New Schiff bases derived from D-galactose were synthesized by condensation of aldehyde (1,2:3,4-Di-O-isopropylidene-6-carboxaldehyde-α-D-galactopyranose) with different aromatic amines such as (4-bromo, 3-hydroxy, 4-iodo, 4-methoxy) aniline in dry benzene using glacial acetic acid as a catalyst. These compounds were converted to oxazepine derivatives by addition reaction with maleic anhydride in dry benzene as a solvent. The structures of the synthesized compounds have been characterized by elemental analysis, FTIR spectra, some of them by using 1HNMR spectra and measurement of its physical properties.

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

A series of 4-(methylsulfonyl)aniline derivatives were synthesized in order to obtain new compounds as a potential anti-inflammatory agents with expected selectivity against COX-2 enzyme. In vivo acute anti-inflammatory activity of the final compounds 11–14 was evaluated in rat using an egg-white induced edema model of inflammation in a dose equivalent to 3 mg/Kg of diclofenac sodium. All tested compounds produced significant reduction of paw edema with respect to the effect of propylene glycol 50% v/v (control group). Moreover, the activity of compounds 11 and 14 was significantly higher than that of diclofenac sodium (at 3 mg/Kg) in the 120–300 minute time interval, while compound 12 expressed a comparable effect to that of di

The Dirichlet process is an important fundamental object in nonparametric Bayesian modelling, applied to a wide range of problems in machine learning, statistics, and bioinformatics, among other fields. This flexible stochastic process models rich data structures with unknown or evolving number of clusters. It is a valuable tool for encoding the true complexity of real-world data in computer models. Our results show that the Dirichlet process improves, both in distribution density and in signal-to-noise ratio, with larger sample size; achieves slow decay rate to its base distribution; has improved convergence and stability; and thrives with a Gaussian base distribution, which is much better than the Gamma distribution. The performance depen