• Journal of Dental Rehabilitation and Applied Science
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• v.35 no.1
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• pp.20-26
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• 2019

Purpose: Recently TF-adaptive movement is developed in order to increase the durability of TF files. The purpose of this study was to assess the effects of adaptive movement on durability and performance of twisted files. Materials and Methods: Resin blocks simulating artificial J-shape canals were used for this study. In TFC group, TF-adaptive ML-1 (25/.08 size) files were used to prepare the canals under continuous rotation 500 rpm/4.0 Ncm. In TFA group, TF-adaptive ML-1 (25/.08 size) files were used to prepare the canals under adaptive movement. After preparing each artificial canal, TF files were observed under dental microscope for assessing existence of unwinding, distortion, and fracture. If unwinding of flute was observed, the number of artificial canals until unwinding of flute occurs was recorded. Required time until instruments reach working length and distance of unwinded portion of files from D0 were measured. All test results were conducted by Mann-Whitney U test at a 0.05 level of significance. Results: No Ni-Ti instrument's separation was observed. Number of resin blocks until file unwinding happens and working time was significantly high in TFA group compared to TF group. Distance of distortion from D0 didn't show significant difference between TFA, TF groups. Conclusion: The number of resin blocks prepared until unwinding happens and working time were significantly high in TFA group. The location of unwinding showed no significant difference between 2 groups. Adaptive movement increased the number of canals prepared until unwinding occurs and working time of twisted files.

• Restorative Dentistry and Endodontics
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• v.45 no.2
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• pp.22.1-22.10
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• 2020

Objectives: This study investigated the influence of glide path size and operating kinetics on the time to reach the working length and the fracture resistance of Twisted File (TF) and Endostar E3 files. Materials and Methods: A total of 120 mandibular single-rooted premolars were selected. Two methods of kinetic motion (TF adaptive and continuous rotary motion) and file systems (TF and Endostar E3) were employed. The files were used in root canals prepared to apical glide path sizes of 15, 20, and 25. The time taken to reach the working length and the number of canals used before the instrument deformed or fractured were noted. Fractured instruments were examined with scanning electron microscopy. Results: The TF system took significantly more time to reach the working length than the Endostar E3 system. Both systems required significantly more time to reach the working length at the size 15 glide path than at sizes 20 and 25. A greater number of TFs than Endostar E3 files exhibited deformation, and a higher incidence of instrument deformation was observed in adaptive than in continuous rotary motion; more deformation was also observed with the size 15 glide path. One TF was fractured while undergoing adaptive motion. Conclusions: No significant difference was observed between continuous rotary and adaptive motion. The TF system and adaptive motion were associated with a higher incidence of deformation and fracture. Apical glide path sizes of 20 and 25 required significantly less time to reach the working length than size 15.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.37-46
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• 2023

This study aims to evaluate the usefulness of Deep Learning Image Reconstruction (TrueFidelity, TF), the image quality of existing Filtered Back Projection (FBP) and Adaptive Statistical Iterative Reconstruction-Veo (ASIR-V) were compared. Noise, CNR, and SSIM were measured by obtaining images with doses fixed at 17.29 mGy and altered to 10.37 mGy, 12.10 mGy, 13.83 mGy, and 15.56 mGy in reconstruction techniques of FBP, ASIR-V 50%, and TF-H. TF-H has superior image quality compared to FBP and ASIR-V when the reconstruction technique change is given at 17.29 mGy. When dose changes were made, Noise, CNR, and SSIM were significantly different when comparing 10.37 mGy TF-H and FBP (p<0.05), and no significant difference when comparing 10.37 mGy TF-H and ASIR-V 50% (p>0.05). TF-H has a dose-reduction effect of 30%, as the highest dose of 15.56 mGy ASIR-V has the same image quality as the lowest dose of 10.37 mGy TF-H. Thus, Deep Learning Reconstruction techniques (TF) were able to reduce dose compared to Iterative Reconstruction techniques (ASIR-V) and Filtered Back Projection (FBP). Therefore, it is considered to reduce the exposure dose of patients.

• Restorative Dentistry and Endodontics
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• v.42 no.3
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• pp.224-231
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• 2017

Objectives: To determine the actual revolutions per minute (rpm) values and compare the cyclic fatigue life of Reciproc (RPC, VDW GmbH), WaveOne (WO, Dentsply Maillefer), and TF Adaptive (TFA, Axis/SybronEndo) nickel-titanium (NiTi) file systems using high-speed camera. Materials and Methods: Twenty RPC R25 (25/0.08), 20 WO Primary (25/0.08), and 20 TFA ML 1 (25/0.08) files were employed in the present study. The cyclic fatigue tests were performed using a dynamic cyclic fatigue testing device, which has an artificial stainless steel canal with a $60^{\circ}$ angle of curvature and a 5-mm radius of curvature. The files were divided into 3 groups (group 1, RPC R25 [RPC]; group 2, WO Primary [WO]; group 3, TF Adaptive ML 1 [TFA]). All the instruments were rotated until fracture during the cyclic fatigue test and slow-motion videos were captured using high-speed camera. The number of cycles to failure (NCF) was calculated. The data were analyzed statistically using one-way analysis of variance (ANOVA, p < 0.05). Results: The slow-motion videos were indicated that rpm values of the RPC, WO, and TFA groups were 180, 210, and 425, respectively. RPC ($3,464.45{\pm}487.58$) and WO ($3,257.63{\pm}556.39$) groups had significantly longer cyclic fatigue life compared with TFA ($1,634.46{\pm}300.03$) group (p < 0.05). There was no significant difference in the mean length of the fractured fragments. Conclusions: Within the limitation of the present study, RPC and WO NiTi files showed significantly longer cyclic fatigue life than TFA NiTi file.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.297-303
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• 2023

Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

• Journal of Radiation Protection and Research
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• v.28 no.2
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• pp.117-125
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• 2003

It was reported that radiopharamaceuticals induced radiation adaptive response (RAR) in patients undergoing nuclear medicine imaging studies. Individual variations of RAR were not studied well. The purpose of this study was to evaluate individual variation of RAR in patients undergoing nuclear medicine imaging studies. Peripheral lymphocytes were collected from 23 patients undergoing $^{99m}Tc-diethylenetriamine$ pentaacetic acid $(^{99m}Tc-DTPA)$ renal scintigraphy, 18 patients undergoing $^{99m}Tc-methylene$ diphosphonate $(^{99m}Tc-MDP)$ bone scintigraphy and 21 patients undergoing $^{99m}Tc-tetrofosmin\;(^{99m}Tc-TF)$ scintigraphy were collected before and 4 hours after injection of radiopharmaceuticals. The lymphocytes were exposed to challenge dose of 2 Gy gamma rays using a cell irradiator. Numbers of ring-form (R) and dicentric (D) chromosomes were counted under the light microscope. and used to calculate the frequency of chromosomal aberration [Ydr=(D+R)/total number of counted lymphocytes]. Adaptation index (k) was defined 3s ratio of Ydr in conditioned lymphocytes over Ydr in unconditioned lymphocytes. Coefficients of variance of k in $^{99m}Tc-DTPA,\;^{99m}Tc-MDP\;and\;^{99m}Tc-TF$ were 35%, 34% and 21%, respectively k was not dependent upon age, sex, and underlying diseases. There was a wide variation of RAR induced by radiopharmaceuticals among patients undergoing nuclear medicine procedures. It remains to be determined for causes of such variation.

• Journal of Plant Biotechnology
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• v.44 no.2
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• pp.142-148
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• 2017

Drought stress is one of the important factors that restrict the expansion of Hevea brasiliensis cultivation to non-traditional regions experiencing extreme weather conditions. Plants respond to drought stress by triggering expression of several drought responsive genes including transcription factors which in turn trigger expression of various downstream signalling pathways and adaptive networks. Expression of such drought responsive genes may revert back to their original level upon re-watering. However, no reports are available on such phenomenon in Hevea and hence, this study was initiated. For this purpose, NAC transcription factor (NAC tf) was chosen as candidate gene. Its expression levels were monitored under intermittent drought as well as irrigated conditions in two clones (RRII 105 and RRIM 600) of H. brasiliensis with contrasting tolerance level. Copy number of NAC tf was found similar in both the clones. Expression of NAC tf was found highly up-regulated in RRIM 600 (a relatively drought tolerant clone) than in RRII 105 (a relatively drought susceptible clone) throughout the drought incidences which upon re-watering, reached back to its original levels in both the clones. The study indicated the existence of an association between expression of NAC tf and drought tolerance trait exhibited by the tolerant clone RRIM 600. The study also proves the influence of drought and re-watering on the leaf photosynthesis and expression of NAC tf in H. brasiliensis.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.285-295
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• 2023

With the development of technology, efforts to reduce the exposure dose received by patients in CT scans are continuing with the development of new reconstruction techniques. Recently, deep learning reconstruction techniques have been developed to overcome the limitations of repetitive reconstruction techniques. This study aims to evaluate the usefulness of images according to reconstruction techniques in pediatric chest CT images. Patient study conducted a study on 85 pediatric patients who underwent chest CT scan at P-Hospital in Gyeongsangnam-do from January 1, 2021 to December 31, 2022. The phantom used in the Phantom Study is the Pediatrics Whole Body Phantom PBU-70. After the test, the images were reconstructed with FBP, ASIR-V (50%) and DLIR (TF-Medium, High), and the images were evaluated by obtaining SNR and CNR values by setting ROI of the same size. As a result, TF-H of deep learning reconstruction techniques had the lowest noise value compared to ASIR-V (50%) and TF-M in all experiments, and SNR and CNR had the highest values. In pediatric chest CT scans, TF images with deep learning reconstruction techniques were less noisy than ASiR-V images with adaptive statistical iterative reconstruction techniques, CNR and SNR were higher, and the quality of images was improved compared to conventional reconstruction techniques.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.692-698
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• 1999

In this paper, we proposed the channel assignment scheme for the CDMA(Code Division Multiple Access) cellular system using power allocation concept. Also, the performance of the proposed scheme was analyzed and it was compared with the channel assignment scheme using the fixed power allocation method in the CDMA cellular system. The proposed scheme allocates the power adaptively in according to the traffic loads and the traffic distribution pattern of neighbor cells in the forward link. We found that total call blocking probability (Pr) is more dependent on blocking probability($P_B$) than outage probability (Po) under physical number of channels ($C_{th}$)=30. Pr(Call Blocking Probability) is dependent on $P_B$(Blocking Probability) and Po(Outage Probability) at the same ratio under $C_{th}$=32, in which case P$P_{TA}$(blocking probability for the adaptive power allocation) is greater than $P_{TF}$(blocking probability for the fixed power allocation) about 6%.

• Computers and Concrete
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• v.21 no.6
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• pp.649-659
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• 2018

Adaptive neuro-fuzzy inference systems (ANFIS) can be efficient in modelling non-linear, complex and ambiguous behavior of cement-based materials undergoing combined damage factors of different forms (physical and chemical). The current work investigates the use of ANFIS to model the behavior (time of failure (TF)) of a wide range of concrete mixtures made with different types of cement (ordinary and portland limestone cement (PLC)) without or with supplementary cementitious materials (SCMs: fly ash and nanosilica) under various exposure regimes with the most widely used chloride-based de-icing salts (individual and combined). The results show that predictions of the ANFIS model were rational and accurate, with marginal errors not exceeding 3%. In addition, sensitivity analyses of physical penetrability (magnitude of intruding chloride) of concrete, amount of aluminate and interground limestone in cement and content of portlandite in the binder showed that the predictive trends of the model had good agreement with experimental results. Thus, this model may be reliably used to project the deterioration of customized concrete mixtures exposed to such aggressive conditions.