Genistein (GEN) is The major isoflavone found in soybeans, has a number of cardiovascular health benefits, Postmenopausal syndrome and osteoporosis. A direct flow injection analysis method for estimation of (GEN) in pure and supplements formulation . This system is based on diazotization coupling reactions between procaine penciline (PR) and genistein in basic medium, they formed yellow dyes have maximum absorption at 416 nm. Calibration curve were constructed over different GEN concentrations, linearity for GEN was 10-100 µg.mL-1 and detection limits of 1.51 ?g/mL. In the FIA technique, all analytical factors were analyzed and optimized. The established method was successfully used to determine GEN in the formulations of its supplement

A new spectrophotometric method has been developed for the assay of olanzapine (OLN.) in pure and dosage forms. The method is based on the diazocoupling of (OLN.) with diazotized p-nitroaniline in alkaline medium to form a stable brown colored water-soluble azo dye with a maximum absorption at 405 nm.  The variables that affect the completion of reaction have been carefully optimized. Beer’s law is obeyed over the concentration range of (0.5-45.0 μg.mL^-1) with a molar absorptivity of 1.5777×10⁴ L.mol^-1.cm^-1.  The limit of detection was  0.3148  Î¼g.mL^-1 and  Sandell’s  sensitivity value was 0.0198 μg.cm^-2. The propose

This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg

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

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

The inelastic C2 form factors and the charge density distribution (CDD) for ^58,60,62Ni and ^64,66,68Zn nuclei has been investigated by employing the Skyrme-Hartree-Fock method with (Sk35-Skzs*) parametrization. The inelastic C2 form factor is calculated by using the shape of Tassie and Bohr-Mottelson models with appropriate proton and neutron effective charges to account for the core-polarization effects contribution. The comparison of the predicted theoretical values was conducted with the available measured data for C2 and CDD form factors and showed very good agreement.

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden