Human Adenosine deaminase is an essential enzyme for modulating the bioactivity of thyroid hormones, and It is important for the maturation and differentiation of lymphocytes, although its clinical importance in thyroid diseases have yet to be identified. Objective: The aim of the current study is to determine the Adenosine deaminase concentration in healthy controls, and in autoimmune thyroid diseases such as Graves' Disease, and Hashimoto's Thyroiditis. Patients and methods: A total of 183 serum specimens of 103 female patients with autoimmune thyroid diseases and 80 healthy control groups were included in this study and collected from the Baghdad Medical City, Iraq. Quantitative Human Adenosine Deaminase ELISA kits were used to estimate concentration of serum Adenosine deaminase. Results: There were a highly significant differences between thyroid patients and controls regarding TSH, T4 and adenosine deamainase serum levels (P-value 0.000), while no significant differences were seen with T3. On the other hands, There was a significant difference in adenosine deaminase protein level of autoimmune thyroid diseases patients in compared with controls (8.39±4.74 vs. 6.99±2.411, P<0.05). The results also indicate that both of age and BMI shows significant differences in patients compared with controls (42.63±12.97 vs. 38.94±12.82, P<0.05). Conclusion: There were a highly significant differences between thyroid patients and controls in TSH, T4, Anti-TPO and anti-TG, except T3.
This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere
... Show MoreThis study was aimed to evaluate the effect of spraying nano chitosan loaded with NPK fertilizer and nettle leaf and green tea extracts on the growth and productivity of potato for the spring and fall seasons of 2021.It was conducted at private farm in Wasit Governorate, Iraq, as a factorial experiment (5 × 5) within randomized complete block design using three replicates. The first factor included spraying with four concentrations of chitosan nanoparticles loaded with NPK fertilizer 0, 10. 15 and 20% in addition to chemical fertilization treatment, the second factor was spraying nettle leaf extract 25 and 35 gL-1 and green tea extract with 2 and 4 g.L-1, in addition to the control treatment, spraying with distilled water only. The
... Show MoreIn this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-
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In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit
... Show MoreThe problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, t
Background: Despite the importance of vaccines in preventing COVID-19, the willingness to receive COVID-19 vaccines is lower among RA patients than in the general population. Objective: To determine the extent of COVID-19 knowledge among RA patients and their attitudes and perceptions of COVID-19 vaccines. Methods: A qualitative study with a phenomenology approach was performed through face-to-face, individual-based, semi-structured interviews in the Baghdad Teaching Hospital, Baghdad, Iraq, rheumatology unit. A convenient sample of RA patients using disease-modifying anti-rheumatic drugs was included until the point of saturation. A thematic content analysis approach was used to analyze the obtained data. Results: Twenty-five RA pa
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
... Show MoreThe financial statements must accurately, clearly and fairly present the financial situation and financial statements should be reliable as well. Pursuant to Board Decision No. (74) 2020, CBI obliges banks, according to the Banking Law No. (94) for the year 2004, Article (33) paragraph 2 concerning real estate owned from previous years and expropriated as a result debt settlement , to apply a real estate liquidation provision at a rate of 20% for each property expropriated and at a rate of 100% for each year of delay up to (5) years .also from the significance of the issue of real estates that become a property of banks as a result of debt settlement and the pr
... Show MoreThe research included five sections containing the first section on the introduction of the research and its importance and was addressed to the importance of the game of gymnastic and skilled parallel effectiveness and the importance of learning, but the problem of research that there is a difference in learning this skill and difficulty in learning may be one of the most important reasons are fear and fear of falling and injury, And a lack of sense of the movement of the movement is one of the obstacles in the completion of the skill and the goal of research to design a device that helps in learning the skill of descending Almtor facing with half a cycle according to the typical locomotor track on the parallel device of the technical men'
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