultation. Results: A total of 114 pts were analysed (mean age 62,4±11,6 years, 85.1% men, 86% with ischemic heart disease). Main comorbidities were hypertension (68,4%), dyslipidaemia (70%) and diabetes (30,7%). 78 pts completed a longer programme with 12 weeks duration while 36 underwent a shorter CRP with 8 weeks. There were no statistically significant differences between both groups regarding population demographics, aetiology, LVEF and co-morbidities. After CRP, there was significant improvement in risk factor control (mainly lipidic profile and weight) and echocardiographic parameters in both groups. We noted an important reduction in LDL levels (85±42.6mg/dL before CRP and 67.68±28.45mg/dL after), approaching the guideline recommended levels (<55mg/dL): 29.8% before vs 42.6% after (p=0.079), with no difference between the two groups (p=0,65). Significant improvement of LVEF was also observed (53% to 57%, p <0.001) without difference between the two groups (p=0.112). Exercise tolerance improved similarly in both groups, assessed by the time of exercise stress test: we registered a global increase of 65 ± 1.38s after CRP, with no difference between the two groups (p = 0.157). Conclusion: Shorter duration CRP showed similar results concerning risk factor control, echocardiographic LVEF and exercise tolerance improvement, suggesting that they can be an effective alternative when needed.
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In this paper, our goal is to analyze and compare cellular network usage data from pre-lockdown, during lock-down, and post-lockdown phases surrounding the COVID-19 pandemic to understand and model human mobility patterns during the pandemic. To this end, we collect and analyze cellular network connections from 1400 antennas for all users in the city of Rio de Janeiro and its suburbs from March 1, 2020 to July 1, 2020. Our analysis reveals that the total number of cellular connections decreases to 78% during the lockdown phase and then increases to 85% of the pre-COVID era as the lockdown eases. We observe that user mobility starts increasing around 3 weeks before the end of lockdown, with the trend continuing into the post-lockdown period. We also design an interactive tool that showcases mobility patterns in different granularities and can help government officials take informed actions to control the spread of the disease. © 2021 IEEE.
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This empirical research aimed to investigate possible informational similarities between the former president of the United States and the president of Brazil, due to the political-ideological alignment between Donald Trump and Jair Bolsonaro, who had a contradictory position in the fight against Covid-19. In order to elucidate the research question, data were collected from posts on the profiles of presidents on Facebook and official pronouncements on government websites since the first day of notification in countries to carry out Content Analysis through the program IRaMuTeQ, based on the theoretical-conceptual framework on disinformation. The results of the analyzes showed informational similarities between the two presidents, as well as similarities in the controversial speech and in attitudes contrary to the measures advocated by the World Health Organization.
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Background: On March 16, 2020, the first death from CO-VID-19 was recorded in Portugal. Since then, there has been a reorganization of health services, changing the normal approach for the different cases of public health. Excess deaths recorded without a COVID-19 diagnosis are called excess mortality without COVID-19 (EM non-COVID-19). This study aims to estimate the EM non-COVID in the 7-month period after the first registered Covid-19 death. Methods: The following 2 methods were used to estimate the excess mortality in this period: The daily historical average of reported deaths and an adapted auto regressive integrated moving average (ARIMA) model, considering the previous 5 years of records until October 16. For this model, after March 16, data was replaced with the daily historical average deaths from the previous 5 years, simulating the closest scenario possible as there was no pandemic. Only deaths from natural causes were selected for these estimations. For EM non-COVID-19 estimation, we subtracted the COVID-19 deaths from the overall excess mortality. Results: Between March 16, 2020, and October 16, 2020, there was an excess of 6,330 deaths from natural causes, i.e., nearly 12% more than expected. Both methods estimated an EM non-COVID-19 of around 66-67% in this period, with a greater relevance in mid-July and mid-September. Conclusions: Excess mortality was present almost every day during the study period. EM non-COVID-19 seemed to vary over time, showing some inadequacy of healthcare services in management of other patients free of COVID-19 in Portugal during periods with a greater patient volume. It is necessary to take care and monitor COVID-19 cases but also non-COVID-19 cases.
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Background: The role of demographic and socio-economic determinants of COVID-19 transmission is still unclear and is expected to vary in different contexts and epidemic periods. Exploring such determinants may generate a hypothesis about transmission and aid the definition of prevention strategies. Objectives: To identify municipality-level demographic and socio-economic determinants of COVID-19 in Portugal. Methods: We assessed determinants of COVID-19 daily cases at 4 moments of the first COVID-19 epidemic wave in Portugal, related with lockdown and post-lockdown measures. We selected 60 potential determinants from 5 dimensions: population and settlement, disease, economy, social context, and mobility. We conducted a multiple linear regression (MLR) stepwise analysis (p < 0.05) and an artificial neural network (ANN) analysis with the variables to identify predictors of the number of daily cases. Results: For MLR, some of the identified variables were: resident population and population density, exports, overnight stays in touristic facilities, the location quotient of employment in accommodation, catering and similar activities, education, restaurants and lodging, some industries and building construction, the share of the population working outside the municipality, the net migration rate, income, and renting. In ANN, some of the identified variables were: population density and resident population, urbanization, students in higher education, income, exports, social housing buildings, production services employment, and the share of the population working outside the municipality of residence. Conclusions: Several factors were identified as possible determinants of CO-VID-19 transmission at the municipality level. Despite limitations to the study, we believe that this information should be considered to promote communication and prevention approaches. Further research should be conducted. © 2021 The Author(s) Published by S. Karger AG, Basel.
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Introduction: Ever since the first positive case was identified on March 2nd in Lousada, a region close to the border of our catchment area, we reacted immediately by systematically repurposing our surgical wards. Objective: Describe the changed made by our Vascular Surgery Department from March 13 to May 14. Methods: We collected clinical, operative, and consultation volume data from March 13 to May 14 and we compared it with the historical averages. We also reviewed the documents related to the planification activity. Results: At the peak of the outbreak, weadopted a split-team policy and encouraged completeteam segregation to reduce the risk of intradepartmental cross-contamination. Non-ambulatory surgical volume decreased by 54.8% (from 31 cases to 14 cases), and the ambulatory surgical activity was cancelled. Our in-person consultation volume decreased 86.4%;73 consultations were completed by phone, in which the patient was never evaluated in-person. In the emergency room the main difference between the pre-pandemic to the pandemic was in the number of patients observed without vascular pathology (82 versus 28). Conclusions: The adaptation to C0VID-19 pandemic reduced significantly the surgical production of our Vascular Surgery Department.
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Purpose: COVID-19 causes lung inflammation and lesions, and chest X-ray and computed tomography images are remarkably suitable for differentiating the new disease from patients with other lung diseases. In this paper, we propose a computer model to classify X-ray images of patients diagnosed with COVID-19. Chest X-ray exams were chosen over computed tomography scans because they are low cost, results are quickly obtained, and X-ray equipment is readily available. Methods: A new CNN network, called CNN-COVID, has been developed to classify X-ray patient’s images. Images from two different datasets were used. The images of Dataset I is originated from the COVID-19 image data collection and the ChestXray14 repository, and the images of Dataset II belong to the BIMCV COVID-19+ repository. To assess the accuracy of the network, 10 training and testing sessions were performed in both datasets. A confusion matrix was generated to evaluate the model’s performance and calculate the following metrics: accuracy (ACC), sensitivity (SE), and specificity (SP). In addition, Receiver Operating Characteristic (ROC) curves and Areas Under the Curve (AUCs) were also considered. Results: After running 10 tests, the average accuracy for Dataset I and Dataset II was 0.9787 and 0.9839, respectively. Since the weights of the best test results were applied in the validation, it was obtained the accuracy of 0.9722 for Dataset I and 0.9884 for Dataset II. Conclusions: The results showed that the CNN-COVID is a promising tool to help physicians classify chest images with pneumonia, considering pneumonia caused by COVID-19 and pneumonia due to other causes. © 2021, Sociedade Brasileira de Engenharia Biomedica.
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Objectives: to develop a terminological subset of the International Classification for Nursing Practice (ICNP) for people with covid-19 sequelae.® Method: methodological study, which followed the steps: Identification of the relevant terms contained in the literature related to Covid-19 sequelae;Cross-mapping of the terms identified in the review with the terms of the classification;Construction of the statements of diagnoses, outcomes and nursing interventions and mapping of the constructed statements;Content validation of the statements by specialist nurses;and Structuring of the subset based on Roy’s Adaptation Model. For data analysis, the Content Validity Index was used, and the statements with Content Validity Index were validated ≥ 0.80. Content validation was performed by 28 specialist nurses. Results: 178 statements of nursing diagnoses/outcomes were constructed, with 450 nursing intervention statements. After content validation, a quantity of 127 diagnoses/outcomes and 148 nursing interventions were obtained, which comprised the terminological subset proposed in the study. Conclusion: the validated statements that make up the terminological subset with greater predominance were those outlines in the physiological adaptive mode. However, the repercussions on the spiritual, social and personal dimensions are also highlighted. © 2022, Universidade Federal de Santa Catarina. All rights reserved.
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The article presents an exploratory, descriptive study on Bad News Communication skills (CMN) of medical interns. The student’s perception was on learning for the CMN was investigated with a cross-sectional design and a mixed approach. A questionnaire was applied, 176 participants were obtained, and a focus group was held with 12 students. The data were analyzed through the calculation of means and standard deviations for quantitative variables and the focus group reports were subjected to Content Analysis. It was observed that in the group that had training, compared to the one who did not, ocurred twice frequency with more skill for CMN. In the CMN’s management, it was considered harder to be “honest without taking away hope” (69%) and “to deal with the patient’s emotion” (59%). 99.4% knew the SPIKES protocol, of which 41.5% considered the expression of emotions as its most difficult stage. Communication and handling of emotions were pointed out as the main difficulties in the doctorpatient relationship, with deficits in the teaching of CMN. It was found that CMN is not limited to the technical issue, but it involves attitudes that need to be addressed with different methodologies, as well as the implementation of educational policies in the medical field, especially given the demands that emerges with the covid-19 pandemic. © 2021, Brazilain Coll Veterinary Parasitology. All rights reserved.
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Objective: To develop and validate a terminological subset of the International Classification for Nursing Practice for COVID-19 patients in critical care. Method: This is a methodological study, which followed the guidelines of the Brazilian method, using the Basic Human Needs as a theoretical model. Content validation was performed by 25 specialist nurses using the Delphi technique. Results: A total of 73 diagnoses and their respective nursing results were prepared. Of these, 62 statements had a Content Validity Index >-0.80, with the need for oxygenation having the highest number of statements. Of the 210 nursing interventions developed, and after suggestions from experts, 150 interventions reached an index >-0.80 and comprised the terminological subset. Conclusion: The terminological subset developed showed statements that were validated by specialist nurses and, therefore, are relevant to the nurse's clinic in the critical care scenario associated with Covid-19.
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OBJECTIVE: To develop and validate a terminological subset of the International Classification for Nursing Practice for COVID-19 patients in critical care. METHOD: This is a methodological study, which followed the guidelines of the Brazilian method, using the Basic Human Needs as a theoretical model. Content validation was performed by 25 specialist nurses using the Delphi technique. RESULTS: A total of 73 diagnoses and their respective nursing results were prepared. Of these, 62 statements had a Content Validity Index >= 0.80, with the need for oxygenation having the highest number of statements. Of the 210 nursing interventions developed, and after suggestions from experts, 150 interventions reached an index >= 0.80 and comprised the terminological subset. CONCLUSION: The terminological subset developed showed statements that were validated by specialist nurses and, therefore, are relevant to the nurse's clinic in the critical care scenario associated with Covid-19.