In this paper, the Reliability Analysis with utilizing a Monte Carlo simulation (MCS) process was conducted on the equation of the collapse potential predicted by ANN to study its reliability when utilized in a situation of soil that has uncertainty in its properties. The prediction equation utilized in this study was developed previously by the authors. The probabilities of failure were then plotted against a range of uncertainties expressed in terms of coefficient of variation. As a result of reliability analysis, it was found that the collapse potential equation showed a high degree of reliability in case of uncertainty in gypseous sandy soil properties within the specified coefficient of variation (COV) for each property. When the COV ranges (0-100) for each soil properties under study, it was found also that the collapse potential equation is very well in predicting the collapse potential of gypseous sandy soils for all values of the COV lies between (0-100) % for initial water content and degree of saturation, and for values of the COV not exceed 11%, 19% for the initial dry unit weight and specific gravity respectively, as well as for the values of the COV not exceed 80%, 97% for the initial voids ratio and gypsum content respectively.
Background: Kocuria kristinae (earlier known as Rothia kristinae) is a relatively new opportunistic pathogen responsible for ear infections. The ability of this organism to form biofilms increases its resistance to therapy and promotes the development of antimicrobial resistance, necessitating new treatment methods. Objective: To assess the effect of 3-caffeoylquinic acid on K. kristinae isolated from patients with ear infections. Methods: Isolation of five clinical strains was done by conventional microbiological procedures. The ability of K. kristinae to form biofilms was determined by the crystal violet method (absorbance at OD₅₇₀) before and after 3-caffeoylquinic acid exposure; statistical data analysis was done using a
... Show MoreInflammatory control is essential to diminish injury and make renal injury treatment simpler. Proposed therapeutics have primarily targeted pro-inflammatory variables. Juniperus oxycedrus was frequently used to treat a variety of infectious disorders, hyperglycemia, obesity, TB, bronchitis, inflammation, and pneumonia. Juniperus oxycedrus twigs and leaves were defatted with n-hexane using Soxhlet apparatus then the residue of plant material dried and re-extracted sequentially by two different solvents Ethylacetate and methanol. The pro-inflammatory markers IL-1 and iNOS, as well as the potential kidney biomarker KIM-1, TNF-α, and transcription factor NF-KB were measured using the RealTime Quantitative qPCR method. The results showed that J
... Show MoreIn this work, spinel ferrites (NiCoFe2O4) were prepared as thin films by dc reactive dual-magnetron co-sputtering technique. Effects of some operation parameters, such as inter-electrode distance, and preparation conditions such as mixing ratio of argon and oxygen in the gas mixture, on the structural and spectroscopic characteristics of the prepared samples were studied. For samples prepared at inter-electrode distance of 5 cm, only one functional group of OH- was observed in the FTIR spectra as all bands belonging to the metal-oxygen vibration were observed. Similarly, the XRD results showed that decreasing the pressure of oxygen in the gas mixture lead to grow more crystal planes in the samples prepare
... Show MoreIn this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes
The Dynamic Load Factor (DLF) is defined as the ratio between the maximum dynamic and static responses in terms of stress, strain, deflection, reaction, etc. DLF adopted by different design codes is based on parameters such as bridge span length, traffic load models, and bridge natural frequency. During the last decades, a lot of researches have been made to study the DLF of simply supported bridges due to vehicle loading. On the other hand, fewer works have been reported on continuous bridges especially with skew supports. This paper focuses on the investigation of the DLF for a highly skewed steel I-girder bridge, namely the US13 Bridge in Delaware State, USA. Field testing under various load passes of a weighed load vehicle was u
... Show Moreorder to increase the level of security, as this system encrypts the secret image before sending it through the internet to the recipient (by the Blowfish method). As The Blowfish method is known for its efficient security; nevertheless, the encrypting time is long. In this research we try to apply the smoothing filter on the secret image which decreases its size and consequently the encrypting and decrypting time are decreased. The secret image is hidden after encrypting it into another image called the cover image, by the use of one of these two methods" Two-LSB" or" Hiding most bits in blue pixels". Eventually we compare the results of the two methods to determine which one is better to be used according to the PSNR measurs