Effect of Artificial Aging Test on PEEK CAD/CAM Fabricated Orthodontic Fixed Lingual Retainer

Riyadh A Ruwiaee; Akram F Alhuwaizi

doi:10.26477/jbcd.v34i2.3147

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Publication Date

Wed Jun 15 2022

Journal Name

Journal Of Baghdad College Of Dentistry

Volume

34

Issue Number

2

DOI

10.26477/jbcd.v34i2.3147

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Effect of Artificial Aging Test on PEEK CAD/CAM Fabricated Orthodontic Fixed Lingual Retainer

PEEK

fixed lingual retainer

Single Bond Universal

artificial aging

Riyadh A Ruwiaee

Akram F Alhuwaizi

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Background: The purpose of this study was to evaluate the effect of in vitro long-term simulation of oral conditions on the bond strength of PEEK CAD/CAM lingual retainers.

Material and methods: The sample consisted of 12 PEEK CAD/CAM retainers each composed of 2 centrally perforated 3x4mm pads joined by a connector. They were treated by 98% sulfuric acid for 1 minute and then conditioned with Single Bond Universal and bonded to the lingual surface of premolar teeth by 3M Transbond TM System. Half of the retainers were artificially aged using a 30-day water storage and 5000 thermocycling protocol before bond strength testing to compare with the non-aged specimens.

Results: The artificially aged retainers showed a marginally lower bond strength than the non-aged retainers. However, independent sample t-test indicated that this difference was statistically not significant.

Conclusion: The durability of the PEEK lingual retainer adhesive system has been confirmed using the well-known oral simulating artificial aging protocol of water storage and thermocycling.

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Publication Date

Fri Apr 01 2022

Journal Name

Journal Of Engineering

Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks

Dunya S.

Khalid R.

Zeyad S. M.

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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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(3)

Publication Date

Tue Jun 30 2015

Journal Name

Iraqi Journal Of Chemical And Petroleum Engineering

Using the Artificial Gas Lift to Increase the Productivity of Noor Oil Field / Mishrif Formation

Artificial gas

Noor oil field

Talib A.

Safaa H.

Shaymaa A. Hussein

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Noor Oil Field is one of Iraqi oil fields located in Missan province / Amarah city. This field is not subjected to licensing rounds, but depends on the national effort of Missan Oil Company. The first two wells in the field were drilled in seventies and were not opened to production until 2009. The aim of this study is to study the possibility of using the method of gas lift to increase the productivity of this field . PROSPER software was used to design the continuous gas lift by using maximum production rate in the design.

The design was made after comparing the measured pressure with the calculated pressure, this comparison show that the method of Beggs-Brill and Petroleum Exper

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Publication Date

Sun Jan 01 2023

Journal Name

Ssrn Electronic Journal

Increasing Safety in Highways Transit Systems by Using Ethical Artificial Intelligence AI

Increasing Safety

Highways Transit Systems

Using Ethical Artificial Intelligence AI

Rasha

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“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

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Publication Date

Wed Jun 07 2023

Journal Name

Journal Of Educational And Psychological Researches

Multiple Intelligence Test Item Selection-Based on Howard Gardner's MI Model Using a Generalized Partial Estimation Model: Ministry of Education \ Karkh First Directorate of Education

: multiple intelligence test

generalized partial estimation form

Ohoud

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The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits

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Publication Date

Mon Jul 01 2019

Journal Name

Journal Of Educational And Psychological Researches

Test Wisdom of Postgraduates at the University of Samarra and Its Relationship to Learning and Psychological Tension: Test Wisdom of Postgraduates at the University of Samarra and Its Relationship to Learning and Psychological Tension

eligibility test

test-wisdom

engagement

psychological tension

sahib Asaad Weis

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Abstract

The aim of the present research is to identify the test wisdom and the preoccupation with learning and psychological tension among postgraduate students at the University of Samarra according to the variables of the department, gender, age, and employee or non-employee, and revealing the relationship between the test wisdom and the preoccupation with learning and psychological tension. The research sample consisted of (75) students randomly selected from postgraduate students at the college of Education. The researcher applies test –wisdom of (Mellman & Ebel) and measurement of preoccupation with learning prepared by (Al-zaabi 2013) also, the researcher used the scale of t

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Publication Date

Sat May 31 2025

Journal Name

3rd International Scientific Conference For Human And Social Studies And Epistemological Challenges

Frankenstein Complex in Daniel H. Wilson's Robopocalypse ( ): Artificial Intelligence Conspiracies

With the advent of technology

the fear of losing control has consistently accompanied humanity. While humans have discovered

invented

and created many remarkable things

they have also been haunted by the possibility of their creations turning against them. This fear

often referred to as the Frankenstein Complex

derives its name from Mary Shelley's Frankenstein (􀀔􀀛􀀔􀀛)

in which Dr. Frankenstein's creation ultimately destroys its maker. The Frankenstein Complex embodies the subconscious fear of artificial intelligence (AI) surpassing and potentially dominating humankind. This apprehension has inspired numerous literary works

including Daniel H. Wilson’s novels. The present study examines the widespread fear of AI

which has fueled conspiracy theories in literature. These theories have not only amplified public anxiety but also hindered understanding among those with limited knowledge of AI and robotics. Dr. Wilson

a robotics expert

uses his imagination as a driving force for both his writing and his inventions. The research focuses on incidents leading to the rise of robots

the concept of the New War

how it was fought

and how it concluded. By comparing

contrasting

and analyzing literary elements and devices with prominent conspiracy theories

the study highlights the interplay between fiction and scientific development. The researchers conclude that while many conspiracy theories contain elements of truth

they often inspire scientists to explore them further. Additionally

some conspiracy theories warrant serious consideration. The study recommends acknowledging the Frankenstein Complex while maintaining faith in the potential benefits of artificial intelligence.

Ansam

Mayada

Zahraa

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Publication Date

Thu Jun 23 2022

Journal Name

American Scientific Research Journal For Engineering, Technology, And Sciences

A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks

5G

4G

Congestion Control (CC)

Artificial Intelligent (AI)

Machine Learning (ML)

Deep Learning (DL)

Maab

Omar

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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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Publication Date

Mon Jan 01 2024

Journal Name

Baghdad Science Journal

Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection

Adverse Drug Reaction

Artificial Neural Network

Classification

Deep Learning

Latent Semantic Analysis

احمد

Nazlia

Zohaa Mubarak

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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date

Tue Jan 01 2019

Journal Name

Opcion

Enhancing Islamic Concepts through English Children's Lit-erature: Al- Ibtila, The Test of Patience

Mayada

Ansam

Noor

...Show More Authors

Publication Date

Sun Apr 06 2008

Journal Name

Diyala Journal For Pure Science

Preliminary Test Bayesian –Shrunken Estimators for the Mean of Normal Distribution with Known Variance

Maha

...Show More Authors

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