RESONANT BRILLOUIN-SCATTERING IN SPATIALLY DISPERSIVE MEDIUM

45NC-5616

An ACA Accelerated isogeometric boundary element analysis of potential problems with non-uniform boundary conditions

This paper presents an Adaptive Cross Approximation (ACA) accelerated Isogeometric Boundary Element Method (IGBEM) using Non-Uniform Rational B-Splines (NURBS) as shape and interpolation functions. Provided that NURBS are used in CAD programs to describe geometry, mesh generation in the IGBEM is no longer necessary. For large and complex models the traditional BEM quickly becomes very time and memory consuming. In order to overcome this problem, the use of ACA is considered in this paper. As the NURBS control points are typically located outside the boundary, non-uniform boundary conditions cannot be applied at control points. So, a transformation matrix is used to allow the application of boundary conditions at control points without losing accuracy and, with a special approach, preserving the time and memory advantages of hierarchical matrices provided by the ACA. Two and tree dimensional numerical examples are presented in order to assess the accuracy and feasibility of the method

Prevalence of peripheral arterial disease in patients with heart failure with preserved ejection fraction

OBJECTIVES: To describe the prevalence of the reduced ankle-brachial index (ABI) in patients with heart failure (HF) with preserved ejection fraction (HFpEF) attended at a HF clinic in the metropolitan region of Porto Alegre, and to compar the patients to those with reduced ejection fraction (HFrEF). METHODS: A descriptive observational study, included patients referred to the heart failure clinic in HU-Ulbra with HFpEF or HFrEF and diastolic dysfunction, and measurements of ABIs using vascular Doppler equipment were performed in both groups. RESULTS: The sample consisted of 106 patients with HF, 53.9% of the patients had HFpEF, and 19.4% had a diagnosis of peripheral arterial disease (PAD) (ABI less than 0.9). PAD was identified in 24.1% of the patients with HFpEF, while15.8% of patients in the HFrEF group were diagnosed with PAD. CONCLUSION: Our results did not identify a significantly different prevalence of altered and compatible PAD values in patients with HFpEF. However, we showed a prevalence of 19.4%, a high value if we consider similar populations

Comparison of Clinical Efficacy between a Single Administration of Long-Acting Gonadotrophin-Releasing Hormone Agonist (GnRHa) and Daily Administrations of Short-Acting GnRHa in In Vitro Fertilization-Embryo Transfer Cycles

This study was aimed to evaluate the efficacy of a single administration of long-acting gonadotrophin-releasing hormone agonist (GnRHa) as compared with daily administrations of short-acting GnRHa in controlled ovarian hyperstimulation (COH) for in vitro fertilization and embryo transfer (IVF-ET) cycles. The mean dosage of recombinant follicle-stimulating hormone (rFSH) required for COH (2,354.5±244.2 vs. 2,012.5±626.1 IU) and the rFSH dosage per retrieved oocyte (336.7±230.4 vs. 292.1±540.4 IU) were significantly higher in the long-acting GnRHa group (N=22) than those in the short-acting GnRHa group (N=28) (p<0.05). However, the mean number of visit to the hospital that was required before ovum pick-up (3.3±0.5 vs. 22.2±2.0) and the frequency of injecting GnRHa and rFSH (12.8±1.2 vs. 33.5±3.5) were significantly decreased in the long-acting GnRHa group (p<0.0001). The clinical pregnancy rate, implantation rate, and early pregnancy loss rate were not significantly different between the 2 groups. So, we suggest that a single administration of long-acting GnRHa is a useful alternative for improving patient's convenience with clinical outcomes comparable to daily administrations of short-acting GnRHa in COH for IVF-ET cycles

Automatic Detection of Malignant Masses in Digital Mammograms Based on a MCET-HHO Approach

Digital image processing techniques have become an important process within medical images. These techniques allow the improvement of the images in order to facilitate their interpretation for specialists. Within these are the segmentation methods, which help to divide the images by regions based on different approaches, in order to identify details that may be complex to distinguish initially. In this work, it is proposed the implementation of a multilevel threshold segmentation technique applied to mammography images, based on the Harris Hawks Optimization (HHO) algorithm, in order to identify regions of interest (ROIs) that contain malignant masses. The method of minimum cross entropy thresholding (MCET) is used to select the optimal threshold values for the segmentation. For the development of this work, four mammography images were used (all with presence of a malignant tumor), in their two views, craniocaudal (CC) and mediolateral oblique (MLO), obtained from the Digital Database for Screening Mammography (DDSM). Finally, the ROIs calculated were compared with the original ROIs of the database through a series of metrics, to evaluate the behavior of the algorithm. According to the results obtained, where it is shown that the agreement between the original ROIs and the calculated ROIs is significantly high, it is possible to conclude that the proposal of the MCET-HHO algorithm allows the automatic identification of ROIs containing malignant tumors in mammography images with significant accuracy.Digital image processing techniques have become an important process within medical images. These techniques allow the improvement of the images in order to facilitate their interpretation for specialists. Within these are the segmentation methods, which help to divide the images by regions based on different approaches, in order to identify details that may be complex to distinguish initially. In this work, it is proposed the implementation of a multilevel threshold segmentation technique applied to mammography images, based on the Harris Hawks Optimization (HHO) algorithm, in order to identify regions of interest (ROIs) that contain malignant masses. The method of minimum cross entropy thresholding (MCET) is used to select the optimal threshold values for the segmentation. For the development of this work, four mammography images were used (all with presence of a malignant tumor), in their two views, craniocaudal (CC) and mediolateral oblique (MLO), obtained from the Digital Database for Screening Mammography (DDSM). Finally, the ROIs calculated were compared with the original ROIs of the database through a series of metrics, to evaluate the behavior of the algorithm. According to the results obtained, where it is shown that the agreement between the original ROIs and the calculated ROIs is significantly high, it is possible to conclude that the proposal of the MCET-HHO algorithm allows the automatic identification of ROIs containing malignant tumors in mammography images with significant accuracy

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models

Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw) and herd-year-season-management (RRMw-m) groups for mean W450, standard deviations of herd-year (RRMg) and herd-year-season-management (RRMg-m) groups adjusted for 365-450 days weight gain (G450) averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively). The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001)

Ichthyofauna Used in Traditional Medicine in Brazil

Fish represent the group of vertebrates with the largest number of species and the largest geographic distribution; they are also used in different ways by modern civilizations. The goal of this study was to compile the current knowledge on the use of ichthyofauna in zootherapeutic practices in Brazil, including ecological and conservational commentary on the species recorded. We recorded a total of 85 species (44 fresh-water species and 41 salt-water species) used for medicinal purposes in Brazil. The three most commonly cited species were Hoplias malabaricus, Hippocampus reidi, and Electrophorus electricus. In terms of conservation status, 65% of species are in the “not evaluated” category, and 14% are in the “insufficient data” category. Three species are in the “vulnerable” category: Atlantoraja cyclophora, Balistes vetula, and Hippocampus erectus. Currently, we cannot avoid considering human pressure on the population dynamics of these species, which is an essential variable for the conservation of the species and the ecosystems in which they live and for the perpetuation of traditional medical practices

Casbane diterpene as a promising natural antimicrobial agent against biofilm-associated infections

Croton nepetaefolius is a native plant from northeastern Brazil that belongs to the Euphorbiaceae family. The biological action of this plant has been extensively explored, being the secondary metabolites responsible for its properties alkaloids, diterpenes, and triterpenes. This study aimed to evaluate the ability of casbane diterpene (CD), isolated from the ethanolic extract of C. nepetaefolius, to inhibit microbial growth and biofilm formation of several clinical relevant species (bacteria and yeasts). It was found that CD possessed biocidal and biostatic activity against the majority of the species screened, with minimal active concentrations ranging between 125 and 500 µg/mL. In addition, it was observed that biofilm formation was inhibited even when the planktonic growth was not significantly affected. In conclusion, CD showed potential to be a natural tool for the treatment of diseases caused by different infectious microorganismsThis study was supported by FUNCAP and CNPq (Brazil) and by FCT (Portugal) through the project PTDC/SAU-ESA/64609/2006

Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics