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9638. Ultimately, this paper illustrates the viability of a novel machine learning pipeline to automate the classification of undifferentiated and differentiated cells. In the future, this research could aid in automated strategies that determine the viability of MHC-like cells after differentiation.Coronavirus pandemic (COVID-19) has infected more than ten million persons worldwide. Therefore, researchers are trying to address various aspects that may help in diagnosis this pneumonia. Image segmentation is a necessary pr-processing step that implemented in image analysis and classification applications. Therefore, in this study, our goal is to present an efficient image segmentation method for COVID-19 Computed Tomography (CT) images. The proposed image segmentation method depends on improving the density peaks clustering (DPC) using generalized extreme value (GEV) distribution. The DPC is faster than other clustering methods, and it provides more stable results. However, it is difficult to determine the optimal number of clustering centers automatically without visualization. So, GEV is used to determine the suitable threshold value to find the optimal number of clustering centers that lead to improving the segmentation process. The proposed model is applied for a set of twelve COVID-19 CT images. Also, it was compared with traditional k-means and DPC algorithms, and it has better performance using several measures, such as PSNR, SSIM, and Entropy.Smear-positive pulmonary tuberculosis (PTB) is more infectious compared to smear-negative PTB and have great significance for epidemiology and infection control. The prevalence of smear-positive PTB rarely affects males and females equally. L-SelenoMethionine solubility dmso Hence, we aimed to identify the sex-related differences in the prevalence of smear-positive PTB and its associated factors in Kuala Lumpur, Malaysia. A cross-sectional study was conducted using data from the National Tuberculosis Information System (TBIS) from 1 January, 2015, to 31 December, 2019. The study population was selected using simple random sampling from the list of registered PTB patients in TBIS. The criteria for inclusion were all Malaysian adults aged ≥18 years residing in Kuala Lumpur and registered as PTB in TBIS. Factors associated with smear-positive PTB in male and female patients were determined using multiple logistic regression analysis. Overall prevalence of smear-positive PTB was 68.6%, and male patients predominated (71%). The malefemale prevalence ratio of smear-positive PTB was 2.41. Male patients who worked as machine operators and elementary workers (adjusted odds ratio (aOR) 2.23, 95% confidence interval (CI) 1.24-4.02, p = 0.007), were self-employed (aOR 2.58, 95% CI 1.46-4.56, p = 0.001), lived in a residence categorized as 'other' (aOR 2.49, 95% CI 1.28-4.86, p = 0.007) and were smokers (aOR 1.37, 95% CI 1.01-1.87, p = 0.045) had higher odds for smear-positive PTB. Meanwhile, female patients with diabetes mellitus had higher odds for smear-positive PTB (aOR 1.92, 95% CI 1.05-3.54, p = 0.035), while female patients who were healthcare workers had lower odds (aOR 0.33, 95% CI 0.12, 0.94, p = 0.039). The prevalence of smear-positive PTB is higher in males compared to females. The factors associated with smear-positive PTB differed based on sex. The current TB control program, especially on smear-positive PTB, should likely be strategized and stratified by sex.Auditory masking occurs when one sound is perceptually altered by the presence of another sound. Auditory masking in the frequency domain is known as simultaneous masking and in the time domain is known as temporal masking or non-simultaneous masking. This works presents a sound coding strategy that incorporates a temporal masking model to select the most relevant channels for stimulation in a cochlear implant (CI). A previous version of the strategy, termed psychoacoustic advanced combination encoder (PACE), only used a simultaneous masking model for the same purpose, for this reason the new strategy has been termed temporal-PACE (TPACE). We hypothesized that a sound coding strategy that focuses on stimulating the auditory nerve with pulses that are as masked as possible can improve speech intelligibility for CI users. The temporal masking model used within TPACE attenuates the simultaneous masking thresholds estimated by PACE over time. The attenuation is designed to fall exponentially with a strength deteronsideration of short-acting temporal masking can improve speech intelligibility in CI users. The half-live with the highest average speech perception benefit (0.5 ms) corresponds to time scales that are typical for neuronal refractory behavior.The tetraploid Avena species in the section Pachycarpa Baum, including A. insularis, A. maroccana, and A. murphyi, are thought to be involved in the evolution of hexaploid oats; however, their genome designations are still being debated. Repetitive DNA sequences play an important role in genome structuring and evolution, so understanding the chromosomal organization and distribution of these sequences in Avena species could provide valuable information concerning genome evolution in this genus. In this study, the chromosomal organizations and distributions of six repetitive DNA sequences (including three SSR motifs (TTC, AAC, CAG), one 5S rRNA gene fragment, and two oat A and C genome specific repeats) were investigated using non-denaturing fluorescence in situ hybridization (ND-FISH) in the three tetraploid species mentioned above and in two hexaploid oat species. Preferential distribution of the SSRs in centromeric regions was seen in the A and D genomes, whereas few signals were detected in the C genomes. Some intergenomic translocations were observed in the tetraploids; such translocations were also detected between the C and D genomes in the hexaploids. These results provide robust evidence for the presence of the D genome in all three tetraploids, strongly suggesting that the genomic constitution of these species is DC and not AC, as had been thought previously.Butterfly Optimization Algorithm (BOA) is a recent metaheuristics algorithm that mimics the behavior of butterflies in mating and foraging. In this paper, three improved versions of BOA have been developed to prevent the original algorithm from getting trapped in local optima and have a good balance between exploration and exploitation abilities. In the first version, Opposition-Based Strategy has been embedded in BOA while in the second Chaotic Local Search has been embedded. Both strategies Opposition-based & Chaotic Local Search have been integrated to get the most optimal/near-optimal results. The proposed versions are compared against original Butterfly Optimization Algorithm (BOA), Grey Wolf Optimizer (GWO), Moth-flame Optimization (MFO), Particle warm Optimization (PSO), Sine Cosine Algorithm (SCA), and Whale Optimization Algorithm (WOA) using CEC 2014 benchmark functions and 4 different real-world engineering problems namely welded beam engineering design, tension/compression spring, pressure vessel design, and Speed reducer design problem.
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