With the aim of developing potential antimicrobials, a series of new 5-fluoroisatin derivatives incorporated with different secondary amines (piperidine, morpholine, pyrrolidine, dimethylamine, and diphenylamine) for monomer, and (piperazine) in case of dimer Mannich bases, separately in presence of formaldehyde to obtain Mannich bases of 5-fluoroisatin derivatives, which then each Mannich derivatives reacts with phenylhydrazine to form Schiff bases as final products. The resulting compounds were characterized by two spectroscopic analyses; (Fourier- transform infrared) FT-IR and proton nuclear magnetic resonance spectroscopy (¹H-NMR). In addition, the in vitro antibacterial and antifungal activities were tested against some human pathogen

This research set out to provide a faster, easier, and more efficient process for nanoparticle (NP) synthesis of aluminum oxide NPs preparation by microwave irradiation, using plant extracts separately and in the same way (tea, coffee, rosemary), which is an easy-to-use and inexpensive method. The structural properties were investigated by X-ray diffractometer analysis technique (XRD). The X-ray analysis shows the structure has a polycrystalline nature with a hexagonal phase. The optical properties were studied using ultraviolet visible (UV-Vis) spectrometer, where the energy gap was determined. The surface morphology properties of the prepared aluminum NPs were examined by atomic force microscope (AFM). The Fourier transform infra

In this article, Pb2Ba1.7Sr0.3Ca2Cu3O10+δ superconductor material was synthesized using conventional solid-state reaction method. X-ray diffraction (XRD) analysis demonstrated one dominant phase 2223 and some impurities in the product powder. The strongest peaks in the XRD pattern were successfully indexed assuming a pseudo-tetragonal cell with lattice constants of a = 3.732, b = 3.733 and c = 14.75 Å for a Pb-Based compound. The crystallite size and lattice strain between the layers of the studied compound were estimated using several methods, namely the Scherrer, Williamson-Hall (W.H), sizestrain plot (SSP) and Halder Wagner (H.W) approach. The values of crystallite size, calculated by Scherrer, W.H, SSP and H.W methods, were 89.454077

A field study was conducted at the college of Agriculture, Baghdad University-Jadiriyah to investigate the effect of adding potassium fertilizer and organic nutrient (Reef Amirich) on the population density of two sucking pests of cucumber, cotton whitefly, Bemisia tabaci and onion thrips, Thrips tabaci during the spring season/2016. Results indicated that potassium sulphate (50, 100 and 150 kg/ha) and organic nutrient (0.8 and 1.6ml/l) reduced both the population density of B. tabaci and T. tabaci nymphs depending on the fertilizer level of the user, the treatment 150 kg/ha for the potassium fertilizer and 1.6 ml/L for organic nutrient was the highest among others when minimized density of nymphs by 1.62 nymphs of B. tabaci/disk leaf and 0

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

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

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p