A critical milestone in nano-biotechnology is establishing reliable and ecological friendly methods for fabricating metal oxide NPs. Because of their great biodegradable, electrical, mechanical, and optical qualities, zirconia NPs (ZrO2NPs) attract much interest among all zirconia NPs (ZrO2NPs). Zirconium oxide (ZrO2) has piqued the interest of researchers throughout the world, particularly since the development of methods for the manufacture of nano-sized particles. An extensive study into the creation of nanoparticles utilizing various synthetic techniques and their potential uses has been stimulated by their high luminous efficiency, wide bandgap, and high exciton binding energy. Zirconium dioxide nanoparticles may be used as antimicrobial and anticancer agents in food packaging. In response to the growing interest in nano ZrO2, researchers invented and developed methods for synthesizing nanoparticles. ZrO2 nanocomposites with various morphologies have recently been created using biological (green chemistry) methods. Microbes and plants both contribute to the production of zirconia in the laboratory. Capping and stabilizing agents are provided by the biomolecules found in plant extracts, whereas microorganisms provide enzymes as capping and stabilizing agents (intracellular or extracellular). It is possible to analyze the nanoparticles produced using a variety of analytical approaches, including ultraviolet-visible spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), and Fourier transform infrared spectroscopy (FT-IR). When applied to bacteria (both Gram-positive and Gram-negative) and fungi, ZrO2NPs show promising antibacterial capabilities. Normal and malignant cells are sensitive to ZrO2 nanoparticles, which can be explained by the generation of reactive oxygen (ROS). This work discusses and describes many ways of producing ZrO2 nanoparticles, their properties, and various application possibilities.
A new ligand complexes have been synthesis from reaction of metal ions of MnII , CoII , NiII , CuII , ZnII , CdII and PdII with schiff base [(E)-1-((2-amino-5-(3, 4, 5-trimethoxybenzyl) pyrimidin-4-ylimino) methyl) naphthalen-2-ol [HL)]. The prepared [HL] was characterized by FT-IR, UV-Vis spectroscopy, 1H13CNMR spectra Mass spectra and melting point. The compounds were characterized by techniques UV-Vis and FT-IR spectral studies, micro analysis (C.H.N), determination of atomic absorption, chloride content, molar conductivity measurements, magnetic susceptibility and melting point. The ligand acts as a monobasic tridentate, coordinating through deprotonated phenolic O and azomethine N atoms. The compounds are neutral electrolytic in dimeth
... Show MoreA tetradentate (N2O2) Schiff base (H2Ldfm) was successfully synthesized via condensation of curcumin / diferuloylmethane (dfm) and L-leucine amino acid (HL). There were three different methods that used for synthesizing H2Ldfm; (refluxing, grading, and fusion). Ten different metal complexes were also successfully synthesized by combination of the Schiff base (H2Ldfm) and 1,10-phenanthroline (phen) ligand to form a hexadentate (N4O2) mixed ligands (Ldfm , phen) with ten different metal salts (M) where{ M= Al(III), Mn(II), Fe(III), Co(II), Ni(II), Cu(II), Ag(I), Cd(II), Hg(II), and Pb(II)}. The molar ratio of reactants was (1:1:1) (M: H2Ldfm : phen). The new Schiff base and its new complexes were characterized by different physicochemical tec
... Show MoreIn this paper the effect of mixing TiO2 nanoparticles with epoxy resin is studied. The TiO2 nanoparticles would be synthesis and characterized by scanning electron microscopy (SEM), XRD FTIR, for two particle sizes of 50 and 25 nm. The thermal conductivity is measured with and without composite epoxy resin; the results showed that the thermal conductivity was increased as nanoparticle concentration increased too. The thermal conductivity was increased as particle size decreased.
In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method and the least squares method and that using the method of simulation model first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.
There is a suggestion that an antidiuretic hormone-induced decrease in diuresis might contribute to the rapid relief of the acute pain in renal colic. This study was designed to evaluate the efficacy of desmopressin nasal spray compared with diclofenac given intramuscularly in patients with acute renal colic. The study included 75 patients randomized into three different groups; group A received desmopressin (40 μg, nasal spray), group B diclofenac (75 mg) intramuscularly and group C, both desmopressin and diclofenac. Pain was assessed using a visual analogue scale (a 10-cm horizontal scale ranging from `no pain' to `unbearable pain') at baseline, 10, 20 and 30 min after administering t
... Show MoreThirty one samples of gum swabs were collected from patients with tooth caries (5-30 years old) from the College of Science (Biology department )- University of Baghdad- Iraq for the period from October 2018 to December 2018. , The samples were transported, after inoculation in a transport media (nutrient broth), to the laboratory of the College of Science and then cultured on mannitol salt agar and blood agar). The isolates belonging to Staphylococcus spp. were identified by biochemical tests and Vitek 2 compact system, while the more antibiotic resistant isolates were identified by using Polymerase Chain Reaction(ï´¾PCR) and sequencing of 16SrRNA . The results showed sharp UV absorption peaks at 330 - 340nm and AFM at 5
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
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