The Antifungal Effect of Propolis Endodontic Irrigant with Three Other Irrigation Solutions in Presence and Absence of Smear Layer: An In Vitro Study

Introduction: the aim of this in vitro study was to compare the antifungal effect of propolis as an endodontic irrigant agent with a mixture of doxycycline, citric acid, and a detergent (MTAD), 2% chlorhexidine (CHX) and 3% sodium hypochlorite (NaOCl) against Candida albicans in presence and absence of smear layer. Methods and Materials: Extracted teeth with single canals (n=104) were prepared and randomly distributed into four experimental groups; 30% propolis, MTAD, 2% CHX and 3% NaOCl. Each group had two subgroups; with and without smear layer. The antifungal effectiveness was evaluated. The Kruskal-Wallis and Mann-Whitney tests were used to compare the overall effectiveness of different treatments at significance level of 0.05. Results: Propolis, CHX and NaOCl had similar levels of effectiveness to each other against C. albicans, and these levels were not affected by the presence or absence of the smear layer. Each irrigant was significantly more effective than MTAD or saline solution. MTAD was less effective in the presence of the smear layer than in its absence. Conclusions: Propolis irrigation can produce root canals that are free of C. albicans, even in the presence of the smear layer. Keywords: Candida albicans; Chlorhexidine; Irrigating Solution; Propolis; Smear Layer; Sodium Hypochlorit

Morphometric Analysis of the Mandibular Canal, Anterior Loop, and Mental Foramen: A Cone-Beam Computed Tomography Evaluation

This study investigated the cone-beam computed tomography (CBCT)-based features of the mandibular canal, mental foramen, anterior loop, and accessory mental foramina with respect to age and sex. A total of 306 CBCT mandibular images were included in this retrospective study to measure the mandibular canal location and extension, the mental foramen position, the presence of the anterior loop, and the accessory mental foramina. The measurements were obtained in sagittal, coronal, and axial views. Descriptive statistics are presented. Sex-related differences, correlations, and comparisons were calculated using SPSS at 5% significance level. The mandibular canal was located more coronal and medial in male patients. The majority of cases had the mental foramen located just apical to the mandibular second premolar with a mean height of 2.94 mm and a mean length of 3.28 mm. Age affected the size of the mental foramen. The mental canal in all cases tended to show a coronal direction. Mesial extension of the anterior loop was found in 66.01% of the images while accessory mental foramina were detected in 2.6%. The complexity of the mandibular canal, mental foramen, anterior loop, and accessory mental foramina among Sudanese patients with respect to age and sex was confirmed

The effect of reduced glutathione on the toxicity of silver diamine fluoride in rat pulpal cells

Introduction: Due to its ability to arrest untreated dental caries, silver diamine fluoride (SDF) has been advocated for indirect pulp capping procedures. However, the high concentrations of silver and fluoride in SDF raise concerns about its biocompatibility to pulpal tissues. Objectives: This study aimed to investigate the effect of SDF on the viability, alkaline phosphatase (ALP) activity, and morphology of pulpal-like cells (RPC-C2A) and to evaluate the influence of reduced glutathione (GSH) on SDF-induced cytotoxicity and deposit formation on dentin. Methodology: The cytotoxicity of diluted 38% SDF solutions (10-4 and 10-5), with or without the addition of 5 mM or 50 mM GSH, was evaluated at 6 and 24 hours. Cell viability was detected using WST-8 and the effect on ALP activity was performed using an ALP assay kit. Cell morphology was observed using a phase-contrast microscope. Scanning electron microscopy analysis was conducted to evaluate the effect of GSH incorporation or conditioning on SDF-induced deposit formation on dentin discs. Cytotoxicity data were analyzed by two-way analysis of variance (ANOVA) and Tukey post hoc tests (p<0.05). Results: There were significant differences between the groups. The results demonstrated that all tested SDF dilutions caused a remarkable cytotoxic effect, while the addition of GSH prevented SDF-induced damage at 6-hour exposure time in the higher dilution of SDF. Dentin treated with plain SDF or GSH-incorporated SDF solution showed deposit formation with occluded dentinal tubules, unlike the other groups. Conclusion: SDF severely disturbed the viability, mineralization-ability, and morphology of pulpal-like cells, while controlled concentrations of GSH had a short-term protective effect against SDF-induced damage. GSH showed an inhibitory effect on SDF-induced dentinal deposit formation. Further research is warranted to evaluate the effect of GSH on caries-arresting, anti-hypersensitivity, and antibacterial functions of SDF

Psychological distress among undergraduate dental students in Saudi Arabia and its coping strategies—a systematic review

The objective of this paper was to evaluate the studies that have reported on psychological issues among dental students in Saudi Arabia and to develop coping strategies to overcome these mental health-related issues. The present systematic review is in accordance with the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The search for the articles was carried out in the electronic databases by four independent researchers. The data search was performed in the electronic search engines like PubMed, Google Scholar, Web of Science, Scopus, Medline, Embase, Cochrane and Saudi Digital Library for scientific research articles published from January 2000 until December 2020. STROBE guidelines were adopted for qualitative analysis of six articles which met the eligibility criteria. The analysis of the literature revealed that most of the studies included were conducted in the past 8 years in different regions of Saudi Arabia. Findings of this systematic review clearly state that dental students in Saudi Arabia experience higher levels of depression, stress and anxiety and stress during their education period, with a higher stress for female students compared to male students. There is an urgent need to introduce interventional programs and preventive strategies to overcome the long-term effects

Pixel design and characterization of high-performance tandem OLED microdisplays

Organic Light-Emitting Diode (OLED) microdisplays - miniature Electronic Displays comprising a sandwich of organic light emitting diode over a substrate containing CMOS circuits designed to function as an active matrix backplane – were first reported in the 1990s and, since then, have advanced to the mainstream. The smaller dimensions and higher performance of CMOS circuit elements compared to that of equivalent thin film transistors implemented in technologies for large OLED display panels offer a distinct advantage for ultra-miniature display screens. Conventional OLED has suffered from lifetime degradation at high brightness and high current density. Recently, tandem-structure OLED devices have been developed using charge generation layers to implement two or more OLED units in a single stack. They can achieve higher brightness at a given current density. The combination of emissive-nature, fast response, medium to high luminance, low power consumption and appropriate lifetime makes OLED a favoured candidate for near-to-eye systems. However, it is also challenging to evaluate the pixel level optical response of OLED microdisplays as the pixel pitch is extremely small and relative low light output per pixel. Advanced CMOS Single Photon Avalanche Diode (SPAD) technology is progressing rapidly and is being deployed in a wide range of applications. It is also suggested as a replacement for photomultiplier tube (PMT) for photonic experiments that require high sensitivity. CMOS SPAD is a potential tool for better and cheaper display optical characterizations. In order to incorporate the novel tandem structure OLED within the computer aided design (CAD) flow of microdisplays, we have developed an equivalent circuit model that accurately describes the tandem OLED electrical characteristics. Specifically, new analogue pulse width modulation (PWM) pixel circuit designs have been implemented and fabricated in small arrays for test and characterization purposes. We report on the design and characterization of these novel pixel drive circuits for OLED microdisplays. Our drive circuits are designed to allow a state-of-the-art sub-pixel pitch of around 5 μm and implemented in 130 nm CMOS. A performance comparison with a previous published analogue PWM pixel is reported. Moreover, we have employed CMOS SPAD sensors to perform detailed optical measurements on the OLED microdisplay pixels at very high sampling rate (50 kHz, 10 μs exposure), very low light level (2×10-4 cd/m2) and over a very wide dynamic range (83 dB) of luminance. This offers a clear demonstration of the potential of the CMOS SPAD technology to reveal hitherto obscure details of the optical characteristics of individual and groups of OLED pixels and thereby in display metrology in general. In summary, there are three key contributions to knowledge reported in this thesis. The first is a new equivalent circuit model specifically for tandem structure OLED. The model is verified to provide accurately illustrate the electrical response of the tandem OLED with different materials. The second is the novel analogue PWM pixel achieve a 5μm sub-pixel pitch with 2.4 % pixel-to-pixel variation. The third is the new application and successful characterization experiment of OLED microdisplay pixels with SPAD sensors. It revealed the OLED pixel overshoot behaviour with a QIS SPAD sensor

Hardware Accelerated Aerial Image Simulation by FPGA

這篇論文是在討論如何使用FPGA替空間成像模擬作硬體加速。目前這種模擬系統大至都建構在以軟體為基礎的電腦上，因為如果說使用純硬體去解決的話，將會花費較長的設計時間並且難以除錯。使用硬體最大的優勢就在於它的效率十分良好，在一個晶片裡面我們可以用平行化的方式讓多個處理器去做加速。 這篇論文主要的核心就是我們如何發展一個使用FPGA的空間成像模擬器。為了要做快速的模擬，我們最好在稀疏的點去計算影像強度，避免在一般高密度的網格做計算[1]。我們一開始使用了Hopkins的部份一致性成像方程式 (Hopkins partially coherent imaging equations)，這個分 解又被稱為一致性的加總系統結構 (sum of coherent systems - SOCS)。為了要實現這個分解法 ，我們採用了奇異值分解 (singular value decomposition – SVD)，這在之後會在做詳細的說明。 我們知道， 其實每一個一致性系統就是一個線性平移不變 (linear shift invariant system – LSI) 系統， 所以我們可以應用超位置 (superposition)去計算它的卷積 (convolution)。 這部份使 用的輸入 資料，其實是一個 由像是曼哈頓二元幾何光柵的 矩形組合成的 一個函數，空間 成像的計 算可以更進一步的利用IC光柵模範 (mask pattern) 的結構 做加速。我們使用了 一個以查表 為核 心的技術，去處理對於由矩 形組成的光 柵函數一般卷積， 包含了任意的卷 基核心 (kernel)。對於SOCS裡的 N x N 個卷積 核心，被查詢的表格需要O (N x N) 的空間。在 [1] 這篇文獻中指出， 為了要得到 一個點的強度，我們需要 O (Na x Mr) 的計算，其中 Na是高階近似光 學系統的 最高次方項，Mr 是描述光柵區域的矩形個 數。但是透過 FPGA的平行加 速，這 個計算複雜度可以減少成 O (Mr)。在最先進的 模擬技術中， 我們越來越需 要使 用高階近似的光學系統，我們很清楚的可以看到FPGA 是如何有效率的降 低每一個點的強度計算，特別是FPGA它可以做平行處理，以及使用ROM 來加速運算的特性。 在專案最初的階段，我們用XESS公司所設計XSV-800 的 FPGA板去實現這個模 擬系統。 但是相較於大型以及真實的模擬系統，我們舊版本的FPGA板在硬體資源上就顯得不足。雖然 Xilinx 最新版本的 FPGA – Virtex 5 提供了更好的環境， 但很 遺憾我們實驗室並沒有辦 法取得這些設備。我們決定使用合適的軟體去模擬這個系統，它在效能上和功能性都有很好的結果。我們的FPGA內部是使用Verilog程式碼撰寫，用來控制晶片並實現整個空間成像模擬的設計。This thesis describes a hardware implementation of aerial image simulation in lithography using an FPGA (Field Programmable Gate Array). Such simulators are presently performed using mainly software-based techniques on dedicated computers, as designing pure hardware solutions can be slower and harder to debug. The advantage of hardware designs is in performance, as one chip could be used to parallelize many processes at the same time. A major contribution of this thesis is the development of an aerial image simulator which is accelerated by FPGA. For fast simulation, it is best to compute intensity of image at sparse points rather than on a regular dense grid [1]. We begin with the decomposition of the Hopkins partially coherent imaging equations, this decomposition is called sum of coherent systems (SOCS) structure. The implementation of this decomposition is done numerically by using singular value decomposition (SVD) which is described in detail. It is shown that each of the coherent system is a linear shift invariant (LSI) system, so the convolution can be used to compute their outputs by applying superposition. The data input used here is a function which is consisting of rectangles as Manhattan geometry mask with just two transmission values, e.g. binary masks, the aerial image calculation can be further sped up by utilizing the structure of IC mask patterns. For general convolution of mask functions, consisting of rectangles, with arbitrary convolution kernels, a lookup technique is used and the process is outlined. The storage size needed for lookup tables is numbers for each convolution kernel in the SOCS. In [1] it was shown that to achieve single point intensity computation needs computation on the order of where is the order of approximation to the optical system and is the number of rectangles in the mask region description, but this computation is decreased efficiently by using FPGA to parallelize this operation to yield a computation on the order of . It is clearly shown how FPGA can be utilized efficiently to reduce the cost of each single point intensity computation, since highly demand of high order of approximation order for optical systems is needed nowadays in such simulators, and also the nature of FPGA with spatial computational style and enhanced inherent operations and blocks inside it. The implementation discussed herein uses the XSV-800 FPGA board designed by XESS Corporation in the first stage of this project to implement a simple system. But for bigger and real aerial image simulators, and lacking of hardware resources in old versions of FPGAs, a latest FPGA chip from Xilinx, Virtex 5, is used for this purpose. Because of unavailability of this kind of FPGA’s board in our lab, we decided to study our system by simulating it by suitable software which gives a good indication of performance and functionality. The FPGA is configured with code designed in Verilog that handles control of the chips involved to implement an aerial image simulator design.摘要 iii Abstract v Acknowledgements vii Table of Contents viii List of Figures xi List of Tables xii Chapter 1 Introduction 1 1.1 Introduction to Aerial Imaging 3 1.1.1 The Image Formation Model 3 1.2 Lithography Model 6 1.2.1 Mask Writing 6 1.2.2 Optical System 6 1.2.3 Resist Development 7 1.2.4 Etching 7 1.3 Lithography Basic Components 7 1.3.1 Critical Dimension 8 1.4 Importance of Lithography Simulation 8 1.5 FPGA Solution 9 1.5.1 Hardware vs. Sofiware -) Spatial vs. Temporal 10 1.5.2 FPGAvs. CPU 11 1.6 FPGA Design Flow 12 1.7 Problem Definition 15 1.7.1 General Problem 16 1.7.2 Aerial Image Quality 16 1.8 Review of Previous Work 17 Chapter 2 Partially Coherent Systems 18 2.1 Coherent Decompositions of Partially Coherent Imaging Systems 18 2.2 Hopkins Imaging Equation 20 2.2.1 Preliminary Results 20 2.2.2 Sum-Of-Coherent Systems 21 2.3 Modeling the results 22 2.4 2-D Kernel Determination 23 Chapter 3 Aerial Image Computation Modeling 26 3.1 The Aerial Image Model 27 3.2 Intensity Point Calculation 28 3.3 Mask Representation 29 3.4 General Function Convolution with a Mask 30 3.5 Kernel Lookup Tables 32 3.6 Fast Aerial Image Simulation 33 Chapter 4 Hardware Environment 36 4.1 Description of Board 36 4.1.1FPGA 37 4.1.2CPLD 37 4.1.3 RAMDAC and VGA Monitor Interface 38 4.1.4SRAM 38 4.2 Verilog/ Xilinx ISE 9.li 38 4.2.1 Verilog 39 4.2.2 The ISE Series 39 4.2.3 Xilinx Core Generator 40 4.3 Summary 40 ChapterS Design Implementation and Evaluation 41 5.1 Aerial Image Model 41 5.2 Kernels 42 5.2.1 Initialization 43 5.3 Aerial Imaging 43 5.3.1 Mask Decomposition 43 5.3.2 Slit Windowing 44 5.3.3 Intensity Point 44 5.3.4 Memories 45 5.3.5 Memory Addresses 46 5.4 FPGA Timing Summary 46 5.5 Design Evaluation 47 5.5.1 Aerial Image Simulation Test Cases 47 5.5.2 Comparisons 49 Chapter 6 Conclusions and Future Developments 54 6.1 Conclusions .54 6.2 Future Developments .55 Bibliography 5

Shallow Depth Map Estimation from Image Defocus Blur Point Spread Function Information

The aim of this research is addressing both the influence of the limited aperture size of the optical imaging system of the camera, and the defocus aberration influence on output images in order to measure useful information such as defocus and depth through the MTF (Modulation Transfer Function), further we analyze the existing defocus levels by measuring the size of blur kernels. One of the goals of our study is to make shallow depth photos with blurry background; photographers need to use cameras such as SLR (single-lens reflex) not only for carefully choosing the best position with respect to the object but also changing the lens effective focal length or aperture size in order to obtain an artistic effect mostly desired in many types of photographs (e.g. portraits), which is not available for normal camera users who prefer to use low cost compact point-and-shot cameras; for their ease of use and convenience. Nowadays, the size of TFT-LCDs (thin-film-transistor liquid-crystal displays) is getting larger, as a result; it becomes harder to inspect defects that may exist which usually require a human visual examiner to judge the severity of the defects on the final product. These defects; so called mura (Japanese shorthand) are defined as visual blemish with non-uniform shapes and boundaries. It is becoming a very serious unpleasant effect which needs to be detected and inspected in order to characterize the LCD’s quality. Through this research, we essentially propose two contributions. One that given only two images taken under different camera parameters, we measure a reliable defocus map based on scale-space analysis, then we propagate the defocus measures over edges to the entire image using matting process, eventually we will have a refined dense defocus map, which is utilized in applications such as amplifying the existing blurriness yielding a shallow depth photos from all focused images. On the other hand, it helps extracting the foreground object shape and isolating it from the background. The second contribution is experimentally detecting many types of MURA defects on LCD panels by some low-complex effective post-processing imaging techniques. Practically; we utilize the computational photography techniques to amplify defocus levels and to detect low contrast defects such as MURA. Our Computational techniques will allow the average photographers to capture more appealing photos, and the LCD manufacturers to increase their Engineer’s efficiencies and performance. We strongly proof that this study will enable cameras and automated vision systems to embed useful computation with few user interventions.The aim of this research is addressing both the influence of the limited aperture size of the optical imaging system of the camera, and the defocus aberration influence on output images in order to measure useful information such as defocus and depth through the MTF (Modulation Transfer Function), further we analyze the existing defocus levels by measuring the size of blur kernels. One of the goals of our study is to make shallow depth photos with blurry background; photographers need to use cameras such as SLR (single-lens reflex) not only for carefully choosing the best position with respect to the object but also changing the lens effective focal length or aperture size in order to obtain an artistic effect mostly desired in many types of photographs (e.g. portraits), which is not available for normal camera users who prefer to use low cost compact point-and-shot cameras; for their ease of use and convenience. Nowadays, the size of TFT-LCDs (thin-film-transistor liquid-crystal displays) is getting larger, as a result; it becomes harder to inspect defects that may exist which usually require a human visual examiner to judge the severity of the defects on the final product. These defects; so called mura (Japanese shorthand) are defined as visual blemish with non-uniform shapes and boundaries. It is becoming a very serious unpleasant effect which needs to be detected and inspected in order to characterize the LCD’s quality. Through this research, we essentially propose two contributions. One that given only two images taken under different camera parameters, we measure a reliable defocus map based on scale-space analysis, then we propagate the defocus measures over edges to the entire image using matting process, eventually we will have a refined dense defocus map, which is utilized in applications such as amplifying the existing blurriness yielding a shallow depth photos from all focused images. On the other hand, it helps extracting the foreground object shape and isolating it from the background. The second contribution is experimentally detecting many types of MURA defects on LCD panels by some low-complex effective post-processing imaging techniques. Practically; we utilize the computational photography techniques to amplify defocus levels and to detect low contrast defects such as MURA. Our Computational techniques will allow the average photographers to capture more appealing photos, and the LCD manufacturers to increase their Engineer’s efficiencies and performance. We strongly proof that this study will enable cameras and automated vision systems to embed useful computation with few user interventions.中文口試委員審定書 ii 英文口試委員審定書 iii Abstract iv Acknowledgements vi Dedication vii Table of Contents viii List of Figures xii List of Tables xvii Chapter 1 Introduction 18 Chapter 2 Background and Preliminaries 22 2.1 Geometrical Imaging and Camera Model 22 2.1.1 f-number: N 25 2.2 Point Spread Function (PSF) 26 2.2.1 Wave Optics: Airy Disk PSF 26 2.2.2 Circle of Confusion: coc 29 2.2.3 Focal Gradient 31 2.2.4 Sensor Size Effect 33 2.2.5 Defocus Aberration Model 34 2.2.6 Depth of Field: The Circle of Confusion is Fixed 37 2.3 Optical Transfer Function (OTF) 40 Chapter 3 Depth Map Estimation from Defocus Blur PSF Information 43 3.1 Introduction 43 3.2 Previous and Related Work 44 3.3 Depth from Focus Process: DFF 49 3.4 Blur Estimation from Defocus Information 50 3.4.1 Sparse Defocus Estimation from One Image 54 3.4.2 Defocus Estimation from Two Images 63 3.5 Defocus Estimation Enhancement 69 3.5.1 Sparse Blur Map Post-Processing 70 3.5.2 Image Blocks neighborhood effect 72 3.5.3 Image Zoom Calibration 73 3.5.4 Scale-Space Image Processing 75 3.6 Defocus Propagation and Interpolation 81 3.6.1 Defocus Propagation by Alpha-Matting 81 3.7 Depth from Defocus Process Implementation Using Two Images 84 3.7.1 Input Image Preparation and Smoothing 85 3.7.2 Parsavel’s Theorem (Energy Theorem) and Laplacian Filter 85 3.7.3 Calibration Process 87 3.7.4 Depth Map Measurement 88 3.7.5 Implementation Flow-chart 90 3.8 Experimental Results 94 3.8.1 Computer Environment 94 3.8.2 Cameras and Settings 94 3.8.3 Defocus Map Generation from a Single Image 95 3.8.4 Estimated Defocus Map by Two Images 97 3.9 Summary 112 Chapter 4 Automatic MURA Defect Detection and Inspection in LCD Panels 114 4.1 Introduction 114 4.2 Previous and Related Work 116 4.3 System Architecture and Approach 117 4.3.1 Pseudo-Mura Patterns 119 4.4 Mura Detection Algorithm by Segmentation 121 4.4.1 Preprocessing and Residual Image Extraction 123 4.4.2 Averaging Filter 124 4.4.3 Gradient Operation and Derivatives 125 4.4.4 The Second Derivative (Laplacian) of the Sample Image 126 4.4.5 The Fusion Operation of Two Responses 127 4.4.6 Thresholding 130 4.4.7 Morphological Post-Processing Operation 131 4.5 Experimental Results 131 4.6 Discussions 132 4.7 Summary 132 Chapter 5 Defocus Amplification and Focused Object Extraction 134 5.1 Introduction 134 5.2 Related Works 135 5.3 Image Defocus Amplification 136 5.3.1 Defocus Map Amplification Experimental Results 137 5.4 Focused Object Extraction 142 5.5 Summary 143 Chapter 6 Conclusion and Future Work 144 6.1 Summary 144 6.2 Future Work 145 Bibliography 14

Detecting the Second Mesiobuccal Canal in Maxillary Molars in a Saudi Arabian Population: A Micro-CT Study

The aim of this study was to determine MB2 canal detectability in maxillary first and second molars obtained from a Saudi population using micro-CT. Maxillary first (n=35) and second (n=30) molars were scanned with micro-CT technology. The number of canals was recorded, and in case of having more than one canal, the level of extracanal detection was analyzed. The presence of extracanal was categorized based on the level they were first detected. Among the maxillary first molars, 28 (80%) and six (17%) teeth had two and three MB canals, respectively. Among the maxillary second molars, 24 (80%) and four (13%) teeth had two and three MB canals, respectively. The MB2 canal was detected at the chamber floor in 70% and 61% of the maxillary first and second molars, respectively. At 1 mm depth, the MB2 canal was found in 15% and 18% of the maxillary first and second molars, respectively. At 2 mm depth, the MB2 canal was found in 3% and 18% of the maxillary first and second molars, respectively. The remaining teeth had the MB2 canal at levels deeper than 2 mm. The MB2 canal was detected in 97% and 93%% of maxillary first and second molars, respectively. Among them, the MB2 canal could be immediately detected in 70% and 61% of the maxillary first and second molars, respectively, once the pulp chamber is exposed. However, the rest of the MB2 were observed at deeper levels in the root and this requires troughing preparation in the chamber floor

Apical Gutta-percha cone adaptation and degree of tug-back sensation after canal preparation

Aims: The aim of this study was to investigate the degree of tug-back after canal preparation with respect to the Gutta-percha-occupied area (GPOA). Materials and Methods: Roots of twenty premolar teeth were prepared till size 35/0.04, then GP cones of same size and taper were adapted to root canals and the degree of tug-back sensation was scored as loose, slight, adequate, and strong. Root canals were filled with GP and AH26 sealer, and then sectioned horizontally 1 mm from the apical end at three levels. GPOA and its sum from the three levels sum of GPOA (sGPOA%) were calculated using digital stereomicroscope. Statistical Analysis: At each sectioned level, GPOA% was compared with the score of tug-back sensation using one-way ANOVA at a 5% significance level. Multiple pairwise comparisons were performed using Tukey test. Results: Tug-back sensation was present in all canals, described as slight, adequate, and strong in 4, 8, and 8 canals, respectively. Among the tug-back scores, quantitative analyses of GPOA% showed significant differences at 2- and 3-mm levels. The strong tug-back with sGPOA of 76.5 ± 11.1% was significantly higher than that of slight tug-back. Conclusions: Under the conditions of this study, the tug-back scoring system can be applied to determine the amount of GP adaptation inside the root canal. Strong tug-back sensation showed the highest GP adaptation although at least one-fifth of the apical canal region was left unfilled