Quorum sensing (QS) is a perfectly orchestrated molecular communication system. It is a boon for Klebsiella pneumoniae, and bane for the host. This system is believed to make K. pneumoniae a leading cause of multidrug-resistant (MDR) nosocomial infections. This study aimed to investigate the antibacterial and anti-biofilm potential of medicinal plant extracts through interfering with QS of K. pneumoniae. The effect of different concentrations of ethanolic extracts of cinnamon and clove on K. pneumoniae was determined by analyzing the growth curve, survival assay (MTT), Qualitative and quantitative biofilm formation, antibiotic resistance, along with studying gene expression of the genes encoding the above traits, using quantitative real tim

Medicinal plant life have performed an integral role in the development of human lifestyle being used as resources for the manufacturing of contemporary medicines, antibiotics. Microorganisms are responsible for many issues in industry and remedy because of biofilm formation. This study aimed to take a look at the results of Thymus vulgaris alcoholic extract on Staphylococcus aureus the causative marketers of acne in human particularly the women. The extract was acquired mixing 25 g of Thyme powder with 350 ml of 80% ethanol for 6 hours at 40°. Antimicrobial activities of the plant extract and integral oil towards the S. aureus were decided using the agar diffusion technique. The consequences proven that special concentrations of alcoholic

The scientific studies that deal with Herminutia (interpretation) as the art of reading the interpretation practiced by the recipient after his understanding of the literary texts and works of art that he sees or read them so that these readings to make the act of reading and allow him the opportunity to mature and rational reflection of each text or artistic work.

Based on this, the researchers considered the establishment of the problem of their research through the search for the problematic overlap of concepts in the interpretive practices of the literary text?

The second chapter dealt with the definition of the term interpretation as well as interpretation as a theory and concept, and then the indicators reached by t

The research aims at identifyiny the effect of (Danials Model) in concepts Acquisition of Education Principles on Students at college at Education The total unmber of Students , is (65) male and female Students distributed in two groups . The First group is the experiemental group which is taught the (Danials Model) and is (34) Students . The second groupe is the control group which is taught the traditional method of teaching and it is (31) Students . The researcher has matcheol between the two groupe by the following variables : the age , (in monthes) their intelligence their parents a cademic leve of education . The research has constructed a test of (20) items of multiple choice test . The reliability of The test has been cal

The parametric programming considered as type of sensitivity analysis. In this research concerning to study the effect of the variations on linear programming model (objective function coefficients and right hand side) on the optimal solution. To determine the parameter (θ) value (-5≤ θ ≤5).Whereas the result، the objective function equal  zero and the decision variables are non basic، when the parameter (θ = -5).The objective function value increases when the parameter (θ= 5) and the decision variables are basic، with the except of X_24, X₃₄.Whenever the parameter value increase, the objectiv

. 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

Abstract

Objective / Purpose: Online social relationships through the emergence of Web 2.0 applications have become a new trend for researchers to study the behavior of consumers to shop online, as well as social networking sites are technologies that opened up opportunities for new business models. Therefore, a new trend has emerged, called social trade technology. In order to understand the behavioral intentions of the beneficiaries to adopt the technology of social trade, the current research aims at developing an electronic readiness framework and UTAUT model to understand the beneficiary's adoption of social trade technology.

Design/ methodology/ Approach: To achieve the obje

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

Interval methods for verified integration of initial value problems (IVPs) for ODEs have been used for more than 40 years. For many classes of IVPs, these methods have the ability to compute guaranteed error bounds for the flow of an ODE, where traditional methods provide only approximations to a solution. Overestimation, however, is a potential drawback of verified methods. For some problems, the computed error bounds become overly pessimistic, or integration even breaks down. The dependency problem and the wrapping effect are particular sources of overestimations in interval computations. Berz (see [1]) and his co-workers have developed Taylor model methods, which extend interval arithmetic with symbolic computations. The latter is an ef