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Showing papers by "Universidade de Pernambuco published in 2021"


Journal ArticleDOI
TL;DR: In this article, the authors reviewed the most recently published works on plasmonic nanofluids that exclusively present its preparation methods, thermophysical properties, and applications in solar collectors.

115 citations


Journal ArticleDOI
Maria Lc Iurilli1, Bin Zhou1, James E. Bennett1, Rodrigo M. Carrillo-Larco1  +1399 moreInstitutions (374)
09 Mar 2021-eLife
TL;DR: In this article, the authors investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants.
Abstract: From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions.

81 citations


Journal ArticleDOI
TL;DR: In this article, the authors evaluated early results of valve-in-valve (ViV) transcatheter aortic valve replacement (TAVR) versus redo SVR (Surgical Aortic Valve Replacement).
Abstract: Objectives The aim of this study was to evaluate early results of valve-in-valve (ViV) transcatheter aortic valve replacement (TAVR) versus redo surgical aortic valve replacement (SAVR) fo...

73 citations


Journal ArticleDOI
TL;DR: A previously healthy 12-year-old-girl presented with a skin rash, headache, and fever five days after that, she had an acute, progressive, bilateral, and symmetrical motor weakness and evolved to respiratory failure.
Abstract: The authors present a case of acute disseminated encephalomyelitis in a COVID-19 pediatric patient with positive SARS-CoV2 markers from a nasopharyngeal swab. A previously healthy 12-year-old-girl presented with a skin rash, headache, and fever. Five days after that, she had an acute, progressive, bilateral, and symmetrical motor weakness. She evolved to respiratory failure. Magnetic resonance imaging (MRI) of the brain and cervical spine showed extensive bilateral and symmetric restricted diffusion involving the subcortical and deep white matter, a focal hyperintense T2/FLAIR lesion in the splenium of the corpus callosum with restricted diffusion, and extensive cervical myelopathy involving both white and gray matter. Follow-up examinations of the brain and spine were performed 30 days after the first MRI examination. The images of the brain demonstrated mild dilatation of the lateral ventricles and widespread widening of the cerebral sulci, complete resolution of the extensive white matter restricted diffusion, and complete resolution of the restricted diffusion in the lesion of the splenium of the corpus callosum, leaving behind a small gliotic focus. The follow-up examination of the spine demonstrated nearly complete resolution of the extensive signal changes in the spinal cord, leaving behind scattered signal changes in keeping with gliosis. She evolved with partial clinical and neurological improvement and was subsequently discharged.

55 citations


Journal ArticleDOI
Sheryl Ann Abdukahil, Ryuzo Abe, Laurent Abel, Lara Absil  +1061 moreInstitutions (15)
TL;DR: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19 and as discussed by the authors evaluated relationships of age, sex, and nationality to presenting symptoms.
Abstract: Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men.

53 citations


Journal ArticleDOI
TL;DR: Challenges surrounding the use of ivermectin in the context of coronavirus disease-19 (COVID-19) and how novel formulations employing micro- and nanotechnologies may address these concerns are discussed.

47 citations


Journal ArticleDOI
TL;DR: This work proposes different topologies of a multimodal convolution neural network, which is trained to detect falls based on RGB images and information from accelerometers, and achieves the state-of-the-art on UP-Fall detection dataset, demonstrating it can be a scalable solution for robust fall detection in the real world.
Abstract: A computational system able to automatically and efficiently detect and classify falls would be beneficial for monitoring the elderly population and speed up the assistance proceedings, reducing the risk of prolonged injuries and death. One of the most common problems in such systems is the high number of false-positives in their recognition scheme, which may cause an overload on surveillance system calls. We address this problem by proposing different topologies of a multimodal convolution neural network, which is trained to detect falls based on RGB images and information from accelerometers. We train and evaluate our networks with the UR Fall Detection dataset and UP-Fall dataset, and provide an extensive comparison with state-of-the-art models. Our model reached good results on UR Fall Detection dataset and achieved the state-of-art on UP-Fall detection dataset, relying on easily available sensors to do so, demonstrating it can be a scalable solution for robust fall detection in the real world.

42 citations


Journal ArticleDOI
TL;DR: In this paper, a modified dynamic selection (DS) algorithm is used to select the most suitable ML model to forecast a pattern of residual series and if it is a promising candidate to increase the accuracy of the time series forecast from the linear combination.
Abstract: Hybrid systems, which combine statistical and machine learning (ML) techniques using residual (error forecasting) modeling, have been highlighted in the literature due to their accuracy and ability to forecast time series with different characteristics. In these architectures, a crucial task is the proper modeling of the residuals since they may present random fluctuations, complex nonlinear patterns, and heteroscedastic behavior. Hence, the selection, specification, and training of one ML model to forecast the residuals are costly and challenging tasks since issues, such as underfitting, overfitting, and misspecification, can lead to a system with low accuracy or even deteriorate the linear forecast of the time series. This article proposes a hybrid system, named dynamic residual forecasting (DReF), that employs a modified dynamic selection (DS) algorithm to decide: the most suitable ML model to forecast a pattern of the residual series and if it is a promising candidate to increase the accuracy of the time series forecast from the linear combination. Thus, the DReF aims to reduce the uncertainty of the ML model selection and avoid the deterioration of the time series forecast. Furthermore, the proposed system searches for the most suitable parameters of the DS algorithm for each data set. In this article, the proposed method uses a pool of five ML models widely adopted in the literature: multilayer perceptron, support vector regression, radial basis function, long short-term memory, and convolutional neural network. An experimental evaluation was conducted using ten well-known time series. The results show that the DReF obtains superior results for the majority of the data sets compared with single and hybrid models of the literature.

33 citations


Journal ArticleDOI
TL;DR: In this paper, the authors used published and unpublished data to derive an inventory on ecosystem-level carbon stocks and carbon sequestration rates in the Cananeia-Iguape lagoon estuarine system.

32 citations


Journal ArticleDOI
17 Mar 2021-PLOS ONE
TL;DR: In this paper, the authors developed a questionnaire specifically to evaluate medical students' perceptions about participating in the care of patients with suspected infection with coronavirus during the COVID-19 pandemic.
Abstract: BACKGROUND: There has been a rapid increase in the number of cases of COVID-19 in Latin America, Africa, Asia and many countries that have an insufficient number of physicians and other health care personnel, and the need for the inclusion of medical students on health teams is a very important issue. It has been recommended that medical students work as volunteers, undergo appropriate training, not undertake any activity beyond their level of competence, and receive continuous supervision and adequate personal protective equipment. However, the motivation of medical students must be evaluated to make volunteering a more evidence-based initiative. The aim of our study was to evaluate the motivation of medical students to be part of health teams to aid in the COVID-19 pandemic. METHODS AND FINDINGS: We developed a questionnaire specifically to evaluate medical students' perceptions about participating in the care of patients with suspected infection with coronavirus during the COVID-19 pandemic. The questionnaire had two parts: a) one part with questions on individual characteristics, year in medical school and geographic location of the medical school and b) a second part with twenty-eight statements assessed on a 5-point Likert scale (totally agree, agree, neither agree nor disagree, disagree and totally disagree). To develop the questionnaire, we performed consensus meetings with a group of faculty and medical students. The questionnaire was sent to student organizations of 257 medical schools in Brazil and answered by 10,433 students. We used multinomial logistic regression models to analyze the data. Statements associated with greater odds ratios for participation of medical students in the COVID-19 pandemic were related to a sense of purpose or duty ("It is the duty of the medical student to put himself or herself at the service of the population in the pandemic"), altruism ("I am willing to take risks by participating in practice in the context of the pandemic"), and perception of good performance and professional identity ("I will be a better health professional for having experienced the pandemic"). Males were more prone than females to believe that only interns should participate in the care of patients with COVID-19 (odds ratio 1.36 [coefficient interval 95%:1.24-1.49]) and that all students should participate (OR 1.68 [CI:1.4-1.91]). CONCLUSIONS: Medical students are more motivated by a sense of purpose or duty, altruism, perception of good performance and values of professionalism than by their interest in learning. These results have implications for the development of volunteering programs and the design of health force policies in the present pandemic and in future health emergencies.

32 citations


Journal ArticleDOI
TL;DR: In this paper, the performance of a direct absorption solar collector using working-fluids composed of TiN, ZrN, and HfN in an aqueous medium was evaluated using Mie theory and numerical solutions of a two-dimensional heat transfer model.

Journal ArticleDOI
TL;DR: COVID-19 causes low pulmonary compliance and important changes in lung function with hypoxemia and cardiovascular repercussions, which lead to the need for Physiotherapy and the management of oxygen therapy and ventilatory support for these patients.
Abstract: Introduction: The new corona virus (2019-nCoV OR HCOV-19 or CoV2), has emerged in China as the main cause of viral pneumonia (COVID-19, Coronavirus Disease-19). Objective: To provide evidence-based Physiotherapy and functionality in patients with adult and pediatric COVID-19. Methods: This is an integrative literature review using the MedLine / PubMed databases, library of Latin American and Caribbean Literature in Health Sciences (LILACS) and Physiotherapy Evidence Database (PEDRo). Results: Part of the patients with covid 19 show signs of respiratory deficiency with hypoxemia, with low severity in children. Impaired functionality is also expected. Conclusion: COVID-19 causes low pulmonary compliance and important changes in lung function with hypoxemia and cardiovascular repercussions. These changes lead to the need for Physiotherapy and the management of oxygen therapy and ventilatory support (invasive and non-invasive) for these patients.

Journal ArticleDOI
TL;DR: In this article, trainable and non-trainable combination methods are used for PM10 and PM2.5 time series forecasting for eight different locations, in Finland and Brazil, for different periods.
Abstract: The air pollution caused by particulate matter (PM) has become a public health issue due to the risks to human life and the environment. The PM concentration in the air causes haze and affects the lungs and the heart, leading to reduced visibility, allergic reactions, pneumonia, asthma, cardiopulmonary diseases, lung cancer, and even death. In this context, the development of systems for monitoring, forecasting, and controlling emissions plays an important role. The literature about forecasting systems based on Artificial Neural Networks (ANNs) ensembles has been highlighted regarding statistical accuracy and efficiency. In this article, trainable and non-trainable combination methods are used for PM10 and PM2.5 (particles with an aerodynamic diameter less than 10 and 2.5 micrometers, respectively) time series forecasting for eight different locations, in Finland and Brazil, for different periods. Trainable ensembles based on ANNs, linear regression, and Copulas are compared with non-trainable combinations (mean and median), single ANNs, and linear statistical approaches. Different models are considered so far, including Autoregressive model (AR), Autoregressive and Moving Average Model (ARMA), Infinite Impulse Response Filters (IIR), Multilayer Perceptron (MLP), Radial Basis Function Networks (RBF), Extreme Learning Machines (ELM), Echo State Networks (ESN), and Adaptive Network Fuzzy Inference System (ANFIS). The use of ANNs ensembles, mainly combined with MLP, leads to a better one step ahead forecasting performance. The use of robust air pollution forecasting tools is prime to assist governments in managing air pollution issues like hospital collapse during adverse air quality situations. In this sense, our study is indirectly related to the following United Nations sustainable development goals: SDG 3 - good health and well-being and SDG 11 - sustainable cities and communities.

Journal ArticleDOI
TL;DR: In this article, an electric field driven enhancement in the superconducting property in type-II superconductors is presented, which is a crucial step toward the understanding of field effects on the fundamental properties of a superconductor and its exploitation for logic and memory applications.
Abstract: Significant control over the properties of a high-carrier density superconductor via an applied electric field has been considered infeasible due to screening of the field over atomic length scales. Here, we demonstrate an enhancement of up to 30% in critical current in a back-gate tunable NbN micro- and nano superconducting bridges. Our suggested plausible mechanism of this enhancement in critical current based on surface nucleation and pinning of Abrikosov vortices is consistent with expectations and observations for type-II superconductor films with thicknesses comparable to their coherence length. Furthermore, we demonstrate an applied electric field-dependent infinite electroresistance and hysteretic resistance. Our work presents an electric field driven enhancement in the superconducting property in type-II superconductors which is a crucial step toward the understanding of field-effects on the fundamental properties of a superconductor and its exploitation for logic and memory applications in a superconductor-based low-dissipation digital computing paradigm.

Journal ArticleDOI
01 Jan 2021
TL;DR: This work developed and applied an original new approach that combines data of one 3D depth sensor (Kinect) and proprioceptive robot sensors, and uses the principle of limited safety contour around the obstacle to dynamically estimate the robot-obstacle distance, and then generate the repulsive force that controls the robot.
Abstract: Human-Robot Interaction (HRI) is a largely addressed subject today. In order to ensure co-existence and space sharing between human and robot, collision avoidance is one of the main strategies for interaction between them without contact. It is thus usual to use a 3D depth camera sensor (Microsoft Kinect V2) which may involve issues related to occluded robot in the camera view. While several works overcame this issue by applying infinite depth principle or increasing the number of cameras, in the current work we developed and applied an original new approach that combines data of one 3D depth sensor (Kinect) and proprioceptive robot sensors. This method uses the principle of limited safety contour around the obstacle to dynamically estimate the robot-obstacle distance, and then generate the repulsive force that controls the robot. For validation, our approach is applied in real time to avoid collisions between dynamical obstacles (humans or objects) and the end-effector of a real 7-dof Kuka LBR iiwa collaborative robot. Our method is experimentally compared with existing methods based on infinite depth principle when the robot is hidden by the obstacle with respect to the camera view. Results showed smoother behavior and more stability of the robot using our method. Extensive experiments of our method, using several strategies based on distancing and its combination with dodging were done. Results have shown a reactive and efficient collision avoidance, by ensuring a minimum obstacle-robot distance (of $\approx \text{240 mm}$ ), even when the robot is in an occluded zone in the Kinect camera view.

Journal ArticleDOI
TL;DR: In this paper, the authors proposed an intelligent system to support Covid-19 diagnosis based on blood testing. And they used particle swarm optimization, evolutionary algorithms and manual selection based on cost minimization to select the most significant features.
Abstract: A new kind of coronavirus, the SARS-CoV-2, started the biggest pandemic of the century. More than a million people have been killed by Covid-19. Because of this, quick and precise diagnosis test is necessary. The current gold standard is the RT-PCR with DNA sequencing and identification, but its results take too long to be available. Tests base on IgM/IgG antibodies have been used, but their sensitivity and specificity may be very low. Many studies have been demonstrating the Covid-19 impact on hematological parameters. This work proposes an intelligent system to support Covid-19 diagnosis based on blood testing. Laboratory parameters obtained from the hemogram and biochemical tests defined as standards to support clinical diagnosis were used as input features. Afterward, we used particle swarm optimization, evolutionary algorithms, and manual selection based on cost minimization to select the most significant features. We tested several machine learning methods, and we achieved high classification performance: overall accuracy of 95.159% ± 0.693, kappa index of 0.903 ± 0.014, sensitivity of 0.968 ± 0.007, precision of 0.938 ± 0.010, and specificity of 0.936 ± 0.011. These results were achieved using classical and low computational cost classifiers, with Bayes Network being the best of them. In addition, only 24 blood tests were needed. This points to the possibility of a new rapid test with low cost. The desktop version of the system is fully functional and available for free use.

Journal ArticleDOI
TL;DR: In this paper, the outcome of hospitalized coronavirus disease 2019 (COVID-19) patients with heart failure (HF) compared with patients with other cardiovascular disease and/or risk factors (arterial hypertension, diabetes, or dyslipidaemia).
Abstract: AIMS We assessed the outcome of hospitalized coronavirus disease 2019 (COVID-19) patients with heart failure (HF) compared with patients with other cardiovascular disease and/or risk factors (arterial hypertension, diabetes, or dyslipidaemia). We further wanted to determine the incidence of HF events and its consequences in these patient populations. METHODS AND RESULTS International retrospective Postgraduate Course in Heart Failure registry for patients hospitalized with COVID-19 and CArdioVascular disease and/or risk factors (arterial hypertension, diabetes, or dyslipidaemia) was performed in 28 centres from 15 countries (PCHF-COVICAV). The primary endpoint was in-hospital mortality. Of 1974 patients hospitalized with COVID-19, 1282 had cardiovascular disease and/or risk factors (median age: 72 [interquartile range: 62-81] years, 58% male), with HF being present in 256 [20%] patients. Overall in-hospital mortality was 25% (n = 323/1282 deaths). In-hospital mortality was higher in patients with a history of HF (36%, n = 92) compared with non-HF patients (23%, n = 231, odds ratio [OR] 1.93 [95% confidence interval: 1.44-2.59], P < 0.001). After adjusting, HF remained associated with in-hospital mortality (OR 1.45 [95% confidence interval: 1.01-2.06], P = 0.041). Importantly, 186 of 1282 [15%] patients had an acute HF event during hospitalization (76 [40%] with de novo HF), which was associated with higher in-hospital mortality (89 [48%] vs. 220 [23%]) than in patients without HF event (OR 3.10 [2.24-4.29], P < 0.001). CONCLUSIONS Hospitalized COVID-19 patients with HF are at increased risk for in-hospital death. In-hospital worsening of HF or acute HF de novo are common and associated with a further increase in in-hospital mortality.

Journal ArticleDOI
TL;DR: This is the first literature review on general parameter control for evolutionary and swarm-based algorithms and one of the very few systematic reviews on parameter adjustment for those algorithms.
Abstract: This paper presents a systematic literature review on general parameter control for evolutionary and swarm-based algorithms. General methods can be applied to any algorithm, parameter or problem, in contrast to methods that are tailored to specific applications. In this literature review, a total of 4449 studies were retrieved by the search engines and only 50 of them were selected to the extraction phase. Finally, only 15 were fully analyzed and discussed. To the best of our knowledge, this is the first literature review on such a field and one of the very few systematic reviews on parameter adjustment for those algorithms.

Journal ArticleDOI
TL;DR: The unprecedented challenges faced by the Brazilian public health system in dealing with the incursion of SARS-CoV-2 in the midst of ongoing triple arboviral epidemics caused by dengue, chikungunya, and Zika virus are discussed.

Journal ArticleDOI
TL;DR: The authors' results suggest that Caatinga dry forest covering sandy soils is particularly resilient due to regeneration driven by resprouting, and may follow an initial composition model, rather than following a directional and deterministic trajectory associated with species replacements.

Journal ArticleDOI
TL;DR: In this paper, the authors evaluated the impact of the COVID-19 pandemic on office blood pressure (OBP) and home blood pressure monitoring (HBPM) control in a large Brazilian nationwide sample.
Abstract: There are concerns that hypertension control may decrease during the COVID-19 pandemic. This study evaluated the impact of the COVID-19 pandemic on office blood pressure (OBP) and home blood pressure monitoring (HBPM) control in a large Brazilian nationwide sample. The results of an adjusted spline analysis evaluating the trajectory of OBP and HBPM control from 01/Jan/2019 to 31/Dec/2020 among independent participants who were untreated (n = 24,227) or treated (n = 27,699) with antihypertensive medications showed a modest and transient improvement in OBP control among treated individuals, which was restricted to the early months following the COVID-19 pandemic outbreak. Furthermore, slight reductions in OBP and HBPM values were detected in the early months following the COVID-19 pandemic outbreak among treated (n = 987) participants for whom blood pressure measurements before and during the pandemic were available, but not among untreated (n = 495) participants. In conclusion, we found no major adverse influence of the COVID-19 pandemic on OBP and HBPM control in a large nationwide sample. *Adjusted prevalence of high office blood pressure (OBP) and home blood pressure monitoring (HBPM) before and during the Covid-19 pandemic among independent treated participants. **p < 0.05. Whisker-plot: 95% confidence interval.

Journal ArticleDOI
TL;DR: The bulk-fill resin composites showed satisfactory clinical performance compared with conventional resin composite after 12 months and the percentage of the acceptable scores was significantly higher for the USPHS criteria, due to discrepancies in the score description for each criterion.
Abstract: Objective This study was aimed to compare the 12-month clinical performance of two full-body bulk-fill resin composites Filtek bulk fill/3M ESPE (FBF) and Tetric EvoCeram bulk fill/Ivoclar Vivadent (TBF) and a conventional microhybrid resin composite Filtek Z250/3M ESPE (Z250) using the modified the United States Public Health Service (USPHS) and Federation Dentaire Internationale (FDI) criteria. Also, the agreement between the two evaluation criteria was evaluated at baseline and after 12 months of follow-up. Materials and Methods A total of 138 class I and II restorations were placed in posterior teeth (split-mouth design) of 46 volunteers following manufacturer’s instructions and bonded with a self-etching bonding agent (Clear fill SE Bond/Kuraray). The restorations were evaluated at baseline and after 12 months of follow-up by three previously calibrated dentists (Cohen’s K = 0.84). Statistical Analysis Fisher’s exact test and Pearson’s Chi-squared test were used to evaluating the homogeneity of distribution of the clinical characteristics. Friedman’s test was applied to evaluate differences among the resin composites. The results obtained for the USPHS and FDI criteria at the different observation times were compared using the Wilcoxon test. A level of significance of 0.05 was adopted for all tests. Results After 12 months (recall rate, 78.3%, n = 36 patients), the overall success rate was 99.07% for both criteria. Only one failed restoration (0.93%) was detected for each system during follow-up in the TBF group. Conclusion The bulk-fill resin composites showed satisfactory clinical performance compared with conventional resin composite after 12 months. The percentage of the acceptable scores was significantly higher for the USPHS criteria, due to discrepancies in the score description for each criterion.

Journal ArticleDOI
TL;DR: The ex vivo administration of Mirococept is a safe and feasible approach to treat DGF in deceased donor kidney transplantation and an optimal dose of 80 mg (equivalent to 120 mg in human kidney) is identified that provides a basis for further clinical development.

Journal ArticleDOI
TL;DR: AAE is a useful adjunct to AVR, but the benefit of reduced PPM must be balanced against a possibly higher risk of perioperative mortality.

Journal ArticleDOI
25 Dec 2021
TL;DR: The nanoparticles showed high stability and excellent antimicrobial activity for Gram-positive and Gram-negative bacteria and were able to preserve the antioxidant activity of curcumin and showed moderate cytotoxicity against colorectal and lung cancer strains.
Abstract: The encapsulation of curcumin into lecithin/chitosan nanoparticles (NPC) using the electrostatic self-assembly technique was evaluated. NPC were characterized through average size, zeta potential, polydispersity index (PDI), morphology (TEM), encapsulation efficiency, Fourier Transform Infrared Spectroscopy (FT-IR), and thermal analyzes (TGA and DSC). The bioactive properties of NPC were determined by antioxidant (DPPH) and antimicrobial activities (against bacteria and fungi); the cytotoxic activity was performed through the MTT assay against normal and neoplastic cells. The stability of the NPC was evaluated for 28 days at 4 °C and 30 °C. NPC were spherical, with an average size of 236.27 ± 2.29 nm, PDI of 0.15 ± 0.01, Zeta potential of +51.31 ± 2.41 mV, and a high encapsulation rate (92.74 ± 0.01%). The nanoparticles showed high stability and excellent antimicrobial activity for Gram-positive and Gram-negative bacteria. NPC were also able to preserve the antioxidant activity of curcumin and showed moderate cytotoxicity against colorectal and lung cancer strains. These characteristics expand the possibility of applying NPC in the field of nutraceuticals, for example immobilized in different food matrices for the development of new functional products.

Journal ArticleDOI
TL;DR: A Deterministic and Stochastic Petri Net approach for evaluating Fog–Cloud IoT environments composed of hundreds physical Things that allows evaluating the trade-offs of many performability metrics and may help system designers to choose the most suitable Fog-Cloud IoT environment.
Abstract: Internet of Things (IoT) is an emerging paradigm that transforms everyday devices (Things) into Internet-connected devices with sensing, processing, and actuation capabilities. These devices have limited storage and processing capacity, so they have been integrated with Cloud computing to overcome these limitations. Cloud computing offers various benefits such as offload data storage and processing burden at the Cloud side. Nevertheless, because Cloud is not an efficient solution for IoT latency-sensitive applications, Fog computing was introduced to address this limitation. Although Fog–Cloud IoT environments have begun to be adopted in the last few years, such environments have not been properly assessed in terms of their capacity to meet the growing demand of IoT devices. In this work, we present a Deterministic and Stochastic Petri Net (DSPN) approach for evaluating Fog–Cloud IoT environments composed of hundreds physical Things. Our approach allows evaluating the trade-offs of many performability metrics (e.g., utilization, response time, throughput, and availability) and, consequently, may help system designers to choose the most suitable Fog–Cloud IoT environment. We demonstrate the feasibility of our approach through a real-world case study. The results revealed that adopting a Fog device can improve availability. However, the performance is only improved in certain conditions like when the environment is not at full capacity.

Journal ArticleDOI
TL;DR: In this paper, a cross-sectional study was conducted to assess the epidemiological and clinical aspects of COVID-19 in patients younger than 20 years in Pernambuco (Brazil), with cases confirmed by reverse-transcriptase-PCR SARS-CoV-2 between 13 February and June 19, 2020, reported on information systems.
Abstract: COVID-19 in children and adolescents has low frequency, severity, and fatality rate all over the world. A cross-sectional study was conducted to assess the epidemiological and clinical aspects of COVID-19 in patients younger than 20 years in Pernambuco (Brazil), with cases confirmed by reverse-transcriptase-PCR SARS-CoV-2 between 13 February and June 19, 2020, reported on information systems. Data regarding age (< 30 days, 1-11 months, 1-4 years, 5-9 years, 10-14 years, and 15-19 years), gender, color/race, symptoms, pregnancy or puerperium, comorbidities, hospitalization, and death were investigated. Fatality rate and mortality coefficient were calculated, and a multiple logistic regression analysis was performed to determine if gender, age, and comorbidities were factors associated with death. Of 682 pediatric cases, 52.8% were female, with a mean age of 9 ± 7.2 years. The most frequent symptoms were fever (64.4%), cough (52.4%), and respiratory distress (32.4%). Hospitalization was reported in 46.2% of cases, mainly among neonates (80.3%) and infants (73.8%). Thirty-eight deaths were notified, and a fatality rate of 5.6% (95% CI: 3.9-7.3) was found, with higher fatality rates among neonates 11.5% (7 of 61) and 9.5% (8 of 84) infants. The mortality coefficient was 10.9 per 100,000 inhabitants < 1 year of age, whereas comorbidities (Odds ratio [OR] = 14.13, 95% CI: 6.35-31.44), age < 30 days (OR = 5.17, 95% CI: 1.81-14.77), and age 1-11 months (OR = 3.28, 95% CI: 1.21-8.91) were independent factors associated with death. The results demonstrate the vulnerability of neonates and infants with severe conditions, need hospitalization, and high fatality rate, indicating the necessity to adapt public health policies for these age-groups.

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TL;DR: In this paper, the authors investigated the quality of sleep and the prevalence rate of sleeping disorders among physicians during COVID-19 pandemic, and identified the psychological and social factors associated with the condition.
Abstract: Introduction: Coronavirus pandemic began in China in 2019 (COVID-19), causing not only public health problems but also great psychological distress, especially for physicians involved in coping with the virus or those of the risk group in social isolation, and this represents a challenge for the psychological resilience in the world population. Studies showed that health professionals had psychological symptoms such as depression, anxiety, insomnia, stress, among others. Objectives: To investigate the quality of sleep and the prevalence rate of sleeping disorders among physicians during COVID-19 pandemic, and identify the psychological and social factors associated with the condition. Methods: A cross-sectional study of an online questionnaire was applied for physicians in Brazil. Among the 332 participants included, 227 were women. Sociodemographic assessment was used in the questionnaire, as well as the scale of impact on the events of modifications caused by COVID-19, assessment on sleep quality (PSQI), presence and severity of insomnia (ISI), depressive symptoms (PHQ-9), and anxiety (GAD-7). Results: Most physicians (65.6%) had changes in sleep. Poor sleep quality was reported by 73.1%, depressive symptoms were present in 75.8%, and anxiety in 73.4%. Conclusion: Our study found that more than 70% of the physicians assessed had impaired sleep quality, characterizing insomnia symptoms during COVID-19 outbreak. Related factors included an environment of isolation, concerns about COVID-19 outbreak and symptoms of anxiety and depression. Special interventions are needed to promote health professionals’ mental well-being and implement changes in this scenario.

Journal ArticleDOI
TL;DR: In this paper, the authors reported the synthesis of eight novel indole-thiazole derivatives, as well as their ability to interact with DNA, analysed through the UV-vis absorption, fluorescence, circular dichroism (CD), viscosity techniques and molecular docking.

Journal ArticleDOI
TL;DR: In this article, the authors investigated the properties of a set of mineral systems applied to cement-based materials (silica fume, metakaolin, and fly ashes) using X-ray fluorescence, microstructural, and chemometric analyses.
Abstract: Presence of reactive oxides, such as sodium, potassium, and magnesium oxides, compromise the pozzolanic activities of mineral additions to cement-based materials. That is because these oxides react with water to form hydroxides. Subsequently, these hydroxides may react with the otherwise non-reactive oxides, such as silicon and aluminum oxides, to form various silicate and aluminate phases in the cement-based material, that finally compete with the desired CSH phase. Further, the strong pozzolanic activity of the silica fume is seemingly due to its large ability to form the calcium silicate hydrated systems when compared with both metakaolin and fly ashes. All these results have been established by X-ray fluorescence, microstructural, and chemometric analyses that were applied to investigate the pozzolanic activities, thermodynamic, structural, and mechanical properties of a set of mineral systems widely applied to cement-based materials (silica fume, metakaolin, and fly ashes). The chemometric analyses revealed that the materials prepared with silica fume exhibited the largest mechanical properties, whereas the reference the lowest. The cement-based materials with metakaolin and fly ashes present intermediary resistances and similar behaviors. In conclusion, strict control of the purity of the material always needs to be performed to obtain mineral systems with powerful pozzolanic activities.