Development of improved methods for the synthesis of metal oxide nanoparticles are of high priority for the advancement of material science and technology. Herein, the biosynthesis of ZnO using hydrahelix of beta vulgaris and the seed of abrus precatorius as an aqueaus extracts adduced respectivily as stablizer and reductant reagent. The support are characterized by spectroscopic methods ( Ft-IR, Uv-vis ).The FTIR confirmed the presence of ZnO band. The Uv-visible showed absorption peak at corresponds to the ZnO nanostructures. X-ray diffraction, scaning electron microscopy (SEM), dispersive X-ray spectroscopy (EDX) techniques are taken to investigation the size, structure and composition of synthesised ZnO nanocrystals. The XRD pattern mat

The biological activities of some ternary nickel complexes with a Schiff base obtained from 4-dimethylaminobenzaldehyde and 2-aminophenol have been reported. The Schiff base ( HL1) acts as a primary ligand whereas, anthranilic acid ( HL2), 2-nitroaniline ( HL3), alanine ( HL4) and histidine ( HL5) act as secondary ligand or co-ligand. The anticancer activity of these compounds was studied against human colon carcinoma (HCT-116), human hepatocellular liver carcinoma (HEPG-2) and human breast carcinoma (MCF-7) cell lines. As per the results, the compounds were active against the cell lines. The antioxidant activity of the same compounds was evaluated using DPPH (1,1-diphenyl-2-picryl-hydrazyl) radical scavenging and compared with ascorbic aci

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

It is more beneficial science and created and the highest honor is the Koran Sciences, God has honored research in this fun science, came this research that shed the light on the radical incision, and Naughty derivatives as contained in the Koran, and illustrate the diversity of Saghma morphological, and fork them from derivatives what it entailed connotations, as well as the evacuation of cryptic in some of these verses from the biological secrets take minds newly exposed Anitrjt science under the name of scientific miracles.
The research methodology is revenue verse which included the word, and revenue lexical meaning and its meaning in the context of the Qur'an, and reflect the views of the commentators of the verse, and then the r

The aim of this work is synthesis of _Eoly (Vinyl-4-AminoBenzoate) (PVAB) from reaction of _Eoly Vinyl Alkohol PVA with 4-aminobenzoyl chloride in alkaline media. We also prepare the metal complexes of poly (vinyl- 4-aminobenzoate) and antimicrobial properties were evaluated by dilute method against five pathogenic bacteria (Escherichia coli, Shigella dysentery, Klebsiella pneumonae, Staphylococcus aureus, Staphylococcus Albus) and two fungal (Aspergillus Niger, Yeast). All polymer metal complexes showed different activities against the various microbial isolates. The polymer metal complexes showed higher activity than the free polymer.

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise