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Enviromental impact assessment of cement industry using Leopold Matrix
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The assessment of the environmental impact of the cement industry using the Leopold Matrix is ​​to determine the negative and positive impacts on the environment resulting from this industry, and what are the long-term and short-term effects, direct and indirect, and the amount of these effects and potential risks, and that this evaluation process is done through a number of methods, including Matrix method, including (Leopold).

 

The importance of the research because the cement occupies is of great importance in the world, especially in our country, Iraq, in the sector of construction and modernity, and the toxic emissions and solid waste produced by the production of this material.

 

Environmental problems resulting from this industry have been addressed. The basic problem of the cement industry is determined in the environmental field because of the cumulative effect it has on the environment and production capacity on the surrounding environment.

 

The main objective of conducting the research is to assess the environmental impacts of major industrial projects, especially cement, one of the analytical methods in urban planning, which can contribute to reducing the negative effects on the environment and on the uses of the surrounding land. Among the disadvantages of this industry is that it

 

 

 

 

 

 increases air, soil and water pollution, as well as leveling the lands and decreases the health safety of workers through the emissions they cause,

 

perhaps the most prominent of which are carbon dioxide (CO2), carbon dioxide (CO), and methane (CH4).

 

As these gases lead to direct air pollution, especially in the areas surrounding the plant.The Kirkuk cement plant is one of the major economic development projects in the country as it provides a national and local product to support other construction projects, and at the same time it is a category A polluting industry and therefore it is necessary to sign it outside the cities, and it requires an environmental impact assessment prepared in advance according to a detailed study that includes problems and impacts. Expected and solutions to it.

 

The evaluation process is to ensure the protection, improvement and preservation of the environment and natural resources. Therefore, the research considers the necessity to oblige the owners of cement projects to implement the environmental requirements mentioned in the environmental legislation brochure in force, and to develop a strategy to mitigate the negative impacts and alternative options in the production process.

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Publication Date
Sun Jan 15 2023
Journal Name
Dental Hypotheses
Effect of addition of polymerized polymethyl methacrylate (PMMA) and zirconia particles on impact strength, surface hardness, and roughness of heat cure PMMA: An in vitro study
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Introduction: This study was designed to examine the effects of addition of the combination of polymerized polymethyl methacrylate (PMMA) and zirconia (ZrO2) particles to heat cure PMMA resin on impact strength, surface hardness, and roughness. Methods: The 70% (w/w) of polymerized PMMA powder (particle size: 0.70mm) was mixed with 30% (w/w) of zirconia powder (ZrO2) (1mm) to produce PMMA-ZrO2 filler. Ninety acrylic specimens created were divided into three groups containing 0% wt (Control group), 2% wt, and 4% wt, PMMA-ZrO2 filler. Ten specimens were used for impact strength, surface hardness and roughness test, blindly. Data were analyzed via oneway ANOVA and the Tukey post hoc test using R 3.6.3. Results: There was statistically signific

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Fabrication and Characterization of Gas Sensor from ZrO2: MgO Nanostructure Thin Films by R.F. Magnetron Sputtering Technique
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Thin films ZrO2: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and  10)% percentage to be used as the gas sensor for nitrogen dioxide NO2. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Evaluation of the cytotoxic effects of the colchicine compound isolated from the leaves of Calotropis procera (Ait) against MCF-7 and SK-GT-4 cancer cell lines.
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Alkaloids are regarded as important nitrogen-containing chemical compounds that serve as a rich source for discovering and developing new drugs where most plant-origin alkaloids have antiproliferation effects on different kinds of cancers. Alkaloids’ continence of Calotropis procera leaves are detected by two biochemical alkaloid reagents. Also GC-MS analysis for leaf alkaloid extract was done that showed the existence of one type of alkaloid compound at retention time12.8min detected as colchicine (C22H25N06( by comparing it with colchicine standard reference (Sigma Aldrich) with M.wt 399g/mol and percentage area 7.1%. Furthermore, identification, separation, and purification

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Fri Jan 04 2019
Journal Name
Journal Of Planner And Development
نمذجة توزيع المدارس الابتدائية في مدينة الفلوجة باستخدام نظم المعلومات الجغرافية G.I.S
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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Local Dependence for Bivariate Weibull Distributions Created by Archimedean Copula
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In multivariate survival analysis, estimating the multivariate distribution functions and then measuring the association between survival times are of great interest. Copula functions, such as Archimedean Copulas, are commonly used to estimate the unknown bivariate distributions based on known marginal functions. In this paper the feasibility of using the idea of local dependence to identify the most efficient copula model, which is used to construct a bivariate Weibull distribution for bivariate Survival times, among some Archimedean copulas is explored. Furthermore, to evaluate the efficiency of the proposed procedure, a simulation study is implemented. It is shown that this approach is useful for practical situations and applicable fo

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Photonic Crystal Fiber Pollution Sensor Based on the Surface Plasmon Resonance Technology
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Photonic Crystal Fiber (PCF) based on the Surface Plasmon Resonance (SPR) effect has been proposed to detect polluted water samples. The sensing characteristics are illustrated using the finite element method. The right hole of the right side of PCF core has been coated with chemically stable gold material to achieve the practical sensing approach. The performance parameter of the proposed sensor is investigated in terms of wavelength sensitivity, amplitude sensitivity, sensor resolution, and linearity of the resonant wavelength with the variation of refractive index of analyte. In the sensing range of 1.33 to 1.3624, maximum sensitivities of 1360.2 nm ∕ RIU and 184 RIU−1 are achieved with the high sensor resolutions of 7

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Publication Date
Wed Oct 24 2018
Journal Name
Journal Of Planner And Development
تقويم الآليات المقترحه لتنمية محافظة الانبار لسنة 2030 باستخدام اسلوب التحليل الهرمي
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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Evaluation of Amygdalin (B17) and Cucurbita pepo (Pumpkin seed) Activity Against Blastocystis from Diarrheic Patients in Baghdad, Iraq: in Vitro Study
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Blastocystis is a ubiquitous human and animal protozoa that inhabit the gastrointestinal tract. Metronidazole is considered the standard drug for the treatment of Blastocystis infection; however, there is growing evidence of treatment failure, hazardous side effects, and appearance of strains resistant to metronidazole. In the last era, many studies have been implicated in the quest for new treatments for Blastocystis infection, especially natural products. Attention has been focused on the effect of Amygdalin (B17) and pumpkin seed on eradicating parasitic infections. The current work was built up to explore the in vitro efficacy of two natural compounds, Amygdalin (B17) and pumpkin seeds against

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