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This study aimed to analyze the preoperative factors of immature first molars treated with vital pulp therapy and to find out their correlation in pediatric patients. From May 2014 to January 2020, 523 patients and 1,242 immature first molars were investigated. Factors including age, sex, tooth location, Molar-incisor hypomineralization (MIH), caries cavity location, and history of previous restoration were evaluated. As a result of the study, the vital pulp therapy group had 5.56 times more MIH, 3.39 times more mesial cavities, and 8.73 times more distal cavities. In order to avoid vital pulp therapy in immature first molar, early diagnosis and active management of MIH and preventive treatment of mesial and distal caries are necessary after its immediate eruption.

The purpose of this study was to investigate the prevalence and characteristics of pre-eruptive intracoronal radiolucencies (PEIR) from panoramic radiographs in Korean children and adolescents.This study examined panoramic radiographs of 3,000 patients aged between 5 and 14 years old who visited ten dental hospitals in Korea. The age and gender of the patients, the tooth type, the number of intracoronal radiolucent lesions, and the location and size of the lesions were recorded.The overall prevalence of patients with PEIR was 2.5%. The difference in the presence of PEIR between both genders was not significant. Within each tooth type, the mandibular first molar showed highest prevalence of PEIR (29.6%). The central part of the crown was the most frequently observed location of PEIR (56.8%). The size of the PEIR lesions was mostly limited to less than one-third of the thickness of coronal dentin.

Hepatocellular adenoma is a benign tumor of the liver occurring predominantly in young women taking oral contraceptives. The malignant transformation of hepatocellular adenoma into hepatocellular carcinoma has rarely been reported. Herein, we report the case of an elderly male patient with hepatocellular carcinoma that developed from hepatocellular adenoma. The patient’s high risk for surgery and conflicting biopsy and imaging results made it difficult to determine the treatment direction. Eventually, the mass was completely removed by laparoscopic left hemi-hepatectomy without complications. (J Liver Cancer 2021;21:87-91)

This study was performed to evaluate the restoration combined with resin infiltration (RI) of early cavitated smooth surface caries lesion in terms of microleakage. Flowable resin and resin-modified glass ionomer cement (RMGIC) were compared.Sound 20 extracted 3rd molars were divided into 2 groups randomly. Artificial decalcified lesion was induced. Cavities were prepared on the mesial and distal surfaces, and randomly set as experimental and control group. RI was applied to the experimental group before cavity restoration. The control group was restored without RI. In group I and II, flowable resin and RMGIC was used for restoration respectively. After thermocycling and silver nitrate immersion, microleakage was assessed by μ-CT.Depth of microleakage was lower in experimental group than control group only in group II (p = 0.05). Microleakage depth was lower in group II than group I in both experimental and control groups (p = 0.05).RI pretreatment before restoration of early cavitated caries lesions might reduce the microleakage and help long-term maintenance of restoration. In this study, RMGIC was less polymerization shrinkage. Restoration with RMGIC after RI pretreatment reduced the microleakage of the restoration compared to the flowable resin.

We aimed to compare the operative outcomes of laparoscopic right posterior sectionectomy (RPS) and open RPS and evaluate the feasibility of laparoscopic RPS.From January 2009 to December 2017, laparoscopic liver resections were performed in 235 patients at Chonnam National University Hwasun Hospital, South Korea. We retrospectively analyzed the clinical data of 16 patients who underwent laparoscopic RPS and compared the outcomes with those who underwent open RPS (n=17).The laparoscopic group had a mean tumor size of 3.82±1.73 cm (open group [OG]; 4.18±2.07 cm,Laparoscopic RPS can be performed, but the problems of long operative time and decrease in liver function should be resolved.

Overuse of the nonparetic upper extremity can lead to entrapment neuropathies in chronic stroke patients. However, little is known about the effects of cane use in subacute stage of stroke. The aim of this study was to investigate the short-term effects of cane use on the upper extremity nerves in subacute stroke patients recovering from a bedridden state. Thirty subacute hemiparetic stroke patients who were initially bedridden participated when they were able to walk with a cane. Symptoms and signs related to the median or ulnar nerves were checked, and nerve conduction studies were performed. The largest cross-sectional area (CSA) of these nerves from the wrist to elbow was measured with ultrasound. After 3 weeks of cane use, electrophysiologic and ultrasonographic reevaluation was performed. Nerve conduction studies and CSA of the nerves at the nonparetic upper extremity showed significant changes, whereas those of the hemiparetic upper extremity did not. Walking with a cane for a short period can induce the enlargement of the median and ulnar nerves at the nonparetic extremity of subacute hemiparetic stroke patients. Attention should be placed on correct cane usage from the beginning of rehabilitation.

Background Repetitive transcranial magnetic stimulation (rTMS) is one of the effective treatments for neuropathic pain. Little is known about the effects of multi-session theta burst stimulation, one of the new paradigms of rTMS. Objective The aim of this study was to investigate the effects of multi-session intermittent theta burst stimulation (iTBS) on central neuropathic pain, using evaluation tools specific to neuropathic pain. Methods Patients with central neuropathic pain diagnosed using Neuropathic Pain Special Interest Group guidelines were recruited. Thirty patients were randomly assigned to either a real or sham iTBS group. Each patient underwent 5 sessions of iTBS; before and after completion of the 5 sessions, participants were evaluated using the self-completed Leeds assessment of neuropathic symptoms and signs (S-LANSS), the numeric rating scale (NRS), the neuropathic pain symptom inventory (NPSI), and the neuropathic pain scale (NPS). Results S-LANSS, NRS, NPSI, and 3 of 4 NPS combination scores decreased significantly in the real iTBS group but not in the sham iTBS group. No adverse effects were reported during or after iTBS sessions. Conclusions Multi-session iTBS was associated with a significant decrease in neuropathic pain, indicating its effectiveness as a treatment for patients with central neuropathic pain.

IT technology and traditional industries have been combined recently, resulting in IT convergence technology in various fields. Through convergence with the automobile, pedestrian detection technology, in particular, is used in the autonomous navigation control service of autonomous vehicles and also applied in various fields such as intelligent CCTV and robot recognition technology. For pedestrian detection, hierarchical classification and feature vector were used in early stage, and deep learning is under active progress. However, since deep learning for pedestrian detection is time-consuming for processing a large volume of image data, it requires a lot of computing resources, and hence building such a system is very expensive. Therefore, in this paper we shall present a distributed deep learning platform which can easily build a cluster, and execute deep learning process in the distributed cloud environment, while achieving performance improvement in various ways. Our platform provides a convenient interface for easily and efficiently executing the deep learning process in a distributed environment by providing a multilayered system architecture. Our system builds and utilizes computing power in easy and efficient way by leveraging container technique, so-called OS-level virtualization, rather than traditional hypervisor-based virtualization. In our system, we improve the whole performance by exploiting both of data and parameter parallelisms at once and reduce the synchronization overhead by exploiting asynchronous communication for parameter updates. Also, we propose an efficient resource allocation scheme for parameter servers and slaves which can improve the performance from the experiment.

In this study, we aimed to develop and evaluate the performance of deep-learning models that automatically classify mesiodens in primary or mixed dentition panoramic radiographs. Panoramic radiographs of 550 patients with mesiodens and 550 patients without mesiodens were used. Primary or mixed dentition patients were included. SqueezeNet, ResNet-18, ResNet-101, and Inception-ResNet-V2 were each used to create deep-learning models. The accuracy, precision, recall, and F1 score of ResNet-101 and Inception-ResNet-V2 were higher than 90%. SqueezeNet exhibited relatively inferior results. In addition, we attempted to visualize the models using a class activation map. In images with mesiodens, the deep-learning models focused on the actual locations of the mesiodens in many cases. Deep-learning technologies may help clinicians with insufficient clinical experience in more accurate and faster diagnosis.

The purpose of this study is to evaluate and compare the performance of six state-of-the-art convolutional neural network (CNN)-based deep learning models for cervical vertebral maturation (CVM) on lateral cephalometric radiographs, and implement visualization of CVM classification for each model using gradient-weighted class activation map (Grad-CAM) technology. A total of 600 lateral cephalometric radiographs obtained from patients aged 6–19 years between 2013 and 2020 in Pusan National University Dental Hospital were used in this study. ResNet-18, MobileNet-v2, ResNet-50, ResNet-101, Inception-v3, and Inception-ResNet-v2 were tested to determine the optimal pre-trained network architecture. Multi-class classification metrics, accuracy, recall, precision, F1-score, and area under the curve (AUC) values from the receiver operating characteristic (ROC) curve were used to evaluate the performance of the models. All deep learning models demonstrated more than 90% accuracy, with Inception-ResNet-v2 performing the best, relatively. In addition, visualizing each deep learning model using Grad-CAM led to a primary focus on the cervical vertebrae and surrounding structures. The use of these deep learning models in clinical practice will facilitate dental practitioners in making accurate diagnoses and treatment plans.

The use of kidneys from donation after brain death (DBD) donors with acute kidney injury (AKI) is a strategy to expand the donor pool. The aim of this study was to evaluate how kidney transplantation (KT) from a donor with AKI affects long-term graft survival in various situations. All patients who underwent KT from DBD donors between June 2003 and April 2016 were retrospectively reviewed. The KDIGO (Kidney Disease: Improving Global Outcomes) criteria were used to classify donor AKI. The cohort included 376 donors (no AKI group, n = 117 [31.1%]; AKI group n = 259 [68.9%]). Death-censored graft survival was similar according to the presence of AKI, AKI severity, and the AKI trend (p = 0.929, p = 0.077, and p = 0.658, respectively). Patients whose donors had AKI who received using low dose (1.5 mg/kg for three days) rabbit anti-thymocyte globulin (r-ATG) as the induction agent had significantly superior death-censored graft survival compared with patients in that group who received basiliximab (p = 0.039). AKI in DBD donors did not affect long-term death-censored graft survival. Low-dose r-ATG may be considered as an induction immunosuppression in recipients receiving kidneys with AKI because it showed better graft survival than basiliximab.

Recently, with the development of technology, computer vision research based on the human visual system has been actively conducted. Saliency maps have been used to highlight areas that are visually interesting within the image, but they can suffer from low performance due to external factors, such as an indistinct background or light source. In this study, existing color, brightness, and contrast feature maps are subjected to multiple shape and orientation filters and then connected to a fully connected layer to determine pixel intensities within the image based on location-based weights. The proposed method demonstrates better performance in separating the background from the area of interest in terms of color and brightness in the presence of external elements and noise. Location-based weight normalization is also effective in removing pixels with high intensity that are outside of the image or in non-interest regions. Our proposed method also demonstrates that multi-filter normalization can be processed faster using parallel processing.

Recently, various character recognition techniques are advanced and used a lot in real situations. In the real complex situation, it is difficult to recognize characters because of Korean, English of various fonts and background noise. In this paper, we shall present character bounding box module, character recognition module and background elimination module to solve problems. We shall show that the character recognition platform is used in complex situations.

Eruption disturbances in permanent mandibular first molars (PM1s) are uncommon. This retrospective study aimed to investigate differences in the position of the mandibular canal in relation to PM1s, with or without, eruption disturbances. Panoramic and cross-sectional views were reconstructed from cone-beam computed tomography imaging of children with PM1 eruption disturbances. Distances from the most inferior margin of the mandible to the center of the mandibular canal (M&ndash, C) and from the outer margin of the lingual cortex to the center of the mandibular canal (L&ndash, C) were measured for normally erupted PM1s (normal group) and for PM1s with eruption disturbances (ED group) and compared using independent t-tests. The mean M&ndash, C was significantly shorter in the ED group (4.86 &plusmn, 1.07 mm) than in the normal group (6.56 &plusmn, 1.06 mm) (p &lt, 0.05). The mean L&ndash, C was also significantly shorter in the ED group (2.74 &plusmn, 0.74 mm) than in the normal group (3.09 &plusmn, 0.71 mm) (p &lt, 0.05). This study demonstrated that the mandibular canal tended to be positioned more inferiorly in relation to PM1s with eruption disturbances than normally erupted PM1s in children. Clinicians should be aware of this positional deviation when managing children with PM1 eruption disturbances.

이 연구의 목적은 고등학교를 졸업한지 10년 이내의 성인을 대상으로 구강보건교육 경험과 인식을 조사하여 소아와 청소년의 구강보건교육을 제고할 방안을 찾기 위함이다. 412명의 성인에게 설문지를 배포 후 회수된 설문지 중 기준에 부합하는 388명을 선정하였다. 설문 내용은 학령기 구강보건교육 경험과 인식, 구강건...

In this paper, an inductor-type superconducting fault current limiter (I-SC FCL) in the dc power system is proposed to combine the benefits of an inductor and a superconductor. I-SC FCL minimizes the power burden on a superconductor and maximizes the cutoff performance. The inductor delays the rise of the fault current, and the superconductor limits the maximum value of the fault current. Then, they serve together to protect the circuit before the circuit breaker comes into play. The fault currents, limited by an inductor and a superconductor, are introduced into the mechanical dc circuit breaker (M-DCCB). M-DCCB could perform stably due to low power consumption. Analysis of the cutoff characteristics is carried out using the EMTDC/PSCAD program. As a result, the maximum value of the fault current is limited to approximately 2.6 times lower than the previously proposed M-DCCB. Additionally, a low power is burdened on I-SC FCL due to the delay part.

Transformer-type superconducting fault current limiter (TSFCL) interruption system is a current breaking technology proposed by applying a transformer, superconductor, and mechanical dc circuit breaker. When the fault occurs, the fault current is limited due to the operation of the counter electromotive force by the transformer and the quenching of the superconductor. The fault current is then interrupted by the mechanical dc circuit breaker. In this paper, the transition and the interrupting behavior was analyzed according to the applied voltage to secure the stability and reliability of a TSFCL interruption system using the PSCAD EMTDC program. As a result, it was able to improve the current breaking time and the breaking capacity. Also, the burden imposed on a mechanical dc circuit breaker was reduced fivefold.

In this study, superconducting coil-type dc fault current limiter (SC-DC FCL) was proposed. The interruption and operation characteristics of the SC-DC FCL were analyzed, which was applied to a 7.98 kW-class photovoltaic (PV) generation system. Electro magnetic transients including direct current/power system computer aided design (EMTDC/PSCAD) have been used for the simulation. The simulation results showed that the interruption operation time of the mechanical circuit breaker, the power burden applied to the circuit breaker, and the peak value of the fault current were significantly reduced by the application of the SC-DC FCL. In addition, when the SC-DC FCL was applied, the fault current flowing through the line was limited by approximately 78% or more.

With the recent success of deep learning, the amount of data and computation continues to grow daily. Hence a distributed deep learning system that shares the training workload has been researched extensively. Although a scale-out distributed environment using commodity servers is widely used, not only is there a limit due to synchronous operation and communication traffic but also combining deep neural network (DNN) training with existing clusters often demands additional hardware and migration between different cluster frameworks or libraries, which is highly inefficient. Therefore, we propose TensorLightning which integrates the widely used data pipeline of Apache Spark with powerful deep learning libraries, Caffe and TensorFlow. TensorLightning embraces a brand-new parameter aggregation algorithm and parallel asynchronous parameter managing schemes to relieve communication discrepancies and overhead. We redesign the elastic averaging stochastic gradient descent algorithm with pruned and sparse form parameters. Our approach provides the fast and flexible DNN training with high accessibility. We evaluated our proposed framework with convolutional neural network and recurrent neural network models; the framework reduces network traffic by 67% with faster convergence.

The global consumption of electricity is on the rise due to the industrial and population growth. The number of power generation and distribution facilities is increasing in order to meet the growing demand. Furthermore, the low impedance of power systems is causing a fault current that exceeds the capacity of the existing circuit breaker. In this paper, a method was suggested which limits the initial fault current by combining a superconducting fault current limiter (SFCL) with the existing flux-offset-type fault current limiter (FCL). Results showed that the initial fault current within a half cycle was limited by approximately 60%, while the fault current after a half cycle was limited by approximately 80 %. Overall, 99.8% of the fault current was limited, while the power burden on the SFCL was reduced by more than 50%.

As technology advances, the amount of fake news is increasing more and more by various reasons such as political issues and advertisement exaggeration. However, there have been very few research works on fake news detection, especially which uses grammatical transformation on deep neural network. In this paper, we shall present a new Fake News Detection Model, called FAGON(Fake news detection model using Grammatical transformation On deep Neural network) which determines efficiently if the proposition is true or not for the given article by learning grammatical transformation on neural network. Especially, our model focuses the Korean language. It consists of two modules: sentence generator and classification. The former generates multiple sentences which have the same meaning as the proposition, but with different grammar by training the grammatical transformation. The latter classifies the proposition as true or false by training with vectors generated from each sentence of the article and the multiple sentences obtained from the former model respectively. We shall show that our model is designed to detect fake news effectively by exploiting various grammatical transformation and proper classification structure.

Recently, fake news has been incurring many problems to our society. As a result, many researchers have been working on identifying fake news. Most of the fake news detection systems utilize the linguistic feature of the news. However, they have difficulty in sensing highly ambiguous fake news which can be detected only after identifying meaning and latest related information. In this paper, to resolve this problem, we shall present a new Korean fake news detection system using fact DB which is built and updated by human's direct judgement after collecting obvious facts. Our system receives a proposition, and search the semantically related articles from Fact DB in order to verify whether the given proposition is true or not by comparing the proposition with the related articles in fact DB. To achieve this, we utilize a deep learning model, Bidirectional Multi-Perspective Matching for Natural Language Sentence(BiMPM), which has demonstrated a good performance for the sentence matching task. However, BiMPM has some limitations in that the longer the length of the input sentence is, the lower its performance is, and it has difficulty in making an accurate judgement when an unlearned word or relation between words appear. In order to overcome the limitations, we shall propose a new matching technique which exploits article abstraction as well as entity matching set in addition to BiMPM. In our experiment, we shall show that our system improves the whole performance for fake news detection.

This Recently, a lot of information is spreading rapidly on SNS. Inaccurate communication of news media includes fears about unreliable sources and fake news that lacks confirmation of facts. Fake news is spread through SNS, causing social confusion and further economic loss. The purpose of the news is accurate information transmission. In this regard, it is very important to judge the discrepancies in the contents of the text and the distorted reports. We try to solve the problem of judging whether the sentence to be verified is correct after collecting the facts. This paper defines the problem of extracting the related sentences from the input sentence in Fact Data Corpus which is assumed to be fact and judging whether the extracted sentence and the input sentence are true or false. In the various NLP tasks, we create a Korean-specific pre-training model using state-of-the-art BERT. Using this model, fine-tuning is performed to match the data set detected by Korean fake news. The AUROC score of 83.8% is derived from the test set generated using the fine-tuned model.

Background: Tacrolimus (TAC) is a main therapy for liver transplantation (LT) patients, but it has side effects such as chronic nephrotoxicity that progressively aggravate renal function. The purpose of this study was to retrospectively compare the renal function be tween a TAC group and a combination of everolimus and reduced TAC (EVR-TAC) group after deceased donor liver transplantation (DDLT). Methods: The study comprised 131 patients who underwent DDLT between January 2013 and April 2018 at our institution. They received TAC or EVR-TAC after DDLT. Everoli mus (EVR) was introduced between 1 and 6 months after DDLT. Results: Thirty-six of 131 patients (27.5%) received EVR-TAC. The incidence of chronic kidney disease (CKD; estimated glomerular filtration rate

Introduction As the general population continues to age, elderly patients have dramatically increased for detecting hepatocellular carcinoma (HCC) and required for surgical management. The aim of this study was to compare the postoperative and long-term outcomes of hepatectomy those patients according to the operation time. Methods This study included 130 elderly patients who underwent surgical resection for solitary, treatment-naive HCC between November 1998 and March 2020. Group 1 was defined as patients undergoing LR before 2016 (n = 68) and Group 2 was defined as those undergoing liver resection (LR) after 2016 (n = 62). Results The proportion of major LR and laparoscopic LR in the Group 2 were significantly higher than in the Group 1. Median operation time and blood loss during operation in the Group 2 were smaller than in the Group 1. In addition, intraoperative red blood cell (RBC) transfusion rate, complication rates, and median hospitalization in Group 2 were significantly lower than Group 1. The disease-free survival and patient survival in the Group 2 were better than in the Group 1 even though the presence of tumor grade 3 or 4 and the incidence of microvascular invasion in the Group 1 were higher than in the Group 2. Group 1, long hospitalization, presence of satellite nodule, and intraoperative RBC transfusion were predisposing factors for patient death. Conclusions Laparoscopic LR in elderly HCC patients, was performed more frequently than in the past, resulting in an increase in the number of liver surgeries and improved survival.

Introduction Surgical resection is one of the curative options for hepatocellular carcinoma (HCC). Posterosuperior segmentectomy is defined as anatomical resection of the liver segments 7 and 8. However, minimally invasive resection of posterosuperior liver segments is considered a difficult and complex operation and is therefore rarely reported. Methods We present a video of laparoscopic posterosuperior segmentectomy of the liver (S7, 8) due to HCC, in a 66-years old male patient. Liver mobilization was performed with exposure of the inferior vena cava. Intraoperative ultrasound was used to locate the tumor and identify its relationship with the portal veins of segments 7 and 8. The liver parenchyma was divided using ultrasonic energy device and the Glissonean pedicles were ligated using hem-o-lock and surgical clips. The surgical specimen was removed through a lower midline incision. Results Operative time was 162 minutes, and the estimated blood loss was 400 mL. The patient recovered without problems such as admission to the intensive care unit or blood transfusion. Pathology confirmed progressed HCC. Conclusions Laparoscopic posterosuperior segmentectomy is difficult, but is feasible and safe. This video can help inexperienced surgeons perform this complex procedure.

Introduction Inadequate liver volume and weight is a major source of morbidity and mortality after adult living donor liver transplantation (LDLT). The purpose of our study was to investigate HCC recurrence, graft failure, and patient survival according to change in right liver graft weight after histidine-tryptophan-ketoglutarate (HTK) solution perfusion in LDLT. Methods Two hundred twenty-eight patients underwent LDLT between 2013 and 2017. We calculated the change in graft weight by subtracting pre-perfusion graft weight from post-perfusion graft weight. Patients with increased graft weight were defined as the positive group, and patients with decreased graft weight were defined as the negative group. Results After excluding patients who did not meet study criteria, 148 patients underwent right or extended right hepatectomy. The negative group included 89 patients (60.1%), and the positive group included 59 patients (39.9%). Median graft weight change was -28 g (range, -132-0 g) in the negative group and 21 g (range, 1-63 g) in the positive group (p < 0.001). Median hospitalization time was longer for the positive group than the negative group (27 days vs. 23 days; p = 0.048). There were no statistical differences in tumor characteristics, postoperative complications, early allograft dysfunction, or acute rejection between the two groups. Disease-free survival, death-censored graft survival, and patient survival were lower in the positive group than the negative group. Additionally, the positive group showed strong association with HCC recurrence, death-censored graft survival, and patient survival in multivariate analysis. Conclusions This study suggests that positive graft weight change during HTK solution perfusion indicates poor prognosis in LDLT.

Introduction Several treatments have recently been known for hepatocellcular carcinoma (HCC) who have failed to treat sorafenib. Immune checkpoint inhibitors have proven to be effective, but data on the safety and efficacy of liver transplant (LT) patients are limited. We aimed to report the effect of nivolumab after failure of sorafenib treatment in patients with recurrent HCC after liver transplantation. Methods This study retrospectively evaluated patients who failed sorafenib for recurrent HCC treatment after liver transplantation in a single center from March 2007 to December 2018. Patients with recurrent hepatocellular carcinoma after liver transplantation who received regorafenib or nivolumab after sorafenib treatment failure were included. Results Of the 53 study patients, 8 received regorafenib and 10 received nivolumab. There is no difference in the characteristics of the two groups. Median overall survival (OS) from LT or HCC recurrence was 58.1 months and 40.2 months in the novolumab group and was 25.6 months and 17.6 months in the non-nivolumab group (p = 0.104 and p = 0.143, respectively). The median OS from nivolumab use was 5.3 months and the median OS from sorafenib use in non-nivolumab group was 14.8 months (p = 0.657). All 10 patients receiving nivolumab failed to control HCC progression and 6 patients (60%) were dead due to HCC progression during a median follow-up period of 2.4 months (interquartile range, 1.8-7.2 months) from the onset of nivolumab. Conclusions Present study suggests that the use of nivolumab in LT patients with recurrent HCC has not shown a clear function in inhibiting HCC progression yet.

Introduction Although hepatocellular carcinoma (HCC) is rare in hepatitis C virus (HCV) patients without cirrhosis, little is known about the postoperative results of these patients. We performed this study to compare the outcomes of cirrhotic and non-cirrhotic HCV patients with solitary treatment-naive HCC and to assess ability of non-invasive markers to predict prognosis in these patients. Methods Two hundred seven adult hepatectomy patients with HCV-related HCC were prospectively identified at our institution between July 2005 and May 2019. Results One hundred sixteen (56%) hepatectomy patients had HCC in a non-cirrhotic liver. The non-cirrhotic group had better liver function than the cirrhotic group. Consistently, the FIB-4 grade, ALBI grade, and APRI were higher in the cirrhotic group than in the non-cirrhotic group. The cumulative disease-free survival rates and patient survival rates in the non-cirrhotic group were significantly better than in the cirrhotic group. HCC recurrence is related to major liver resection (LR) and alpha-fetoprotein (AFP) > 40 ng/mL, death is related to long hospitalization, and AFP > 40 in multivariate analysis. APRI was the only predisposing factor for HCC recurrence in non-cirrhotic patients in multivariate analysis. The FIB-4 grade, ALBI grade, and the presence of cirrhosis were not related to HCC recurrence or patient survival in multivariate analyses. Conclusions The non-cirrhotic group had a higher survival than the cirrhotic group after curative LR, although the difference was not significant in multivariate analysis. The factors influencing HCC recurrence and patient survival were different in the cirrhotic and non-cirrhotic groups.

The wireless power transfer (WPT) characteristics between the transmitter and receiver coils according to the existence of ferrite were analyzed in this study to improve the transmission distance of superconductor resonance coils. To set the optimal reflection coefficient, the thickness increased by 1 mm, from 0 to 10 mm. It was found that the transfer efficiency improved with the lowest reflection coefficient at the thickness of 2 mm. The 2-mm-thick ferrite was applied to the transmitter coil, and the reflection coefficient was measured by the distance. As a result, the transfer efficiency with ferrite was highest at the distance of 2500 mm. Also, it was confirmed that the WPT characteristics were improved up to 500 mm by the application of ferrite. It is believed when the superconductive WPT system is organized using such advantageous ferrite, its transmission distance and efficiency improvement can be secured.

In this study, a SFCL-combined DC circuit breaker system was proposed by applying the current-limiting technology for DC circuit breaking. The SFCL-combined circuit breaker system consists of a mechanical DC circuit breaker combined with superconductors. To ensure the reliable structure and operation of the SFCL-combined circuit breaker system, a simulation grid was designed using the EMTDC/PSCAD program, and simulation was conducted. The results showed that the SFCL-combined DC circuit breaker system with superconductors limited the maximum fault current by 37%. In addition, the burden on the DC circuit breaker was decreased by 87%.

Objectives The aim of this study was to evaluate the bond strengths of one-step self-etch adhesives applied to primary tooth dentin with and without additional acid etching. Materials and Methods In total, 154 specimens were prepared using 50 naturally exfoliated primary molars. Four commercial one-step self-etch adhesives were used in this study: Scotchbond™ Universal, All-Bond Universal™, Adper™ Prompt™ L-Pop™, and Clearfil S3 Bond™. Two etch-and-rinse adhesives, Prime & Bond® NT™ and Scotchbond™ Multi-Purpose, served as controls. Microtensile bond strength tests were performed for specimens treated with the one-step self-etch adhesives with and without additional acid etching and those treated with the two etch-and-rinse adhesives. Results All one-step self-etch adhesives except Adper Prompt L-Pop exhibited increased microtensile bond strength values (p

The magnetic resonance method requires high quality factor(Q-factor) of resonators. Superconductor coils were used in this study to increase the Q-factor of wireless power transfer(WPT) systems in the magnetic resonance method. The results showed better transfer efficiency compared to copper coils. However, as superconducting coils should be cooled below critical temperatures, they require cooling containers. In this viewpoint, shielding materials for the cooling containers were applied for the analysis of the WPT characteristics. The shielding materials were applied at both ends of the transmitter and receiver coils. Iron, aluminum, and plastic were used for shielding. The electric field distribution and S-parameters (S11, S21) of superconducting coils were compared and analyzed according to the shield materials. As a result, plastic shielding showed better transfer efficiency, while iron and aluminum had less efficiency. Also, the maximum magnetic field distribution of the coils according to the shielding materials was analyzed. It was found that plastic shielding had 5 times bigger power transfer rate than iron or aluminum. It is suggested that the reliability of superconducting WPT systems can be secured if plastic is used for the cooling containers of superconducting resonance coils.