• Restorative Dentistry and Endodontics
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• v.43 no.2
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• pp.26.1-26.12
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• 2018

Objective: The purpose of this study was to investigate the degree of conversion (DC) and mechanical properties of a microhybrid Filtek Z250 (3M ESPE) resin composite after aging. Method: The specimens were fabricated using circular molds to investigate Vickers microhardness (Vickers hardness number [VHN]) and DC, and were prepared according to ISO 4049 for flexural strength testing. The initial DC (%) of discs was recorded using attenuated total reflectance-Fourier transforming infrared spectroscopy. The initial VHN of the specimens was measured using a microhardness tester under a load of 300 g for 15 seconds and the flexural strength test was carried out with a universal testing machine (crosshead speed, 0.5 mm/min). The specimens were then subjected to thermocycling in $5^{\circ}C$ and $55^{\circ}C$ water baths. Properties were assessed after 1,000-10,000 cycles of thermocycling. The surfaces were evaluated using scanning electron microscopy (SEM). Data were analyzed using 1-way analysis of variance followed by the Tukey honest significant difference post hoc test. Results: Statistical analysis showed that DC tended to increase up to 4,000 cycles, with no significant changes. VHN and flexural strength values significantly decreased upon thermal cycling when compared to baseline (p < 0.05). However, there was no significant difference between initial and post-thermocycling VHN results at 1,000 cycles. SEM images after aging showed deteriorative changes in the resin composite surfaces. Conclusions: The Z250 microhybrid resin composite showed reduced surface microhardness and flexural strength and increased DC after thermocycling.

• The Journal of Advanced Prosthodontics
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• v.11 no.4
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• pp.223-231
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• 2019

PURPOSE. The purpose of this study was to evaluate the shear bond strength (SBS) of an indirect resin composite (IRC) to the various resin matrix ceramic (RMC) blocks using different surface treatments. MATERIALS AND METHODS. Ninety-nine cubic RMC specimens consisting of a resin nanoceramic (RNC), a polymer-infiltrated hybrid ceramic (PIHC), and a flexible hybrid ceramic (FHC) were divided randomly into three surface treatment subgroups (n = 11). In the experimental groups, untreated (Cnt), tribochemical silica coating (Tbc), and Neodymium-Doped Yttrium Aluminum Garnet (Nd:YAG) laser irradiation (Lsr) with 3 W (150 mJ/pulse, 20 Hz for 20 sec.) were used as surface treatments. An indirect composite resin (IRC) was layered with a disc-shape mold ($2{\times}3mm$) onto the treated-ceramic surfaces and the specimens submitted to thermal cycling (6000 cycles, $5-55^{\circ}C$). The SBS test of specimens was performed using a universal testing machine and the specimens were examined with a scanning electron microscope to determine the failure mode. Data were statistically analyzed with two-way analysis of variance (ANOVA) and Tukey HSD test (${\alpha}=.05$). RESULTS. According to the two-way ANOVA, only the surface treatment parameter was statistically significant (P<.05) on the SBS of IRC to RMC. The SBS values of Lsr-applied RMC groups were significantly higher than Cnt groups for each RMC material, (P<.05). Significant differences were also determined between Tbc surface treatment applied and untreated (Cnt) PIHC materials (P=.039). CONCLUSION. For promoting a reliable bond strength during characterization of RMC with IRC, Nd:YAG laser or Tbc surface treatment technique should be used, putting in consideration the microstructure and composition of RMC materials and appropriate parameters for each material.

• Journal of Technologic Dentistry
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• v.39 no.2
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• pp.75-82
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• 2017

Purpose: This study provided the basic data for selection the zirconia block and CAM by means of marginal fitness observations, flexural strength test and hardness test. Methods: Three dental zirconia blocks(ABCera, NaturaZ, ST98) and two dental milling machines(CAD/CAM MS, DWX-50) were used in this study. Metal abutment(diameter 10 mm, height 5 mm, inclined angle $3^{\circ}$ taper, 1 mm chamfer margin) was fabricated by Ti customized abutment, and then zirconia copings were fabricated for each ten specimens. Silicone replica technique was used to observe the marginal fitness of cross-sections with a stereomicroscope at ${\times}50$ magnification. The dental zirconia blocks was cut into 10 pieces each having a size of $25mm{\times}5mm{\times}1mm$, and fabricated according to the manufacturer's instructions, and flexural strength was measured using a universal testing machine. For hardness test, a micro Vickers hardness tester was used as it was in the flexural strength test. Statistical analysis was performed by one way ANOVA and post-test was performed by Scheffe test. Results: For marginal fitness of bucco-lingual axial, ZU group($59.7{\pm}10.3{\mu}m$) was the lowest, followed by RA, ZA, ZD, RD, RU. For marginal fitness of mesio-distal axial, ZU group($59.3{\pm}10.2{\mu}m$) was the lowest, followed by RA, ZA, RD, ZD, RU. One-way ANOVA showed statistically significant difference between groups(p<0.05). For flexural strength, ABCera block($718.0{\pm}57.2MPa$) was the highest, followed by NaturaZ, ST98. For hardness, ABCera block($1550.3{\pm}19.8Hv$) was the highest, followed by ST98, NaturaZ. There was no significant difference in flexural strength and hardness between blocks(p>0.05). Conclusion: Based on the results of this study, the type of dental zirconia block did influence the marginal fitness, and all dental zirconia blocks are expected to be suitable for clinical application. The highest flexural strength and hardness were ABCera block, and no statistically significant difference was observed.

• Journal of dental hygiene science
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• v.11 no.5
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• pp.431-436
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• 2011

The aim of this study was to compare the effects of the short-term use of the desensitizing dentifrices marketed in Korea in vitro. Fifty human dentine specimens were wet ground with silicone carbide paper and etched with 6% citric acid for 90 seconds to allow complete opening of the dentinal tubule. Ten specimens from each group were brushed for 50 and 150 strokes with a V8 Cross Brushing Machine(Sabri Co., U. S. A). All the specimens were evaluated by SEM(${\times}3000$). The degree of occlusion of the dentinal tubules was quantified using an image analyzer. The results were analyzed by one-way ANOVA and Tukey's multiple comparisons using Window SPSS. The dentifrices containing nano-carbonate apatite, potassium nitrate and hydroxyapatite showed significantly higher occlusion effects than the other dentifrices after toothbrushing for 50 strokes(p<0.05). The Sensodyne freshmint$^{(R)}$dentifrice showed 34% fewer open tubular areas compared with the Sensodyne original$^{(R)}$dentifrice for 50 strokes. According to the short-term use of desensitizing dentifrices, the dentifrices containing nano-carbonate apatite, potassium nitrate and hydroxyapatite were most effective in occluding the dentinal tubules.

• Journal of Dental Rehabilitation and Applied Science
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• v.29 no.4
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• pp.377-383
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• 2013

This study examined the radiopacity of eight contemporary luting cements by direct digital radiography. Five disc-shaped specimens ($5mm{\times}1mm$) were prepared for each material tested (BisCem, Clearfil SA Luting, Duolink, Maxcem Elite, Multilink Speed, Panavia F 2.0, RelyX Unicem Clicker, V-link). The specimens were radiographed using a Kodak CS 7600 image plate (Carestream Health, Inc., Rochester, NY, USA) and an aluminum step wedge with a range of thicknesses (1.5 to 16.5 mm in 1.5 mm increments) and a 1 mm tooth used as a reference. A dental X-ray machine Kodak 2200 Intraoral X-ray System (Carestream Health, Inc., Rochester, NY, USA), operating at 70 kVp, 4 mA, 0.156 s and a source-to-sample distance of 30 cm, was used. According to international standards, the radiopacity of the specimens was compared with that of an aluminum step wedge using NIH ImageJ software (available at http://rsb.info.nih.gov/ij/).The data was analyzed by ANOVA and a Tukey's post hoc test. Maxcem Elite (5.66) showed the highest radiopacity of all materials, followed in order by Multilink Speed (3.87) and V-link (2.83). The radiopacity of Clearfil SA Luting (1.35), BisCem (1.33), Panavia F 2.0 (1.29) and Duolink (1.10) were between enamel (1.79) and dentin (0.19). RelyX Unicem Clicker (0.71) showed the lowest radiopacity, which was higher than that of dentin. All materials showed a radiopacity above the minimum recommended by the International Organization for Standardization and the American National Standards/American Dental Association with the exception of RelyX Unicem Clicker.

• Journal of the korean academy of Pediatric Dentistry
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• v.35 no.1
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• pp.18-29
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• 2008

The purpose of this study was to compare the polymerization shrinkage of several filling methods using strain gauges. In this study, a light-emitting diode(LED) curing unit(Elipar Freeligh2, 3M EPSE, USA) and plasma arc lamp(PAL) curing unit(Flipo, LOKKI, France) were used for curing, Filtek $Z350^{TM}$(3M EPSE, USA) composite resin was used for the cavity filling. Sixty permanent bicuspid teeth, that were extracted for orthodontic treatment, were studied. The cavities were prepared on the occlusal surface and were filled using the following methods : 1) bulk filling, 2) parallel filling, 3) oblique filling The strain was recorded on the buccal, lingual, mesial and distal surfaces and the strain values were computed into stress values. The shear bond strength of each filling method was tested using a Micro Universal Testing machine. The results can be summarized as follows: 1. In the strain changes, all LED and PAL curing groups showed an increase on the buccal surface and a slow decrease as time elapsed. 2. In the strain changes of the mesial and distal surfaces, the decreases and increases were shown repeatedly and reduced as time elapsed. 3. There were no significant statistical strain changes among filling methods in the LED or PAL curing groups. 4. There were significant statistical strain changes between the LED and PAL curing groups on the buccal surface(p<0.05). 5. From the shear bond strength results, in the LED curing group, filling method 3 showed lower surface stress than filling method 1 and 2(p<0.05). In the PAL curing group, there were no significant statistical strain changes between each filling method. 6. The surface stress of each group was lower than the shear bond strength.

• Smart Structures and Systems
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• v.25 no.5
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• pp.605-617
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• 2020

The existence of damages in structures causes changes in the physical properties by reducing the modal parameters. In this paper, we develop a two-stages approach based on normalized Modal Strain Energy Damage Indicator (nMSEDI) for quick applications to predict the location of damage. A two-dimensional IsoGeometric Analysis (2D-IGA), Machine Learning Algorithm (MLA) and optimization techniques are combined to create a new tool. In the first stage, we introduce a modified damage identification technique based on frequencies using nMSEDI to locate the potential of damaged elements. In the second stage, after eliminating the healthy elements, the damage index values from nMSEDI are considered as input in the damage quantification algorithm. The hybrid of Teaching-Learning-Based Optimization (TLBO) with Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) are used along with nMSEDI. The objective of TLBO is to estimate the parameters of PSO-ANN to find a good training based on actual damage and estimated damage. The IGA model is updated using experimental results based on stiffness and mass matrix using the difference between calculated and measured frequencies as objective function. The feasibility and efficiency of nMSEDI-PSO-ANN after finding the best parameters by TLBO are demonstrated through the comparison with nMSEDI-IGA for different scenarios. The result of the analyses indicates that the proposed approach can be used to determine correctly the severity of damage in beam structures.

• The Journal of Advanced Prosthodontics
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• v.4 no.3
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• pp.121-126
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• 2012

PURPOSE. The aim of the study was to evaluate the effect of 3 silicone primers and 3 surface characterization of acrylic resin surface on bond strength between silicone elastomer and acrylic resin. MATERIALS AND METHODS. 96 Cosmesil silicones bonded to heat-curing acrylic resin were fabricated with the dimension of $75{\times}10{\times}3$ mm. The 3 primers used in this study were G611 platinum primer, A-330 Gold platinum primer, and cyanoacrylates resin. Specimens without primer were used as control. The 3 types of surface characterization done were retentive holes with 1.5 mm in diameter and 0.5 mm deep, retentive beads of 0.6 mm diameter and the third type which was plain without any characterization. The specimens were then checked for bond strength by subjecting them to $180^{\circ}$ peel test on a universal testing machine. The obtained results were then subjected to statistical analysis using 2-way ANOVA and Scheff$\acute{e}$ multiple post hoc procedures. The statistical significance was set at 5% level of significance. RESULTS. The maximum bond strength was seen for samples in which A-330G primer was used followed by G611 primer. The control group showed the minimum bond strength. Surface characterization of retentive holes increased the bond strength considerably as compared to retentive beads and samples without any surface characterization. CONCLUSION. Within the limitations of the study, A-330G primer was more compatible with Cosmesil M511 silicone and has better bonding of Cosmesil to acrylic resin. Retentive holes made on acrylic surface increased the bond strength considerably than those without any surface characterization.

• Annual Conference of KIPS
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• 2022.11a
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

• Advances in nano research
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• v.15 no.5
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• pp.451-466
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• 2023

Gastrointestinal cancer (GC) is a prevalent malignant tumor of the digestive system that poses a severe health risk to humans. Due to the specific organ structure of the gastrointestinal system, both endoscopic and MRI diagnoses of GIC have limited sensitivity. The primary factors influencing curative efficacy in GIC patients are drug inefficacy and high recurrence rates in surgical and pharmacological therapy. Due to its unique optical features, good biocompatibility, surface effects, and small size effects, nanotechnology is a developing and advanced area of study for the detection and treatment of cancer. Because of its deep location and complex surgery, diagnosing and treating gastrointestinal cancer is very difficult. The early diagnosis and urgent treatment of gastrointestinal illness are enabled by nanotechnology. As diagnostic and therapeutic tools, nanoparticles directly target tumor cells, allowing their detection and removal. XGBoost was used as a classification method known for achieving numerous winning solutions in data analysis competitions, to capture nonlinear relations among many input variables and outcomes using the boosting approach to machine learning. The research sample included 300 GC patients, comprising 190 males (72.2% of the sample) and 110 women (27.8%). Using convolutional neural networks (CNN) and artificial neural networks (ANN)-EXtreme Gradient Boosting (XGBoost), the patients mean± SD age was 50.42 ± 13.06. High-risk behaviors (P = 0.070), age at diagnosis (P = 0.037), distant metastasis (P = 0.004), and tumor stage (P = 0.015) were shown to have a statistically significant link with GC patient survival. AUC was 0.92, sensitivity was 81.5%, specificity was 90.5%, and accuracy was 84.7 when analyzing stomach picture.