Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

MCA has gained a reputation for being a very useful statistical method for determining the association between two or more categorical variables and their graphical description. For performance this method, we must calculate the singular vectors through (SVD). Which is an important primary tool that allows user to construct a low-dimensional space to describe the association between the variables categories. As an alternative procedure to use (SVD), we can use the (BMD) method, which involves using orthogonal polynomials to reflect the structure of ordered categorical responses. When the features of BMD are combined with SVD, the (HD) is formed. The aim of study is to use alternative method of (MCA) that is appropriate with order

In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better

Reaction of L1 [((E)-N1-(nitrobenzylidene)benzene-1,2-diamine] and L2( m-aminophenol), and one equivalent of di- or tri-valent metals(Cr(ӀӀӀ), Mn(ӀӀ), Fe(ӀӀӀ), Co(ӀӀ), Ni(ӀӀ), Cu(ӀӀ) and Zn(ӀӀ) afforded the complexes [M(L1)(L2)2]Cl, M=Cr(ӀӀӀ) and Fe(ӀӀӀ) and the complexes [M(L1)(L2)2] M= Mn(ӀӀ), Co(ӀӀ), Ni(ӀӀ), Cu(ӀӀ) and Zn(ӀӀ). The structure of the Schiff base ligand and their complexes are characterized by (C:H:N), FT.IR, UV.Vis, 1HNMR, 13CNMR and mass spectral. The presence of metal in the complexes are characterized by flame atomic absorption. The spectral data of the complexes have revealed the octahedral geometry. The (L1), (L2) and mixed ligand metal complexes were screened for their ability as cataly

Synthesis, Characterization And Biological Evaluation of Schiff Base And Ligand Metal Complexes of Some Drug Substances

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A Schiff base ligand (L) was synthesized via condensation of N-( 1-naphthyl) ethylenediamine dihydrochloride with phthalaldehyde. The ligand was characterized by FT-IR, UV–Vis, 1H NMR, mass spectrometry, and elemental analysis (C, H, N). Five metal complexes (Co(II), Ni(II), Cu(II), Zn(II), and Cd(II)) were prepared with the ligand in a 1:1 (M:L) ratio using an aqueous ethanol solution. The complexes were characterized by FT-IR, UV–Vis, mass spectrometry, and elemental analysis (C, H, N). Additionally, 1H NMR spectroscopy was employed for Cd(II) complex. Antimicrobial activity of the ligand and its metal complexes against pathogenic bacteria (K. pneumoniae, E. coli, S. aureus, and S. epidermidis) and fungus (C. albicans) were evaluated