Antibiotic resistance is the capability of the strains to resist or protect themselves from the effects of an antibiotic. Such a resistance towards the current antimicrobials leads to the search of novel antimicrobials. Nanotechnology has been promising in different field of science and among it is the use of nanoparticles as antibacterial agents. The gastrointestinal tract seems to be the primary reservoir of uropathogenic E.coli (UPEC) in humans. UPEC strains harbour the urinary tract and cause urinary tract infection. They cause serious ailments in terms of humans. They develop resistance and increase their virulence by forming biofilms. They also show a remarkable locomotory movement with the aid of autoinducer controlled ge

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

Undoped and Iodine (I)–doped chrome oxide (Cr2O3)thin films have been prepared by chemical spray pyrolysis technique at substrate temperatures(773K) on glass substrate. Absorbance and transmittance spectra have been recorded as a function of wavelength in the range (340-800 nm) in order to study the optical properties such as reflectance, Energy gap of allowed direct transition, extinction coefficient refractive index, and dielectric constant in real and imagery parts all as a function of wavelength. It was found that all the investigated parameters affect by the doping ratios.

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.

Fifty of urine samples were collected from patients with urinary tract infection
(UTI). The samples were collected from AL- Yarmuk hospital in Baghdad. All of
the isolates were diagnosed using biochemical test and vitek. The result showed that
30 (60%) isolates identified as E.coli from 50 urine samples. The colicinogenic
isolates were determined using cup assay methods. The results showed that 10 out of
30 isolates (33.3%) were detect as colicin producers from 30 isolate identified as
E.coli depending on the clear zone that observed against the sensitive isolate.
Colicin was extracted from the efficient isolate. Colicin activity (320 U/ml) was
determined by well assay method. The protein concentration (520 μg /m

Citrate-gel auto combustion technique was used to synthesize nickel-copper mixed ferrite nanoparticles Ni_xCu_1-xFe₂O₄ (x= 0.0, 0.4, 1.0) with different calcinating temperatures (200, 450, 650 and 850 °C). Structural, morphological, magnetic, and electrical properties were studied using X-ray diffraction (XRD), transmission electron microscopy (TEM), field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), vibrating sample magnetometer (VSM), and LCR meter in order to determine significant influences of Cu²⁺ cations content in nickel ferrite. The XRD patterns showed that all compositions had cubic spinels, except CuFe₂O₄

Complexes reaction of Fe+2, Cd+2, Hg+2 and Ag+ with the 2-thiotolylurea were prepared in ethanolic medium with the (1:1) M:L ratio yielded a series of neutral complexes. The prepared complexes were characterized using flame atomic absorption, micoelemental analysis (C.H.N), chloride content (Mohr Method) , FT.IR and UV-Vis spectroscopic, as well as magnetic susceptibility and conductivity measurement. From the above data, the proposed molecular structure for Fe+2, Cd+2 and Hg+2 complexes are tetrahedral geometry while Ag+ complex is trigonal structure.

This article discusses the estimation methods for parameters of a generalized inverted exponential distribution with different estimation methods by using Progressive type-I interval censored data. In addition to conventional maximum likelihood estimation, the mid-point method, probability plot method and method of moments are suggested for parameter estimation. To get maximum likelihood estimates, we utilize the Newton-Raphson, expectation -maximization and stochastic expectation-maximization methods. Furthermore, the approximate confidence intervals for the parameters are obtained via the inverse of the observed information matrix. The Monte Carlo simulations are used to introduce numerical comparisons of the proposed estimators. In ad

LA TRANSGRESSION CHEZ RIMBAUD Lecture de I' aspect de Transgression dans Marine

     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the