A New Optimal Diagnosis System for Coronavirus (COVID-19) Diagnosis Based on Archimedes Optimization Algorithm on Chest X-Ray Images

The new coronavirus, COVID-19, has affected people all over the world. Coronaviruses are a large group of viruses that can infect animals and humans and cause respiratory distress; these discomforts may be as mild as a cold or as severe as pneumonia. Correct detection of this disease can help to avoid its spreading increasingly. In this paper, a new CAD-based approach is suggested for the optimal diagnosis of this disease from chest X-ray images. The proposed method starts with a min-max normalization to scale all data into a normal scale, and then, histogram equalization is performed to improve the quality of the image before main processing. Afterward, 18 different features are extracted from the image. To decrease the method difficulty, the minimum features are selected based on a metaheuristic called Archimedes optimization algorithm (AOA). The model is then implemented on three datasets, and its results are compared with four other state-of-the-art methods. The final results indicated that the proposed method with 86% accuracy and 96% precision has the highest balance between accuracy and reliability with the compared methods as a diagnostic system for COVID-19.

Integral stochastic ordering of the multivariate normal mean-variance and the skew-normal scale-shape mixture models

‎In this paper‎, ‎we introduce integral stochastic ordering of two‎ most important classes of distributions that are commonly used to fit data possessing high values of skewness and (or)‎ ‎kurtosis‎. ‎The first one is based on the selection distributions started by the univariate skew-normal distribution‎. ‎A broad‎, ‎flexible and newest class in this area is the scale and shape mixture of multivariate skew-normal distributions‎. ‎The second one is the general class of Normal Mean-Variance Mixture distributions‎. ‎We then derive necessary and sufficient conditions for comparing the random vectors from these two classes of distributions‎. ‎The integral orders considered here are the usual‎, ‎concordance‎, ‎supermodular‎, ‎convex‎, ‎increasing convex and directionally convex stochastic orders‎. ‎Moreover‎, ‎for bivariate random vectors‎, ‎in the sense of stop-loss and bivariate concordance stochastic orders‎, ‎the dependence strength of random portfolios is characterized in terms of order of correlations‎.

Genetic control of coppice regrowth in Eucalyptus spp.

Forest companies prefer a coppice system as a silvicultural strategy owing to its economic and sustainability advantages compared to developing new plantations for second rotations. However, studies aiming to determine the selection of superior genetic material for this management strategy are scarce. In this study, we evaluated five clonal tests of Eucalyptus spp. located in Itatinga and Angatuba, São Paulo State, Brazil, to determine the genetic correlations and control of productivity for regrowth management in two rotations. The volume (m3) and survival of the Eucalyptus spp. clonal tests were determined for the two rotations at 5.5 years of age. The experiments were carried out in a randomized block design with six replicates, five plants per plot, and unbalanced treatments. The heritability in the normal scale (\hat h_n^2) for the survival ranged from 0.056 to 0.11, the heritability in the broad sense (\hat h_g^2) ranged from 0.205 to 0.334, and the genotypic correlation was positive and high (0.71-0.86), and statistically significant to the genetic means for the two rotations. The ranking of the best clones in the second rotation was similar (76 %) to their ranking in the first selection. Thus, for the evaluated material, there was no need for the second measurement to obtain accurate selection when managing a coppice system.

ARQUEOLOGÍA DE SUPERFICIE EN TAJÍN

El sitio arqueológico de Tajín es considerado como el más importante de la Costa del Golfo, México, ubicada en una superficie de 144 hectáreas, emplazada en área de pequeñas colinas con cuencas abierta y cerradas, en una sucesión de plazas arquitectónicas edificada en plataformas semi-artificiales de manera estratificada. Edificios con terrazas soportadas por columnas cilíndricas, techos planos de gran envergadura y complejidad. Además de presentar una arquitectura sofisticada a base de lajas que dan forma a los nichos, grecas y cornisa volada, también contiene esculturas en piedra de volumen mediano y figuras a escala humana modeladas en estuco. Presenta 17 juegos de pelota y eso es un indicador de la religiosidad de sus habitantes y sus habituales, representaciones del ritual plasmado en 6 tableros usando la técnica de bajorelieves. Aquí, también, encontramos pinturas a escala normal y en miniatura. Es inconmensurable la riqueza iconográfica que marcan los hechos más relevantes de sus gobernantes.SURFACE ARCHEOLOGY IN TAJÍN ABSTRACTThe archaeological site of Tajín is considered as the most important of the Gulf Coast, Mexico, located in an area of 144 hectares, located in an area of small hills with open and closed basins, in a succession of architectural squares built on semiartificial platforms of stratified way. Buildings with terraces supported by cylindrical columns, planes of great scope and complexity. In addition to presenting a sophisticated architecture, a basis of the law that shapes the niches, fretwork and flown cornice, it also contains stone sculptures of medical volume and figures in a human scale modeled in stucco. It presents 17 ball games and that is an indicator of the religiosity of its inhabitants and their regulars, representations of the ritual embodied in 6 paintings using the technique of bas-reliefs. Here, too, we find paintings on a normal scale and in miniature. The iconographic wealth that marks the most relevant events of its rulers is immeasurable.Key words: Archeology, Tajín, Complexity, Painting, Iconography

Bendability of Shot Blasted Ultrahigh-Strength Steels

The effect of shot blasting on the bendability of two tempered trial ultrahigh-strength steels has been studied by comparing the bending behaviour of otherwise identical plates with and without shot blasting. The yield strength of the studied 10 mm thick trial steel was 700 MPa and 7.5 mm trial steel 1100 MPa. The local microstructures below the different surfaces were characterized using laser scanning confocal microscopy and FESEM. Microhardness profiles and surface roughness (Raand Rz) were measured and bendability was determined using three-point brake press bending. Shot blasting was found to decrease the bendability of both steels. For the 700 MPa steel shot blasting increased the surface roughness metric Rasubstantially from 7.4 μm with the normal scale surface to 12.6 μm, and for the 1100 MPa steel from 2.8 μm to 6.8 μm. For the 700 MPa steel with the bend axis parallel to rolling direction, the minimum usable punch radius for defect-free bends with normal scale surfaces was 13 mm (1.3 x thickness) and for the 1100 MPa steel, 14 mm (1.9 x thickness), while for shot blasted surfaces corresponding values were respectively 20 mm (2.0 x thickness) and 18 mm (2.4 x thickness). All of these values are excellent considering the strength levels involved. Shot blasting increased the subsurface hardness and introduced work hardening of surface layers. Possible explanations for the observed effects of shot blasting on the bendability are discussed.

WRF Model Study of the Great Plains Low-Level Jet: Effects of Grid Spacing and Boundary Layer Parameterization

Previous studies have shown that the Weather Research and Forecasting (WRF) Model often underpredicts the strength of the Great Plains nocturnal low-level jet (NLLJ), which has implications for weather, climate, aviation, air quality, and wind energy in the region. During the Lower Atmospheric Boundary Layer Experiment (LABLE) conducted in 2012, NLLJs were frequently observed at high temporal resolution, allowing for detailed documentation of their development and evolution throughout the night. Ten LABLE cases with observed NLLJs were chosen to systematically evaluate the WRF Model’s ability to reproduce the observed NLLJs. Model runs were performed with 4-, 2-, and 1-km horizontal spacing and with the default stretched vertical grid and a nonstretched 40-m vertically spaced grid to investigate which grid configurations are optimal for NLLJ modeling. These tests were conducted using three common boundary layer parameterization schemes: Mellor–Yamada Nakanishi Niino, Yonsei University, and Quasi-Normal Scale Elimination. It was found that refining horizontal spacing does not necessarily improve the modeled NLLJ wind. Increasing the number of vertical levels on a non-stretched grid provides more information about the structure of the NLLJ with some schemes, but the benefit is limited by computational expense and model stability. Simulations of the NLLJ were found to be less sensitive to boundary layer parameterization than to grid configuration. The Quasi-Normal Scale Elimination scheme was chosen for future NLLJ simulation studies.

Estimation of gillnet and hook selectivity for Carangoides fulvoguttatus (Forsskal, 1775) captured off Kanyakumari coast of India

Selectivity and fishing powers of multi-mesh gillnets with mesh sizes of 13.5, 14, 14.5 and 15 cm and hooks No. 5, 6, 7 and 8 were studied using the experimental catch data of the carangid Carangoides fulvoguttatus. (Forsskal, 1775). The selectivity curves, parameters and residual plots for different models viz., normal scale, normal location, log-normal, gamma and bi-normal models were produced applying the SELECT (Share Each Length Class Total) methodology which has been incorporated in the software GILLNET (Generalised Including Log-Linear N Estimation Technique). The models were evaluated using the statistical tools viz., model deviance, dispersion parameter and residual plots to determine the best fit of the selectivity data. The uni-normal model, normal scale was found as best fit for the gillnet catch data while bi-normal was identified as suitable model for the hook catch data. The mesh size of 14.5 cm and hook No. 5 performed better than the other modeled meshes and hooks respectively. Gillnet selectivity data did not converge into bi-normal model due to single mode of capture. However, the hook catch data converged into bi-normal model with two modes of selection curve. Over dispersion was found common in catch data obtained from both gears due to larger size of fishes caught and demonstrated lack of fit in both selection data.