This study was conducted to isolate and identify killer yeast Hanseniaspora uvarum from dates vinegar and measurement the ability of this yeast to produce killer toxin. The antimicrobial activity of the concentrated supernatant containing partially purified concentrated killer toxin was also detected against several pathogenic bacteria and yeast species, which includes two types of yeast Rhodotorula mucilaginosa and Candida tropicalis and four human pathogenic bacteria Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeurginosa. In addition, the antagonistic activity of examined yeast have been studied toward four types of fungi, where two are pathogenic

In this study, synthesised new ligand: potassium 2,2'-(quinoxaline-2,3- diyl)bis(1-phenylhydrazinecarbodithioate) (L). The ligand synthesised by reacting N1,N2-dip-tolyloxalamide as the starting material with CS2 and KOH to add the CS2 group and then with phenylendiammine to achieve (L). The ligand used in the synthesis of complexes with (CoII, NiII and CdII). The new ligand and its complexes characterised by FT-IR, UV-Vis, 1H, 13C-NMR, Mass spectroscopy, and elemental analysis, in addition to the above techniques were using magnetic moment, atomic absorption, chloride content, and melting point to describe the metal complexes.

Curing of concrete is the maintenance of a satisfactory moisture content and temperature for a
period of time immediately following placing so the desired properties are developed. Accelerated
curing is advantages where early strength gain in concrete is important. The expose of concrete
specimens to the accelerated curing conditions which permit the specimens to develop a significant
portion of their ultimate strength within a period of time (1-2 days), depends on the method of the
curing cycle.Three accelerated curing test methods are adopted in this study. These are warm water,
autogenous and proposed test methods. The results of this study has shown good correlation
between the accelerated strength especially for

Assessing parameters in autoregressive (AR) models is a fundamental aspect of time-series analysis and is widely used in fields such as finance, climate science, and engineering. Ordinary least squares and maximum likelihood estimation are commonly used for this purpose, but their performance can be affected when the estimation process is subject to complex constraints. In this study, two nonlinear programming techniques—the Gradient Projection (GP) method and Convex Quadratic Programming (CQP) based on the complementary pivot algorithm—were examined for estimating the parameters of an AR(2) model. The two nonlinear methods were compared with traditional estimation techniques using the Mean Squared Error (MSE) as the primary criterion.

لقد تسبب انتشار الإرهاب في العالم وكذلك الحروب الأهلية والصراعات في أوائل القرن الحادي والعشرين في جميع أنحاء العالم في الكثير من الأضرار وخلفت ضحايا جسيمة. أدت الهجمات الإرهابية على النساء، مثل اختطاف بوكو حرام لأكثر من 270 تلميذة في نيجيريا وتقارير عن انتشار الاغتصاب والاعتداء الجنسي في المناطق التي مزقتها الحرب، إلى إنتاج العديد من العروض المسرحية في الولايات المتحدة التي تصور خواص الجناة وكذلك الضحا

The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the