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The mechanism of managing religious difference
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The mechanism of managing religious difference

God is the Lord of the worlds, forget them and their jinn, Arabs and non-Muslims, He is the Lord of Muslims and Lord of non-Muslims, as He created them male and female despite their differences in tongues and colors, so He created them according to their diversity and distinction in beliefs and religions.

 To prevent flare-ups due to differences, the Lord of the worlds set limits that he has forbidden to cross, and draw clear maps as mechanisms for managing religious differences and lifting psychological barriers between the different, so that they can coexist in peace and freedom, each adhering to his faith, and practicing the rituals of his religion.

This is the nature of religious difference and this is how this difference is managed, and it is driven by a divine will that was organized to respect diversity and prevent disharmony and fighting. Rather, their Lord drew them mechanisms and controls to continue the march of this diversity in harmony without the encroachment of one sect on another, with the legitimacy of the call to God and intellectual scramble Moderate in order to achieve the right and bear the responsibility of what a person chooses in terms of belief and behavior in life.

Among these controls and mechanisms: God Almighty’s acknowledgment that all human beings are from Adam, their differences are legitimate from a divine law, united by the circle of human brotherhood that accommodates all, the right to call for truth, dialogue in the best way, and respect for the sanctities of others and the religious symbols of sects, while adhering to forgiveness, forgiveness and documentation The bonds of closeness and leaving the matter to the Lord of the worlds to separate truth and falsehood in the Hereafter, and He is the wisest of the rulers.

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Publication Date
Mon Apr 07 2025
Journal Name
Al-nahrain Journal For Engineering Sciences
Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification
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Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

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Publication Date
Wed Jun 29 2022
Journal Name
College Of Islamic Sciences
The difficulties facing literary sixth students in studying modern and contemporary history from their point of view
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  The research aims to find out the difficulties of studying the subject of modern and contemporary history and its proposed solutions from the point of view of the students of the literary sixth in the secondary schools of the Directorate of Education Rusafa I-Baghdad, the research community of students of the literary sixth stage, which Number(150) students,and to achieve the- And Fisher's equation-and percent weight).The results showed the existence of a number of real difficulties achieved for the study of modern and contemporary history of the sixth literature, and the data showed the existence of Unreal difficulties diagnosed from the students ' point of view .In light of this, the researcher dev

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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 ob

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Publication Date
Fri Jan 01 2021
Journal Name
Analytical And Bioanalytical Chemistry Research
Mutual Derivatization in the Determination of Dapsone and Thymol Using Cloud Point Extraction Followed by Spectrophotometric Detection
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A procedure for the mutual derivatization and determination of thymol and Dapsone was developed and validated in this study. Dapsone was used as the derivatizing agent for the determination of thymol, and thymol was used as the derivatizing agent for the determination of Dapsone. An optimization study was performed for the derivatization reaction; i.e., the diazonium coupling reaction. Linear regression calibration plots for thymol and Dapsone in the direct reaction were constructed at 460 nm, within the concentration range of 0.3-7 μg ml-1 for thymol and 0.3-4 μg ml-1 for Dapsone, with limits of detection 0.086 and 0.053 μg ml-1, respectively. Corresponding plots for the cloud point extraction of thymol and Dapsone were constructed

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Publication Date
Mon May 22 2023
Journal Name
Journal Of Applied Business And Technology
Toxic Workplace, Mental Health and Employee Well-being, the Moderator Role of Paternalistic Leadership, an Empirical Study
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Based on previous research results that recognized the role of paternalistic leadership in promoting a positive work climate, this study explored the impact of a toxic work environment on the mental health and well-being of employees. We used the quantitative methodology to collect and analyze data. A sample of 108 participants from Iraqi internet service provider (ISPs) companies represented the purposive study sample. We targeted employees who experienced the COVID-19 pandemic. All data was collected through an electronic questionnaire (Google and Microsoft Forms). The research model was tested using structural equation modeling (SEM). The results showed a negative effect of the toxic workplace on the mental health of employees. T

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Publication Date
Tue Dec 24 2024
Journal Name
Malaysian Journal Of Mathematical Sciences
Exploring the Role of Hunting Cooperation, and Fear in a Prey-Predator Model with Two Age Stages
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The aim of this study is to utilize the behavior of a mathematical model consisting of three-species with Lotka Volterra functional response with incorporating of fear and hunting cooperation factors with both juvenile and adult predators. The existence of equilibrium points of the system was discussed the conditions with variables. The behavior of model referred by local stability in nearness of any an equilibrium point and the conditions for the method of approximating the solution has been studied locally. We define a suitable Lyapunov function that covers every element of the nonlinear system and illustrate that it works. The effect of the death factor was observed in some periods, leading to non-stability. To confirm the theore

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Thu Jan 19 2023
Journal Name
Plos One
Knowledge sharing behaviour among head nurses in online health communities: The moderating role of knowledge self-efficacy
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Background

Head nurses are vital in understanding and encouraging knowledge sharing among their followers. However, few empirical studies have highlighted their contribution to knowledge-sharing behaviour in Online Health Communities (OHCs). In addition, scant literature has examined the moderating role of knowledge self-efficacy in this regard.

Purposes

This study examines the moderating role of self-efficacy between the association of four selected individual factors of head nurses (i.e., Trust, Reciprocity, Reputation, and Ability to Share) and their knowledge-sharing behaviour in OHCs in Jordan.

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Publication Date
Sun Sep 22 2019
Journal Name
Baghdad Science Journal
Investigating the Histological Changes in Heart, Lung, Liver and Kidney of Male Albino Mice Treated with Ivabradine
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            The present study aimed to investigate the histological changes of heart, lung, liver and kidney which caused by different concentrations (10, 20 and 40 mg/kg) of Ivabradine. Results of the study revealed some histological changes represented by aggregation of the lymphocytes around respiratory bronchioles of the lung. In the liver, the drug caused hepatocyte necrosis and infiltration of the lymphocytes. In Kidney, there are no histopathological modifications in the tissue after the animals treated with 10 mg\kg of Ivabradine. When the animals treated with Ivabradine drug at 20mg/kg of bw, dose showed vascular congestion between myocardial fibers of heart. Emphysematous c

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Application of GIS technique in the studies on fish assemblages in Shatt Al-Arab River, Basrah, Iraq
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The present study has examined the spatiotemporal varieties of the demographics of the Shatt Al-Arab River fishes and their relation to some ecological components. The aim is to forecast these groups in the unexplored parts of the waterway with an emphasis on environmental indices of diversity. Three sites in the river were selected as an observation and study of these species, which lasted from March 2019 to February 2020, the study dealt with factors affecting fishes, as Water Temperature (WT), Dissolved Oxygen (DO), Potential Hydrogen Ion (pH), Salinity (Sal), and Transparency (Tra). Gill nets, cast nets, hooks, and hand nets were adopted to collecting fish. The results indicated that the fish population comprises 60 species represent

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