Mixed ligand complexes of bivalent metal ions, viz; M= Fe(II),Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition Na2[M (Amox)(Sac)3] in 1:1:3 molar ratio, (where Amox = Amoxicillin tryhydrate (C16H19N3O5S.H2O) and Sac = Saccharine(C7H5NO3S) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity, determination the percentage of the metal in the complexes by flame(AAS), FT-IR, magnetic susceptibility measurements and electronic spectral data. The ligands and their metal complexes have been screened for their biological activity against selected microbial strains (gram +ve) and (gram -ve).

Mixed ligand complexes of bivalent metal ions, viz; M= Fe(II),Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition Na2[M (Amox)(Sac)3] in 1:1:3 molar ratio, (where Amox = Amoxicillin tryhydrate (C16H19N3O5S.H2O) and Sac = Saccharine(C7H5NO3S) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity, determination the percentage of the metal in the complexes by flame(AAS), FT-IR, magnetic susceptibility measurements and electronic spectral data. The ligands and their metal complexes have been screened for their biological activity against selected microbial strains (gram +ve) and (gram -ve).

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

A few examinations have endeavored to assess a definitive shear quality of a fiber fortified polymer (FRP)- strengthened solid shallow shafts. Be that as it may, need data announced for examining the solid profound pillars strengthened with FRP bars. The majority of these investigations don't think about the blend of the rigidity of both FRP support and cement. This examination builds up a basic swagger adequacy factor model to evaluate the referenced issue. Two sorts of disappointment modes; concrete part and pulverizing disappointment modes were examined. Protection from corner to corner part is chiefly given by the longitudinal FRP support, steel shear fortification, and cement rigidity. The proposed model has been confirmed util