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1. Effects of the nutrition of different diets and lipid content of the insect host larvae, Galleria mellonella on the efficacy of indigenous entomopathogenic nematodes

Author

Mona Ahmed Hussein, Hamdy Abdelnaby Salem, Sayed Hala, and Salah Mahmoud

Subjects
diets, galleria mellonella, heterorhabditis bacteriophora, lipids, multiplication, pathogenicity, steinernema carpocapsae, Plant culture, SB1-1110
Abstract

Entomopathogenic nematodes (EPNs) are promising as biocontrol agents for the most economically important insect pest attacking a wide range of host plants. Therefore, the aim of this work was to study the impact of four artificial diets and one natural food on numbers, weights, and total lipid content of the greater wax moth larvae, Galleria mellonella (Linnaeus) (Lepidoptera: Pyralidae) as well as the impact of these diets on the ability of nematode species Heterorhabditis bacteriophora and Steinernema carpocapsae to infect insects and multiply inside an insect host which had been reared on one of five different diets (D1, D2, D3, D4 and D5). The correlation between larvae weight and total lipid content, pathogenicity or multiplication of nematodes was also studied. The obtained results indicated that D2, D5 and D3 gave the highest growth or weights of larvae. The larvae produced weighed 3.71, 3.67 and 3.25 g from 50 g media, respectively. Statistically, larvae weights had a positive and significant correlation with the lipid content in larvae where r = 0.732. On the other hand, infective juveniles (IJs) of nematodes produced from insect hosts reared on D2 and D5 revealed more pathogenicity on larvae, since they caused the highest percent of mortality, 53.33 and 50.0% for H. bacteriophora, and 56.67 and 53.33% for S. carpocapsae, respectively. The total lipid content had a positive and highly significant correlation with the pathogenicity of the two nematode species where r = 0.97 and 0.971, respectively. Ultimately, the supplied foods of the artificial diets D2, D3 and natural beeswax (D5) gave the most suitable chance for developing insect growth and increasing the EPN quality and enhancing the potential of EPNs as biological control agents against different insect pests.

Published
2022
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33. Efficient COVID-19 super pixel segmentation algorithm using MCFO-based SLIC.

Author

Faragallah, Osama S., El-Hoseny, Heba M., and El-Sayed, Hala S.

Abstract

In computer vision segmentation field, super pixel identity has become an important index in the recently segmentation algorithms especially in medical images. Simple Linear Iterative Clustering (SLIC) algorithm is one of the most popular super pixel methods as it has a great robustness, less sensitive to the image type and benefit to the boundary recall in different kinds of image processing. Recently, COVID-19 severity increased with the lack of an effective treatment or vaccine. As the Corona virus spreads in an unknown manner, th-ere is a strong need for segmenting the lungs infected regions for fast tracking and early detection, no matter how small. This may consider difficult to be achieved with traditional segmentation techniques. From this perspective, this paper presents an efficient modified central force optimization (MCFO)-based SLIC segmentation algorithm to discuss chest CT images for detecting the positive COVID-19 cases. The proposed MCFO-based SLIC segmentation algorithm performance is evaluated and compared with the thresholding segmentation algorithm using different evaluation metrics such as accuracy, boundary recall, F-measure, similarity index, MCC, Dice, and Jaccard. The outcomes demonstrated that the proposed MCFO-based SLIC segmentation algorithm has achieved better detection for the small infected regions in CT lung scans than the thresholding segmentation. [ABSTRACT FROM AUTHOR]

Published
2023
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