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Rules for dealing with the offender in Islamic thought
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Research summary

Today, the Islamic nation is going through a phase that is one of the most dangerous that it has never experienced before. This phase was characterized by the following:

The nation is divided into states and its weakness in most of its doctrinal, political, social, economic and moral aspects.
Enemies targeting the nation's faith and capabilities, and the emergence of loyalty to the enemies of the nation from some groups of society, spreading misconceptions in the Muslim community.
Spreading the spirit of rebellion in all segments of society and striving to stir up the people against the rulers and put pressure on the rulers.

All these manifestations and others require the nation's wise men to study, review and find appropriate solutions. Today, the enemies are waiting for us and trying hard to divide the word. It is our duty to unify the word and close ranks to face the multiple challenges.

All of this prompted me to write this research and set the rules adopted by the thinkers of Islam to reconsider our dealings with each other so as not to allow our enemies to exploit the simplest differences that lead to the rift of the fraternal ranks.

Therefore, the approach that can govern issues of disagreement must be clear through established controls from the Holy Qur’an, the purified Sunnah, and the sayings of the nation’s scholars to preserve the unity of the nation.

The integrity of the curriculum solves many disputes, brings hearts closer, strengthens the nation, and blocks the way for the enemies of the nation. In this research, a number of intellectual controls were collected to deal with the violators, adopted by preachers and thinkers, depending on the Holy Qur’an and the noble Prophet’s Sunnah, with reference to the sayings of scholars in the indication of each of them on what is intended or From what they extracted from the spirit of Sharia glue.

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Publication Date
Wed Mar 31 2021
Journal Name
Electronics
Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

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Abstract<sec><title>Objectives

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

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E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.

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A total of 63 patients with periodontitis (case) and 35

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Tue Dec 01 2020
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Application of SWAT Model for Sediment Loads from Valleys Transmitted to Haditha Reservoir
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This study included the extraction properties of spatial and morphological basins studied using the Soil and Water Assessment Tool (SWAT) model linked to (GIS) to find the amount of sediment and rates of flow that flows into the Haditha reservoir . The aim of this study is determine the amount of sediment coming from the valleys and flowing into the Haditha Dam reservoir for 25 years ago for the period (1985-2010) and its impact on design lifetime of the Haditha Dam reservoir and to determine the best ways to reduce the sediment transport. The result indicated that total amount of sediment coming from all valleys about (2.56 * 106 ton). The maximum annual total sediment load was about (488.22 * 103 ton) in year 1988

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Publication Date
Fri Dec 30 2022
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Publication Date
Sat Aug 01 2020
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Thu Dec 01 2022
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Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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A model for incorporating suitable methods of usability evaluation into agile software development
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