Background: Herbs are being widely explored to discover alternatives to synthetic antibacterial agents.Small Cardamom often referred to as queen of spices because of its very pleasant aroma and taste, have a history as old as human race. Most people use cardamom as a spice and are largely unaware of its numerous health benefits. The purpose of this study was to evaluate the effect of different concentrations of water and alcoholic cardamom extracts on sensitivities, growth, and adherence of Mutans streptococci in vitro. Materials and Methods: In this study, saliva was collected from ten volunteers (College students 18-22 years). Agar well technique was used to study the sensitivities of Mutans streptococci to different concentrations of small cardamom extracts and other control agents, also the effects of small cardamom extracts on viable counts, adherence of Mutans streptococci were studied Results: According to agar well diffusion methods, both cardamom extracts were effective in inhibition of Mutans streptococci, but still weaker than chlorhexidine gluconate 0.2%. Alcoholic extracts showed higher zone of inhibition compared to the same concentration of water with high significance differences (P<0.01). The effects of 10%, 15%, and 20% of both water and alcohol extracts of small cardamom were tested on the viability counts of Mutans streptococci in vitro. Highly significant reduction in the counts of bacteria was reported of both cardamom extracts and CHX in comparison to control without agents after 24 hr. Both cardamom extracts less effective than CHX. All the concentration of water and alcohol cardamom mouth washes tested was not effective in prevention the adherence of bacteria on teeth surface in vitro, while CHX was effective in prevention the adherence of bacteria. Conclusion: Cardamom extracts were effective against Mutans streptococci, but still less than CHX.
In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
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The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.
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Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the
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This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.
In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.
The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi
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Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
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