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Efficacy of arthrocentesis with injection of hyaluronic acid in the treatment of inflammatory-degenerative disease of temporomandibular joint
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Background:Temporomandibular joint (TMJ) problems refer to a group of heterogeneous pain and dysfunction conditions involving the mastication, reducing life quality of the patients. Arthrocentesis is a simple and less invasive surgical method for the treatment of inflammatory-degenerative disease than other conservative procedures and better than arthroscope. This clinical study aimed at evaluating the benefit of arthrocentesis with injection of hyaluronic acid in the management of inflammatory-degenerative disease of the TMJ. Material and methods: Eighty consecutive patients were enrolled in this study with pain symptoms of TMJ, insufficient masticatory efficiency during function and limitation of mouth opening; they were assessed with clinical examination and approved with computed tomography scan. Arthrocentesis was done by inserting 18 gauge needles in the upper joint compartment, lavage by normal saline solution and at the end of the procedure 1ml of hyaluronic acid (HA) was injected. Intensity of the TMJ pain and masticatory efficiency was analyzed by visual analog scale (VAS), maximum mouth opening (MMO) was assessed by a ruler. All the assessed parameters were measured before the procedure then 1 and 4 months later. Results: During 5 months follow-up, comparison of the obtained results showed reduction in pain at chewing and rest 87.5%, improvement in mouth opening 100% and significant improvement in masticatory efficiency 87.5% of patients. Conclusion: The procedure of arthrocentesis with Sodium Hyaluronate injection, used in patients who suffered from inflammatory-degenerative disease (IDD), showed therapeutic benefits, simplicity, safety, patient satisfaction, lack of significant side effects and complications.

 

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Fri Jan 12 2024
Journal Name
Medaad
Bridging Traditional and Immersive Technologies in Design Education: A Comprehensive Framework for Institutional Adoption
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The significant addition of immersive technologies, Virtual Reality (VR), Augmented Reality(AR) and Mixed Reality(MR) are transforming the domain of design education. Still, finding an equilibrium between these new tools alongside with traditional methods of teaching is a menace which educational institutes needs to solve. This paper proposes a structure that would help the ease with which to include immersive technologies within design education, keeping in mind the solid points of more conventional pedagogical methods. Based on a survey of interior design programs, this research highlights the potential for VR, AR and MR in student engagement, creativity skills and professional practices. The results suggest that adoption of an im

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Publication Date
Fri Oct 31 2025
Journal Name
Mathematical Modelling Of Engineering Problems
Heterogeneous Traffic Management in SDN-Enabled Data Center Network Using Machine Learning-SPIKE Model
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Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou

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Publication Date
Tue Dec 01 2020
Journal Name
Results In Physics
Alpha clustering preformation probability in even-even and odd-A<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e3355" altimg="si39.svg"><mml:msup><mml:mrow /><mml:mrow><mml:mn>270</mml:mn><mml:mo>−</mml:mo><mml:mn>317</mml:mn></mml:mrow></mml:msup></mml:math>(116 and 117) using cluster formation model and the mass formulae : KTUY05 and WS4
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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Financial analysis indicators and their impact on investment decision-making: for the national insurance company (applied research)
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The financial analysis of the published financial statements is the means that enables businessmen, financial institutions, financial analysts and others to conduct their studies and conclusions to obtain information that helps them in the decision-making process, including decisions related to investment. National in making the decision on the investment activity, for the period from 2012 to 2018, through the information provided by the annual financial statements, by selecting a set of indicators provided by the financial statements, namely (liquidity ratio, activity percentage, profitability ratios) to measure the extent of this ability Indicators in determining their role in making an investment decision.

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Publication Date
Sat May 01 2010
Journal Name
College Of Education Journal, Al-mustansiriyah University
Artin Characters for the Special Linear Group SL(2,p) where p is a prime number  19
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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
An Enhanced Document Source Identification System for Printer Forensic Applications based on the Boosted Quantum KNN Classifier
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

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Publication Date
Fri May 17 2013
Journal Name
International Journal Of Computer Applications
Applied Minimized Matrix Size Algorithm on the Transformed Images by DCT and DWT used for Image Compression
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Examining the seasonal correlation between SSN, T-Isndex, and F10.7 parameters during solar cycles 23 and 24
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Publication Date
Fri Dec 03 2021
Journal Name
Baghdad Journal Of Biochemistry And Applied Biological Sciences
A clinical-statistical study on COVID-19 infection and death status at the Alshifaa Healthcare Center/ Baghdad
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Background: COVID-19 is an ongoing disease that caused, and still causes, many challenges for humanity. In fact, COVID-19 death cases reached more than 4.5 million by the end of August 2021, although an improvement in the medical treatments and pharmaceutical protocols was obtained, and many vaccines were released. Objective: To, statistically, analyze the data of COVID-19 patients at Alshifaa Healthcare Center (Baghdad, Iraq). Methods: In this work, a statistical analysis was conducted on data included the total number, positive cases, and negative cases of people tested for COVID-19 at the Alshifaa Healthcare Center/Baghdad for the period 1 September – 31 December 2020. The number of people who got the test was 1080, where 424 w

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