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Comparative Study of The Amount of Apically Extrusion Of Debris During Root Canal Preparation Using Wave Oneâ„¢, Trushape 3Dâ„¢, Hyflexâ„¢ CM and One Shapeâ„¢ Instrumentation Systems (An In Vitro Study)

Background: Many types of instruments and techniques are used in the instrumentation of the root canal system. These instruments and techniques may extrude debris beyond the apical foramen and may cause post-instrumentation complications. The aim of this study was to evaluate the amount of apically extruded debris resulted by using 4 types of nickel-titanium instruments (WaveOne, TRUShape 3D conforming files, Hyflex CM, and One Shape files) during endodontic instrumentation. Materials and methods: Forty freshly extracted human mandibular second premolar with straight canals and a single apex were collected for this study. All teeth were cut to similar lengths. Pre-weighted glass vials were used as collecting containers. Samples were randomly divided into four groups with 10 samples in each group: Group A instrumentation by WaveOne reciprocating file, Group B instrumentation by TRUShape 3D rotating files, Group C instrumentation by Hyflex CM rotating files and Group D instrumentation by One Shape rotating file. A total volume of 7 ml of sodium hypochlorite was used for irrigation in each sample. Apical patency confirmed and maintained by a size #15 K-File. All canals were instrumented up to a size #25. After completion of endodontic instrumentation, vials were then stored in an incubator for 5 days at 68o C for dryness. Then vials are weighted again, and the pre-weight subtracted from the post-weight, the weight difference resembled the amount of apically extruded debris from the apical foramen during root canal instrumentation. Data obtained were statistically analysed by using ANOVA and LSD tests. Results: The results showed that the Hyflex CM Group (C) has statistical significant lowest apically extruded debris as compared to other groups of this study (P ≤0.05), while the TRUShape Group (B) has statistical significant lowest apically extruded debris as compared to One Shape Group (D) and WaveOne Group (A), while the WaveOne Group (A) showed the highest value of apically extruded debris (p ≤0.01). The result showed that all groups resulted in apical extrusion of debris. Significance: Although all systems caused apical extrusion of debris and irrigant, continuous rotary instrumentation was associated with less extrusion as compared with the use of reciprocating file system.

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Publication Date
Sun Jan 26 2020
Journal Name
Iraqi Journal Of Science
Electro polymerization for (N-Terminal tetrahydrophthalamic acid) for Anti-corrosion and Biological Activity Applications

The present work reports the electrochemical synthesis of poly N Terminal tetrahydrophthalamic acid on stainless steel 316 (S.S), which acts as a working electrode, using an electrochemical polymerization technique. Fourier Transform Infrared Spectroscopy (FT-IR), Atomic Force Microscope (AFM) and Scanning Electron Microscope (SEM) characterized the formed polymer film. Corrosion protection tests for coated and uncoated S.S with polymer film were studied in 0.2 M hydrochloric acid (HCl) solution by using electrochemical polarization technique. Kinetic and thermodynamic activation parameters (Ea, A, ΔH*, ΔS* and ΔG*) were calculated. The biological activity of the polymeric film was determined against Gram positive (Staphy

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Wed Jan 24 2018
Journal Name
The Journal Of Physical Chemistry C
Novel Approach for Fabricating Transparent and Conducting SWCNTs/ITO Thin Films for Optoelectronic Applications

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Publication Date
Wed Nov 01 2023
Journal Name
The Saudi Dental Journal
Salivary lactate dehydrogenase and salivary total protein as potential biomarkers for screening periodontal disease

Abstract Background: Timely diagnosis of periodontal disease is crucial for restoring healthy periodontal tissue and improving patients’ prognosis. There is a growing interest in using salivary biomarkers as a noninvasive screening tool for periodontal disease. This study aimed to investigate the diagnostic efficacy of two salivary biomarkers, lactate dehydrogenase (LDH) and total protein, for periodontal disease by assessing their sensitivity in relation to clinical periodontal parameters. Furthermore, the study aimed to explore the impact of systemic disease, age, and sex on the accuracy of these biomarkers in the diagnosis of periodontal health. Materials and methods: A total of 145 participants were categorized into three groups based

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Involutive Gamma Derivations on n-Gamma Lie Algebra and 3- Pre Gamma -Lie Algebra

     In this paper, the structure of  and  have  been introduced and studied. We also obtain that a is  of a  if and only if there exists an  on such that . In addition, we obtain  that  of if and only if there is an   on  such that  , where  are subspaces of  with eigenvalues 1 and  −1, respectively. We also find  t that the existence of  on  implies that there exists a compatible  under appropriate condition.

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Publication Date
Sat Apr 06 2024
Journal Name
Al- Anbar Medical Journal
Metastatic Ovarian Tumor from Incidental Renal Cell Carcinoma: A Case Report and Literature Review

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Publication Date
Thu Jun 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Image encryption based on combined between linear feedback shift registers and 3D chaotic maps

Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signa

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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Scopus (6)
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges

The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

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