n this paper, we formulate three mathematical models using spline functions, such as linear, quadratic and cubic functions to approximate the mathematical model for incoming water to some dams. We will implement this model on dams of both rivers; dams on the Tigris are Mosul and Amara while dams on the Euphrates are Hadetha and Al-Hindya.
This research deals with the design and simulation of a solar power system consisting of a KC200GT solar panel, a closed loop boost converter and a three phase inverter by using Matlab / Simulink. The mathematical equations of the solar panel design are presented. The electrical characteristics of the panel are tested at the values of 1000 for light radiation and 25 °C for temperature environment. The Proportional Integral (PI) controller is connected as feedback with the Boost converter to obtain a stable output voltage by reducing the oscillations in the voltage to charge a battery connected to the output of the converter. Two methods (Particle Swarm Optimization (PSO) and Zeigler- Nichols) are used for tuning
... Show MoreAn optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and
... Show MoreBackgrround:: Cholera is gastroenteritis caused by enterotoxin producing Vibrio cholera. Cholera is predominantly a waterborne disease especially in countries with inadequate sanitation. Several rapid methods have been developed and used to detect V. cholerae serotypes directly from stools.
Objjecttiives:: to evaluate a rapid and accurate method for the diagnosis of cholera caused by V. cholerae O1 and O139 serogroups d to find the incidence of sporadic cases of cholera in Baghdad.
Metthods:: Sixty four stool samples were collected from four hospitals in Baghdad. The age of patients ranging from two months to 12 years, 26 were females and 38 males. Immunochromatographic visual test for qualitative detection of O1 and /or O139 serog
An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreIn its theoretical framework, this study dealt with the subjects of high commitment management and organizational excellence, as the study came in response to the growing developments and changes in the fields of management. It includes an analysis of correlation and effect between high commitment management, which has been attracting a lot of attention recently due to the intensifying rivalry between organizations because of certain external factors like globalization and world markets liberation, and its effect in achieving organizational excellence.
The practical framework, on the other hand, dealt with the analysis of correlation and effect between the study's variables. The problem
... Show MoreStructure type and disorder have become important questions in catalyst design, with the most active catalysts often noted to be “disordered” or “amorphous” in nature. To quantify the effects of disorder and structure type systematically, a test set of manganese(III,IV) oxides was developed and their reactivity as oxidants and catalysts tested against three substrates: methylene blue, hydrogen peroxide, and water. We find that disorder destabilizes the materialsthermodynamically, making them stronger chemical oxidantsbut not necessarily better catalysts. For the disproportionation of H2O2 and the oxidative decomposition of methylene blue, MnOx-mediated direct oxidation competes with catalytically mediated oxidation, making the most
... Show MoreThe compound 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an environmental contaminant, is a potent ligand for aryl hydrocarbon receptor (AhR). In the current study, we made an exciting observation that naive C57BL/6 mice that were exposed i.p. to TCDD showed massive mobilization of myeloid-derived suppressor cells (MDSCs) in the peritoneal cavity. These MDSCs were highly immunosuppressive and attenuated Con A–induced hepatitis upon adoptive transfer. TCDD administration in naive mice also led to induction of several chemokines and cytokines in the peritoneal cavity and serum (CCL2, CCL3, CCL4, CCL11, CXCL1, CXCL2, CXCL5, CXCL9, G-CSF, GM-CSF, VEGF, and M-CSF) and chemokine receptors