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Effective indicators of healthy cities in facing natural disasters (epidemics and diseases)
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The excessive and rapid urban growth witnessed by most cities in the world can be a cause of diseases and epidemics, especially those problems related to population, which include problems of transportation and increase in density in the centers, in addition to the lack of interest in planning and designing those cities to take into account the health aspect of the city and obtain The health well-being of the population, and each of these problems has negative effects on health in general and on human health in particular through its prevalence. Therefore, many concepts that serve as a tool for achieving public health and the physical health of the population have emerged, including the concept of city health, which is defined as cities that improve their environment and develop their resources by achieving health as urban. And the issue that must be achieved in the city and at various levels, hence the research problem. The lack of clarity of the indicators of healthy cities affecting the achievement of the health dimension of the population, and accordingly the goal of the research was determined to study the concept of healthy cities and their spatial relationship to the spread of diseases and epidemics, in order to reach effective indicators and results that contribute to reducing the speed of the spread of these diseases and epidemics, as the research assumes that: Principles can That the foundations of the concept of healthy cities have a clear impact and role in reducing epidemics. In order to achieve the goal of the research, the concept of healthy cities and the concept of epidemics and their impact on the city were dealt with in order to reach clear relationships and results that can be applied to the Iraqi city (Al-Ghadeer Village Residential Complex in Al-Najaf Al-Ashraf), where the most important results were movement, transportation, density and diversity, and each of these concepts has mechanisms for its application .

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Publication Date
Sat Aug 04 2012
Journal Name
University Of Thi-qar Journal
Prediction of Ultimate Soil Bearing Capacity for Shallow Strip Foundation on Sandy Soils by Using (ANN) Techniqu
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Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us

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Publication Date
Thu Jun 02 2011
Journal Name
Ibn Al-haithem Journal For Pure And Applied Sciences
On modified pr-test double stage shrinkage estimators for estimate the parameters of simple linear regression model
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Publication Date
Sun Sep 02 2012
Journal Name
Baghdad Science Journal
Evaluation of bread wheat Triticum aestivum L. callus genotypes for water stress tolerance using Polyethylene Glycol (PEG)
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A fixed callus weight of 150 mg was induced from immature embryos of three bread wheat Triticum aestivum L. genotypes (Tamos 2, El-izz and Mutant 1) cultured on nutrient medium {MS) containing Polyethylene glycol (PEG-6000) supplemented with concentrations (0.0, 3.0, 6.0, 9.0 or 12.0%) to evaluate their tolerance to water stress. Cultures were incubated in darkness at temperature of 25?1 ?C. Callus fresh and dry weights were recorded and soluble Carbohydrate and the amino acid Proline concentrations were determined. Results showed that there were significant differences in studied parameters among bread wheat genotypes of which Tamos 2 was higher in callus average fresh and dry weights which gave 353.33 and 38.46 mg/cultured tube respecti

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Publication Date
Wed Jun 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Studying the Factors Effects on the Flowability of ZnO-CuO/γAl2O3 Catalyst Through Hopper Before Tableting Process
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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Predicting Biochemical Oxygen Demand at the Inlet of Al-Rustumiya Wastewater Treatment Plant Using Different Mathematical Techniques
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Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor

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Publication Date
Wed Jul 11 2018
Journal Name
دراسات تربوية
Understanding the nature of the scientific endeavor among chemistry teachers according to the Educational Reform Project 2061
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Publication Date
Sat Sep 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Impact of Glycated Haemoglobin on salivary glucose among type 1 diabetic mellitus patients aged 18-22 years
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Background: Diabetes mellitus consists of a group of diseases characterized by abnormally high blood glucose levels. Glycated haemoglobin (HbA1c) is a form of haemoglobin used to identify the average concentration of plasma glucose over prolonged periods of time. It is formed in a non-enzymatic pathway by normal exposure of hemoglobin to high levels of plasma glucose, The main alterations observed in the saliva of Type 1 diabetic patients are hyposalivation and alteration in its composition, particularly those related to the levels of glucose. The aim of the present study was to assess the effect of Glycated haemoglobin level on the level of salivary glucose which may have an effect on oral health condition. Materials and methods

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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
Evaluate the Effectiveness of Agaricus bisporus (Spawn) on Control Damping – off Caused by Pythium aphanidermatum on Cucumber
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This study was conducted to test the effectiveness of Agaricus bisporus inoculums (spawn) in the ratio of (0.25, 0.5 and 1%) v/v to control Pythium aphanidermatum fungus the causal agent of damping- off disease of cucumber plant. results showed the ability of A. bisporus fungus to protect the seedlings from incidence by P. aphanidermatum . all treatments of edible fungus inoculums were significantly different from pathogen treatment after 15 day of planting and there was no significant difference found from control treatment (without pathogen) . the successful of A. bisporus was continued to protect the seedlings after 30 and 45 day after planting. The numbers of seedlings were (8, 7.25 & 7.25) respectively compared to 5.5 seedlings in con

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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