The new coronavirus ( COVID-19 ) , declared by the World Health Organization as a pandemic, has infected more than 1 million people and killed more than 50 thousand. An infection caused ...by COVID-19 can develop into pneumonia, which can be detected by a chest X-ray exam and should be treated appropriately. In this work, we propose an automatic detection method for COVID-19 infection based on chest X-ray images. The datasets constructed for this study are composed of 194 X-ray images of patients diagnosed with coronavirus and 194 X-ray images of healthy patients. Since few images of patients with COVID-19 are publicly available, we apply the concept of transfer learning for this task. We use different architectures of convolutional neural networks ( CNNs ) trained on ImageNet, and adapt them to behave as feature extractors for the X-ray images. Then, the CNNs are combined with consolidated machine learning methods, such as k-Nearest Neighbor, Bayes, Random Forest, multilayer perceptron ( MLP ) , and support vector machine ( SVM ) . The results show that, for one of the datasets, the extractor-classifier pair with the best performance is the MobileNet architecture with the SVM classifier using a linear kernel, which achieves an accuracy and an F1-score of 98.5 & . For the other dataset, the best pair is DenseNet201 with MLP, achieving an accuracy and an F1-score of 95.6 & . Thus, the proposed approach demonstrates efficiency in detecting COVID-19 in X-ray images.
Municipal biowaste is a major environmental issue. Life-cycle assessment is a valuable tool to assess recycling options, and anaerobic digestion and composting have performed adequately. However, ...reviews indicate several discrepancies between studies. Thus, we critically review 25 life-cycle assessments of the composting and anaerobic digestion of municipal biowaste. Our objective is to identify decisive factors, methodological gaps and processes that affect environmental performance. We generally identified methodological gaps in expanding systems borders. In energy systems, the replaced energy source did not consider power generation or dynamic regulation. All studies adopted mixed energy sources or marginal approaches. Agroecosystems included the carbon sequestration potential and compensation for the production of synthetic fertilizers only. A limited range of scientifically proven benefits of compost use has been reported. In general, studies provided a limited account of the effects of use on land emissions, but contradictory assumptions emerged, mainly in modelling synthetic fertilizer compensation. Only three studies compensated direct emissions from the use of synthetic fertilizers, and none included indirect emissions. Further studies should include an analysis of the additional benefits of compost use, compensate for the effects of emissions from synthetic fertilizer use on land and mix attributional and consequential approaches in energy system expansion.
Network slicing at the radio access network (RAN) domain, called RAN slicing, requires elasticity, efficient resource sharing, and customization. In this scenario, radio resource scheduling (RRS) is ...responsible for dealing with scarce and limited frequency spectrum resources available at the RAN domain while fulfilling the slice intents. The wide variety of scenarios supported in 5G and beyond 5G networks makes the RRS problem in RAN slicing scenario a significant challenge. This paper proposes an intent-aware reinforcement learning method to perform the RRS function in a RAN slicing scenario. The slice's quality of service intents is described in a common intent model in a service-level agreement. The proposed method tries to prevent intent faults by making the management of radio resources available among slices. This method uses slices' and users' equipment network metrics in the observation space. The proposed method is evaluated under different network conditions and outperforms different baselines considering the slices' intents fulfillment.
Purpose
Understanding self‐rated health in young people can help orient global health actions, especially in regions of social vulnerability. The present study analysed individual and contextual ...factors associated with self‐rated health in a sample of Brazilian adolescents.
Design and Methods
Cross‐sectional data from 1272 adolescents (aged 11–17; 48.5% of girls) in low human development index (HDI) neighbourhoods were analysed (HDI from 0.170 to 0.491). The outcome variable was self‐rated health. Independent variables relating to individual factors (biological sex, age and economic class) and lifestyle (physical activity, alcohol, tobacco consumption and nutritional state) were measured using standardised instruments. The socio‐environmental variables were measured using neighbourhood registered data where the adolescents studied. Multilevel regression was used to estimate the regression coefficients and their 95% confidence intervals (CI).
Results
Good self‐rated health prevalence was of 72.2%. Being male (B: −0.165; CI: −0.250 to −0.081), age (B: −0.040; CI: −0.073 to −0.007), weekly duration of moderate to vigorous physical activity (B: 0.074; CI: 0.048–0.099), body mass index (B: −0.025; CI: −0.036 to −0.015), number of family healthcare teams in the neighbourhood (B: 0.019; CI: 0.006–0.033) and dengue incidence (B: −0.001; CI: −0.002; −0.000) were factors associated with self‐rated health among students from vulnerable areas.
Conclusions/Practical Implications
Approximately three in every 10 adolescents in areas of social vulnerability presented poor self‐rated health. This fact was associated with biological sex and age (individual factors), physical activity levels and BMI (lifestyle) and the number of family healthcare teams in the neighbourhood (contextual).
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The use of (nanostructured lipid carries) NLC to disperse curcumin in aqueous media is widely found in literature. However, few studies systematically analyze the influence of the ...lipid matrix composition and the presence of curcumin on the physicochemical characteristics of NLC. Thus, the present work aimed to verify the influence of the NLC composition on its structure. Different solid lipid (SL) to liquid lipid (LL) ratios were evaluated, yielding NLC < 600 nm and <400 nm with the use of MCT and castor oil, respectively. The addition of Tween 80 favored the formation of smaller structures. Thermal analysis data confirmed the formation of different structures due to their different composition and also after the incorporation of curcumin. The present study also describes a correlation between the rheology of the NLC dispersion and the degree of structural organization of the NLC, indicating the formation of structures with a differentiated degree of organization. Photomicrographs showed the formation of two different structures, multiple types and amorphous, with drug concentrated in nucleus. in vitro studies have not shown significant IC50 differences between the systems developed with curcumin; however, the time and effectiveness of internalization were different for the two developed systems. The interaction between SL and LL demonstrated to be an important parameter that should be considered before the development of NLC, also the molecular characteristics of each component must be verified in order to develop NLC on a desirable type.
Human activities pose a major threat to tropical forest biodiversity and ecosystem services. Although the impacts of deforestation are well studied, multiple land-use and land-cover transitions ...(LULCTs) occur in tropical landscapes, and we do not know how LULCTs differ in their rates or impacts on key ecosystem components. Here, we quantified the impacts of 18 LULCTs on three ecosystem components (biodiversity, carbon, and soil), based on 18 variables collected from 310 sites in the Brazilian Amazon. Across all LULCTs, biodiversity was the most affected ecosystem component, followed by carbon stocks, but the magnitude of change differed widely among LULCTs and individual variables. Forest clearance for pasture was the most prevalent and high-impact transition, but we also identified other LULCTs with high impact but lower prevalence (e.g., forest to agriculture). Our study demonstrates the importance of considering multiple ecosystem components and LULCTs to understand the consequences of human activities in tropical landscapes.
In this work, a comparative study on different drill point geometries and feed rate for composite laminates drilling is presented. For this goal, thrust force monitoring during drilling, hole wall ...roughness measurement and delamination extension assessment after drilling is accomplished. Delamination is evaluated using enhanced radiography combined with a dedicated computational platform that integrates algorithms of image processing and analysis. An experimental procedure was planned and consequences were evaluated. Results show that a cautious combination of the factors involved, like drill tip geometry or feed rate, can promote the reduction of delamination damage.
The adoption of IoT for smart health applications is a relevant tool for distributed and intelligent automatic diagnostic systems. This work proposes the development of an integrated solution to ...monitor maternal and fetal signals for high-risk pregnancies based on IoT sensors, feature extraction based on data analytics, and an intelligent diagnostic aid system based on a 1-D convolutional neural network (CNN) classifier. The fetal heart rate and a group of maternal clinical indicators, such as the uterine tonus activity, blood pressure, heart rate, temperature, and oxygen saturation are monitored. Multiple data sources generate a significant amount of data in different formats and rates. An emergency diagnostic subsystem is proposed based on a fog computing layer and the best accuracy was 92.59% for both maternal and fetal emergency. A smart health analytics system is proposed for multiple feature extraction and the calculation of linear and nonlinear measures. Finally, a classification technique is proposed as a prediction system for maternal, fetal, and simultaneous health status classification, considering six possible outputs. Different classifiers are evaluated and a proposed CNN presented the best results, with the F1-score ranging from 0.74 to 0.91. The results are validated based on the diagnosis provided by two specialists. The results show that the proposed system is a viable solution for maternal and fetal ambulatory monitoring based on IoT.
Intoxication with lead (Pb) results in increased blood pressure by mechanisms involving matrix metalloproteinases (MMPs). Recent findings have revealed that MMP type two (MMP‐2) seems to cleave ...vasoactive peptides. This study examined whether MMP‐2 and MMP‐9 levels/activities increase after acute intoxication with low lead concentrations and whether these changes were associated with increases in blood pressure and circulating endothelin‐1 or with reductions in circulating adrenomedullin and calcitonin gene‐related peptide (CGRP). Here, we expand previous findings and examine whether doxycycline (a MMPs inhibitor) affects these alterations. Wistar rats received intraperitoneally (i.p.) 1st dose 8 μg/100 g of lead (or sodium) acetate, a subsequent dose of 0.1 μg/100 g to cover daily loss and treatment with doxycycline (30 mg/kg/day) or water by gavage for 7 days. Similar whole‐blood lead levels (9 μg/dL) were found in lead‐exposed rats treated with either doxycycline or water. Lead‐induced increases in systolic blood pressure (from 143 ± 2 to 167 ± 3 mmHg) and gelatin zymography of plasma samples showed that lead increased MMP‐9 (but not MMP‐2) levels. Both lead‐induced increased MMP‐9 activity and hypertension were blunted by doxycycline. Doxycycline also prevented lead‐induced reductions in circulating adrenomedullin. No significant changes in plasma levels of endothelin‐1 or CGRP were found. Lead‐induced decreases in nitric oxide markers and antioxidant status were not prevented by doxycycline. In conclusion, acute lead exposure increases blood pressure and MMP‐9 activity, which were blunted by doxycycline. These findings suggest that MMP‐9 may contribute with lead‐induced hypertension by cleaving the vasodilatory peptide adrenomedullin, thereby inhibiting adrenomedullin‐dependent lowering of blood pressure.
Coronavirus disease (COVID-19) has created an unprecedented devastation and the loss of millions of lives globally. Contagious nature and fatalities invariably pose challenges to physicians and ...healthcare support systems. Clinical diagnostic evaluation using reverse transcription-polymerase chain reaction and other approaches are currently in use. The Chest X-ray (CXR) and CT images were effectively utilized in screening purposes that could provide relevant data on localized regions affected by the infection. A step towards automated screening and diagnosis using CXR and CT could be of considerable importance in these turbulent times. The main objective is to probe a simple threshold-based segmentation approach to identify possible infection regions in CXR images and investigate intensity-based, wavelet transform (WT)-based, and Laws based texture features with statistical measures. Further feature selection strategy using Random Forest (RF) then selected features used to create Machine Learning (ML) representation with Support Vector Machine (SVM) and a Random Forest (RF) to make different COVID-19 from viral pneumonia (VP). The results obtained clearly indicate that the intensity and WT-based features vary in the two pathologies that are better differentiated with the combined features trained using SVM and RF classifiers. Classifier performance measures like an Area Under the Curve (AUC) of 0.97 and by and large classification accuracy of 0.9 using the RF model clearly indicate that the methodology implemented is useful in characterizing COVID-19 and Viral Pneumonia.
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