Mosquitoes play a serious role on public health transmitting several dangerous diseases such as malaria, filariasis and Encephalitis. So it consider as a vector diseases. Therefor it is important to control its spread using ecology friend’s factors like bacteria Bacillus thuringiensis var. israelensis and fungi Beauveria bassiana. Results revealed that the direct effect of Bacillus thuringiensis on the larvae led to the high mortality (100%) during 3 days while Beauveria bassiana have a cumulative effect on the Mosquito stage lifecycle; 7.3 X 104 more significant effect in the first day but there was no significant in the other days of treatment. In the end period of lifecycle there was no adult emergence and the adult which emergence up

This study focuses on the biodegradation of oxymatrine insecticide by some soil fungi isolated from four agriculture stations. The results showed that the highest degradation rate 94.66% was recorded by Ulocladium sp. at 10 days and A. niger recorded the lowest degradation rate 45.86%, while at 20 days Ulocladium sp. also showed the highest degradation rate 94.98% and the lowest degradation rate reached to 82.49% with A.niger. The mix (Exerohilum sp.+Ulocladium sp.) recorded the highest degradation rate of oxymatrine insecticide 90.22%, 88.51%, 85.34%  at 4, 8 and 12 ppm.The use of mixed isolates enhanced the biodegradation process. There is no study of oxymatrine biodegradation

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

The present study was conducted to evaluate the effect of fungi Gigaspora margarita and Glomus desriticola in stimulating the resistance of the capsicum annuum L. towards the chromium and lead after 60 days, planting and using the pots in the glass house. The highest concentration of chromium and lead in the root was found in the presence of the mycorrhizal mixture (194.93, 150.40) μg / g, respectively, compared to the lowest concentration (90.69, 79.37) μg / g respectively, while the highest concentration of chromium and lead in the shoot was found in the presence of the mycorrhizal mixture (94.63, 79.33) μg / g respectively, compared with the lowest concentration in the control treatment (72.58, 60.70) μg / g respectively. The results

Background: The Epstein-Barr virus (EBV) relates to the torch virus family and is believed to have a substantial impact on mortality and perinatal events, as shown by epidemiological and viral studies. Moreover, there have been documented cases of EBV transmission occurring via the placenta. Nevertheless, the specific location of the EBV infection inside the placenta remains uncertain. Methods: The genomic sequences connected to the latent EBV gene and the levels of lytic EBV gene expression in placental chorionic villous cells are examined in this work. A total of 86 placentas from patients who had miscarriage and 54 placentas from individuals who had successful births were obtained for analysis. Results: The research employed QPCR to dete

This study aimed to detect Anaplasma phagocytophilum in horses through hematological and molecular tests. The 16S rRNA gene of the Anaplasma phagocytophilum parasite was amplified by polymerase chain reaction (PCR), then sequenced, and subjected to phylogenetic analysis to explore "Equine Granulocytic Anaplasmosis" (EGA) infection in three important gathering race horses areas in Baghdad governorate, Iraq. Blood samples were obtained from 160 horses of varying ages, three breeds, and both sexes, between January and December 2021. Prevalence and risk variables for anaplasmosis were analyzed using statistical odds ratio and chi-square tests. Results demonstrated that clinical anaplasmosis symptoms comprised jaundice, wei

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in