Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

This paper presents a minimum delay congestion control in differentiated Service communication networks. The premium and ordinary passage services based fluid flow theory is used to build the suggested structure in high efficient manage. The established system is capable to adeptly manage both the physical network resource limitations and indefinite time delay related to networking system structure.

Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.

In this work, lanthanium (III) complexes were synthesized using by Schiff base ligand (L) derived from benzaldehyde and o-aminoaniline with five amino acids (AA) from glycine (Gly), L-alanine (Ala), L-valine (Val), L-asparagine (Asp) and DL- phenylalanine (Phe). The Schiff base ligand has been characterized by elemental analysis, (MASS, FTIR, 1HNMR, 13CNMR, UV-VIS) electronic spectra. The structures of the new complexes have been described of analysis of elements, molar conductivity, (UV-Vis electronic, FTIR, mass) spectra also magnetic moment. The molar conductivity values of the complexes indicat this every of complexes are electrolytes and other analytical studies reveal octahedral geometry for La (III) ion. The Schiff base ligand, five

The Ligand 6,6--(1,2-benzenediazo) bis (3-aminobenzoicacid) derived from o-phenylenediamine and 3-aminobenzoicacid was synthesized. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the ligand with the following metal ions (CoII, NiII, CuII and ZnII ) in aqueous ethanol with a 1:1 M:L ratio and at optimum pH. Characterization of these compounds has been done on the basis of elemental analysis, electronic data, FT-IR and UV-Vis, as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). H

Mixed metal ligand complexes is reported with Curcumin (CUM) as a primary ligand and 1:10-phenanthroline (phen ) as secondary ligand. The structures of these complexes are confirmed by using FT-IR and UV- electronic spectroscopies, magnetic moments, melting points , molar conductivity measurements .and the metal % analysis revealed that the complexes analyze indicates a six coordinated as[M(CUM)( Phen)2]Cl, M=Mn (II), Co(II), Ni(II),Cu(II) ,Zn(II) , Cd(II) , Hg(II) and [M’ (CUM)( Phen)2]Cl2 M’= Cr(III) &. Fe(III). In-vitro antimicrobial studies on ( Curcumin and 1:10-phenanthroline ligands and mixed metal ligand complexes against {(Bacillus subtilis (G+) , Esherichia Coli (G-) and as well as antifungal activities against Candida albican