The study aimed to purification of acid phosphatase (ACP) from sera of obesetype 2 diabetes mellitus patients, this study included from thirty T2DM patients and thirty control, purification process was done with several steps included precipitation with inorganic salt (NH4 ) 2SO4 30%-80%, dialysis, ion exchange chromatography by DEAE sepharose anion column and size exclusion chromatography by Sepharose 6B.ACP, BMI, FBS, HbA1c, Lipid profile, Urea, Creatinie, Insuline, Homa-IR were determined. Results showed the precipitate and concentrated protein appeared four peaks in ion exchange column. ACP located in the first and second peak with purification fold (21.1), (37.2) yield of enzyme and specific activity (173.3) IU/ml, which obtained a si

The research involves examining the influence of partial solar eclipse on the strength of neutral hydrogen from the Sun. Baghdad University Radio Telescope (BURT) was used to monitor the partial solar eclipse on the 25th of October, 2022. Radio observations from the Sun were recorded from 11:30 AM to 03:36 PM. This means that the HI emission from the Sun was recorded before, during and after the event. It was noticed, that at the moment of maximum eclipse, ~ 46% of the Sun’s disk was covered by the Moon. For the purpose of this research, the solar radio wave intensity was monitored and the solar flux density was determined at different times, i.e. before, during and after the partial solar eclipse. The obtained results showed that

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

This paper investigates an effective computational method (ECM) based on the standard polynomials used to solve some nonlinear initial and boundary value problems appeared in engineering and applied sciences. Moreover, the effective computational methods in this paper were improved by suitable orthogonal base functions, especially the Chebyshev, Bernoulli, and Laguerre polynomials, to obtain novel approximate solutions for some nonlinear problems. These base functions enable the nonlinear problem to be effectively converted into a nonlinear algebraic system of equations, which are then solved using Mathematica®12. The improved effective computational methods (I-ECMs) have been implemented to solve three applications involving nonli

The process of controlling a Flexible Joint Robot Manipulator (FJRM) requires additional sensors for measuring the state variables of flexible joints. Therefore, taking the elasticity into account adds a lot of complexity as all the additional sensors must be taken into account during the control process. This paper proposes a nonlinear observer that controls FJRM, without requiring equipment sensors for measuring the states. The nonlinear state equations are derived in detail for the FJRM where nonlinearity, of order three, is considered. The Takagi–Sugeno Fuzzy Model (T-SFM) technique is applied to linearize the FJRM system. The Luenberger observer is designed to estimate the unmeasured states using error correction. The develop