Formulations based on nanomaterials have the ability to reduce the consuming of hazardous pesticides and theirimpact on human health and environment. The present study focused on a comparative investigation of histological effects of nanocapule acetamiprid (NACMP) in vivoand commercial parental bulk form of acetamiprid (ACMP) on albino mice. Nanoformulations of pesticides have the potential to improve food productivity without compromising with the ecosystem. In the present study, nanocapsules containing acetamiprid were prepared from two natural macromolecules, alginate and chitosan. The characterization of the nanocapsules were investigated by Dynamic Light Scattering(DLS), T ransmission Electron Microscopy (TEM) and Atomic force microscopy (AFM). The zetapotential studies show stability of the nanocapsules. TEM results show nanocapsules less than 60 nm in diameter . The encapsulation efficiency was found to be 88.65% as quantified by UV -vis spectra. Nanocapsules were prepared at pH 7. The comparison between nanocapsule ACMPand ACMPat concentration (40mg/kg) for6 weeks. Liver , kidney , spleen and brain tissue sections were taken as biomarkers forhistopathological alterations afterexposure to ACMPand NACMP for6 weeks. Many alterations in tissue section appeared except spleen and brain in 40 mg/kg of NACMPshow no effect.
In this paper, the concept of normalized duality mapping has introduced in real convex modular spaces. Then, some of its properties have shown which allow dealing with results related to the concept of uniformly smooth convex real modular spaces. For multivalued mappings defined on these spaces, the convergence of a two-step type iterative sequence to a fixed point is proved
The impact of decorating Fe, Ru, Rh, and Ir metals upon the sensing capability of a gallium nitride nanotube (GaNNT) in detecting chlorine trifluoride (CT) was scrutinized using the density functionals B3LYP and B97D. The interaction of the pristine GaNNT with CT was a physical adsorption with the sensing response (SR) of approximately 6.9. After decorating the above-mentioned metals on the GaNNT, adsorption energy of CT changed from −5.8 to −18.6, −18.9, −19.4, and −20.1 kcal/mol by decorating the Fe, Ru, Rh, and Ir metals into the GaNNT surface, respectively. Also, the corresponding SR dramatically increased to 39.6, 52.3, 63.8, and 106.6. This shows that the sensitivity of the metal-decorated GaNNT (metal@GaNNT) increased by in
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Strengthening of the existing structures is an important task that civil engineers continuously face. Compression members, especially columns, being the most important members of any structure, are the most important members to strengthen if the need ever arise. The method of strengthening compression members by direct wrapping by Carbon Fiber Reinforced Polymer (CFRP) was adopted in this research. Since the concrete material is a heterogeneous and complex in behavior, thus, the behavior of the confined compression members subjected to uniaxial stress is investigated by finite element (FE) models created using Abaqus CAE 2017 software.
The aim of this research is to study experime
... Show MoreLet h is Γ−(λ,δ) – derivation on prime Γ−near-ring G and K be a nonzero semi-group ideal of G and δ(K) = K, then the purpose of this paper is to prove the following :- (a) If λ is onto on G, λ(K) = K, λ(0) = 0 and h acts like Γ−hom. or acts like anti–Γ−hom. on K, then h(K) = {0}.(b) If h + h is an additive on K, then (G, +) is abelian.
A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.
The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be
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