Background: The internally displaced children are vulnerable groups have less access to dental services, worse oral health, and bear a disproportionate burden of oral diseases. Aim of the study: This study was conducted on group of internally displaced children living in Baghdad governorate camps to measure their dental caries prevalence and experience and find out the association between dental caries and the duration of displacement in camps. Subjects and methods: A sample of 1393 children were selected, 567 internally displaced children from camps in Baghdad governorate and 826 school children as control matching in age and gender. The age of children ranged from 5-12 years old. Oral examination was performed using WHO 2013 criteria, to

Three different distribution modules of silicon solar cells in a panel are used in this study . Each module consists of five identical circular silicon solar cells of radius (5cm) and then the total panel areas are identical. The five solar cells are arranged in the panel in different shapes: circular, triangular and rectangular .The efficiency for these three panel distribution are measured indoor and outdoor. The results show that the efficiency is a function of the cells distribution.

Abstract In the current contribution, a novel binuclear nickel(II) and zinc(II) complexes were prepared from a hexadentate ligand prepared via condensation of 3,3'-Bipyridine-6,6'-dicarbaldehyde , 2-amino-5-chlorobenzaldehyde and 2-Aminophenol .The symmetric ligand (H2DTPE) and its metal complexes were illustrated utilizing various techniques of physicochemical containing magnetic moment, analytical analysis and spectroscopy of mass, IR, 13C and 1H NMR, TGA and UV-Vis. The particles of MO Nanoscale were created from the labeled complex applying the ways of pyrolysis and utilizing methods of XRD, FT-IR, and FE-SEM, that specified close compatibility with the typical pattern for nanoparticles of NiO, ZnO and appeared the reasonable size in

Biogenic gold nanoparticles (AuNPs) were synthesized using broccoli extract to assess their antioxidant activity, wound-healing potential, and selective anticancer effects. Green synthesis with broccoli offers an environmentally friendly way to produce stable and biocompatible nanomaterials. In this study, Brassica oleracea aqueous extract served as both the reducing and capping agent, producing AuNPs with a characteristic surface plasmon resonance peak at 560 nm and a well-defined cubic crystalline structure confirmed by XRD. TEM analysis showed uniformly dispersed, semi-spherical nanoparticles with an average size of 7.5 ± 3.6 nm. The biosynthesized AuNPs exhibited potent antioxidant activity, achieving 91.2 % DPPH scavenging at 100 µg/

In this article the nanoparticles synthesis of ZnO (Nps) by using the precipitation method at concentrations range (0.5, 0.25, 0.125, 0.0625, 0.03125) mg/mL and then activity was examined against Streptococcus spp that causing dental caries in vitro by well diffusion method, find these concentrations effected in these bacteria and better concentration is 0.03125. ZnO Nps were characterization by EDS to prove this particles are ZnO, and also characterized by atomic force microscope (AFM), X-ray Diffraction (XRD) and TEM, from these technic found that the average size about 30.52 nm and hexagonal shape. The UV-visible result reveals that the large band is observed at 340.8 nm, Zeta potential show that the surface charge is 30.19 mv an

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi