Probiotics are live microbes that give many health benefits to human beings and animals, the most studied and commonly used probiotics are Gram-positive bacteria; lactobacilli and bifidobacteria. At nowadays, Lactobacillus spp. constitute more than two-thirds of the total numbers of probiotic species. The present study aimed to characterize Lactobacillus that locally isolated from human mouth and feces as probiotics. A total of three Lactobacillus isolates; Lactobacillus fermentum Lb2, Lactobacillus rhamnosus Lb9, and Lactobacillus paracasei Lb10 were investigated in respect to acid and bile salts tolerance, antibiotics susceptibility, and cell surface hydrophobicity in vitro using bacterial adhesion to hydrocarbons method. In compa

Background: Fast dissolving oral drug delivery system is solid dosage form which disintegrates or dissolves within second when placed in the mouth without need of water or chewing. In present investigation, an attempt has been made to develop oral fast dissolving film of calcium channel blocker lacidipine. Method: Five formulas were prepared by solvent casting method using HPMC (METOLOSE)® as a film forming polymer and evaluated for their physical characteristics such as thickness, weight variation, folding endurance, drug content, disintegration time and in vitro drug release. The compatibility of the drug in the formulation was confirmed by FTIR and DSC studies. Result and Conclusion: The optimized formula F1 showed minimum in vitr

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

Based on nonlinear self- diffraction technique, the nonlinear optical properties of thin slice of matter can be obtained. Here, nonlinear characterization of nano-fluids consist of hybrid Single Wall Carbon Nanotubes and Silver Nanoparticles (SWCNTs/Ag-NPs) dispersed in acetone at volume fraction of 6x10-6, 9x10-6, 18x10-6 have been investigated experimentally. Therefore, CW DPSS laser at 473 nm focused into a quartz cuvette contains the previous nano-fluid was utilized. The number of diffraction ring patterns (N) has been counted using Charge - Coupled- Device (CCD) camera and Pc with a certain software, in order to find the maximum change of refractive index ( of fluids. Our result show that the fraction volume of 18x10-6 is more nonli

The inhibitory behavior of L-Cysteine (Cys) and its derivatives towards iron corrosion through density functional theory (DFT) was investigated. The current research study undertakes a rigorous evaluation of global as well as local reactivity descriptors of the Cys in protonated as well as neutral forms and the changes in reactivity after the combination of Cys into di- and tripeptides. The inhibitory effect of di- and tri-peptides increases since, in the molecular structure, the number of reaction centers increase. We computed the adsorption energies (Eads) and low energy complexes with most stability for the adsorption of small peptides and Cys amino acids onto the surfaces of Fe (1 1 1). We found that the adsorption of tri-peptides onto

Cadmium oxide (CdO) thin films were deposited using the sequencing ion layer adsorption and reaction (SILAR) method. In this study, the effect of the pH value of an aqueous solution of cadmium acetate at a concentration of 0.2 mol of the cadmium oxide film was determined. The solution source for the cadmium oxide film was cadmium ions and an aqueous ammonia solution. The CdO films were deposited on glass substrates at a temperature of 90 ℃. The cadmium oxide film thickness was determined by the weight difference method at pH values ​​(7.2, 8.2). X-ray diffraction (XRD) and scanning electron microscopy (SEM) showed that the size of the crystals increased with the increase in the solution (pH). While the UV-visible spectra of the fil

The aim of this study is to evaluate the levels of trace elements Magnesium (Mg), Zinc (Zn), Copper (Cu), and Selenium (Se) in blood sera of asthmatic patients by Atomic Absorption Spectrophotometry (AAS). The concentrations of Mg, Cu, and Zn have been determined by Flame Atomic Absorption spectrophotometry (FAAS), and Se with flameless Graphite Furnace Atomic Absorption Spectrophotometry (GFAAS). The study involves (55) asthmatic patients as study group and (28) subjects as control from both genders. Serum levels of Mg, Cu, and Se were significantly higher (p<0.001 for all) in patients when compared with healthy subjects, while Zn level was relatively significant (p<0.05). Our observations confirm the efficacy and applicability of (AAS) in