The aim of this research to show the role of some enzymes in pathological mechanism of rheumatoid arthritis (RA) disease. Sixty patients with RA and matched number of apparently healthy volunteers were included in the study. Spectrophotometric methods were used to determine Peroxy nitrite (ONOO), Nitric oxide (NO), Nitric oxide synthase activity (NOS) cycloxygenase-2 activity (COX-2), glutathione peroxidase (GPX) activity and superoxide dismutase (SOD) activity in serum of both groups. Colorimetric assay kits were used to determine Iron. Rheumatoid factor (RF) was determined using Imuno-Latex kit. ONOO, NO levels, and NOS activity were significantly higher in the patients compared to the control group. Conversely, Iron level, SOD activity and GPX activity were significantly lower in the patients compared to the control. In patients group, RF has significant positive correlation with COX-2, NOS activity and NO level while; it has significant negative correlation with Iron level. ONOO level has significant positive correlation with NO level, NOS activity and COX-2 activity while has significant negative correlation with Iron and SOD activity. NOS activity and NO level have significant positive correlation with COX-2 activity while, they have negative correlation with Iron. Iron has significant negative correlation with COX-2 activity. In control group, COX-2 has significant positive correlation with NOS activity and ONOO level. GPX has significant positive correlation with SOD and Iron. In conclusion: disorder activity of COX-2, NOS, SOD and GPX enzymes play important role in the pathological mechanism of rheumatoid arthritis and they linked with a decreased level of serum iron
The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.
Was conducted to compare the two methods above and it became clear by comparing the logistic regression model best of a Linear Discriminant function written
... Show MoreThis study expands the state of the art in studies that assess torsional retrofit of reinforced concrete (RC) multi-cell box girders with carbon fiber reinforced polymer (CFRP) strips. The torsional behavior of non-damaged and pre-damaged RC multi-cell box girder specimens externally retrofitted by CFRP strips was investigated through a series of laboratory experiments. It was found that retrofitting the pre-damaged specimens with CFRP strips increased the ultimate torsional capacity by more than 50% as compared to the un-damaged specimens subjected to equivalent retrofitting. This indicated that the retrofit has been less effective for the girder specimen that did not develop distortion beforehand as a result of pre-loading. From
... Show MoreIn the present study, magnet silica-coated Ag2WO4/Ag2S nanocomposites (FOSOAWAS) were fabricated via a multistep method to address the drawbacks related to single photocatalysts (pure Ag2WO4 and pure Ag2S) and to clarify the significant influence of semiconductor heterojunction on the enhancement of visible-light-driven organic degradation. Different techniques were performed to investigate the elemental composition, morphology, magnetic and photoelectrochemical properties of the fabricated FOSOAWAS photocatalyst. The FOSOAWAS photocatalyst (1 g/L) exhibited excellent photodegradation efficiency (99.5%) against Congo red dye (CR = 20 ppm) after 140 min of visible-light illumination. This result confirmed the ability of the heterojunction be
... Show MoreThis study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
... Show MoreIn this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin
In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin
This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi