Aromatic Schiff-bases are known to have antibacterial activity, but most of these compounds are sparingly soluble in water. The present work describes the synthesis of new Schiff-bases derived from branched aminosugars. Treatment of 3-Amino-3-Cyano-3-Deoxy-1,2:5,6-Di-O-Isopropylene-α-D-Allofuranose (1) with the aldehydes (2) under reflux in methanol afforded the Schiff-bases (3) in good yields. The new Schiff-bases were in accord with their NMR, IR spectral data and elemental analysis.

     New chelating ligand derived from triazole and its complexes with metal ions Rhodium, Platinum and Gold were synthesized. Through a copper (I)-catalyzed click reaction, the ligand produced 1,3-dipolar cycloaddition between 2,6-bis((prop-2-yn-1-yloxy) methyl) pyridine and 1-azidododecane. All structures of these new compounds were rigorously characterized in the solid state using spectroscopic techniques like: 1HNMR, 13CNMR, Uv-Vis, FTIR, metal and elemental analyses, magnetic susceptibility and conductivity measurements at room temperature, it was found that the ligand acts as a penta and tetradentate chelate through N3O2, N2O2, and the geometry of the new complexes are identified as octahedral for (Rh & Pt) complexes a

In this study Microwave and conventional methods have been used to extract and estimate pectin and its degree of esterification from dried grapefruit and orange peels. Acidified solution water with nitric acid in pH (1.5) was used. In conventional method, different temperature degrees for extraction pectin from grape fruit and orange(85 ,90 , 95 and 100?C) for 1 h were used The results showed grapefruit peels contained 12.82, 17.05, 18.47, 15.89% respectively, while the corresponding values were 5.96, 6.74, 7.41 and 8.00 %, respectively in orange peels. In microwave method, times were 90, 100, 110 and 120 seconds. Grapefruit peels contain 13.86, 16.57, 18.69, and 17.87%, respectively, while the corresponding values were of 6.53, 6.68, 7.2

Biodiesel can be prepared from various types of vegetable oils or animal fats with the aid of a catalyst.
Calcium oxide (CaO) is one of the prospective heterogeneous catalysts for biodiesel synthesis. Modification
of CaO by impregnation on silica (SiO2) can improve the performance of CaO as catalyst. Egg shells and rice
husks as biomass waste can be used as raw materials for the preparation of the silica modified CaO catalyst.
The present study was directed to synthesize and characterize CaO impregnated SiO2 catalyst from biomass
waste and apply it as catalyst in biodiesel synthesis. The catalyst was synthesized by wet impregnation
method and characterized by x-ray diffraction, x-ray fluorescence, nitr

The ligand 2-[1-(1H-indol-3-yl)ethylimino) methyl]naphthalene-1-ol, derived from 1-hydroxy-2-naphthaldehyde and 2-(1H-indol-3-yl)ethylamine, was used to produce a new sequence of metal ions complexes. Thus ligand reactions with NiCl₂.6H₂O, PdCl₂, FeCl_3.6H₂O and H₂PtCl₆.6H₂O were sequentially made to collect mono-nuclear Ni(II), Pd(II), Fe (III), and Pt(IV). (IR or FTIR), Ultraviolet Reflective (UV–visible), Mass Spectra analysis, Bohr-magnetic (B.M.), metal content, chloride content and molar conductivity have been the defining features of the composites. The Fe(III) and Pt(IV) complexes have octahedral geometries, while the Ni(II) complex has tetra

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep