• International journal of thyroidology
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• v.11 no.2
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• pp.189-193
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• 2018

A thyroglossal duct cyst (TGDC) is the most common congenital anomaly of the neck. However, carcinoma arising from TGDC is extremely rare. We report 2 cases of TGDC carcinoma. In the first case, a 21-year-old male patient complained of an anterior cervical mass; computed tomography (CT) and sonography revealed cystic mass that was suspected to be a TGDC. Sistrunk operation was performed. Papillary carcinoma was confirmed in pathologic examination. Additionally, he underwent total thyroidectomy and central neck dissection. After radioactive iodine ablation (RAI) was performed. In the second case, a 28-year-old male patient visited our out-patient department complaining of submental mass. He had already been diagnosed TGDC carcinoma 13 years ago and had undergone Sistrunk operation and total thyroidectomy. Malignancy was confirmed using fine-needle aspiration; thus, lateral neck dissection was performed and following this, he underwent RAI. Till date, no evidence of recurrence has been observed in these patients.

• BMB Reports
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• v.52 no.1
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• pp.47-55
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• 2019

Cellular senescence (CS) is one of hallmarks of aging and accumulation of senescent cells (SCs) with age contributes to tissue or organismal aging, as well as the pathophysiologies of diverse age-related diseases (ARDs). Genetic ablation of SCs in tissues lengthened health span and reduced the risk of age-related pathologies in a mouse model, suggesting a direct link between SCs, longevity, and ARDs. Therefore, senotherapeutics, medicines targeting SCs, might be an emerging strategy for the extension of health span, and prevention or treatment of ARDs. Senotherapeutics are classified as senolytics which kills SCs selectively; senomorphics which modulate functions and morphology of SCs to those of young cells, or delays the progression of young cells to SCs in tissues; and immune-system mediators of the clearance of SCs. Some senolytics and senomorphics have been proven to markedly prevent or treat ARDs in animal models. This review will present the current status of the development of senotherapeutics, in relation to aging itself and ARDs. Finally, future directions and opportunities for senotherapeutics use will discussed. This knowledge will provide information that can be used to develop novel senotherapeutics for health span and ARDs.

• Molecules and Cells
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• v.44 no.8
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• pp.557-568
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• 2021

Global knockout of the BK channel has been proven to affect bone formation; however, whether it directly affects osteoblast differentiation and the mechanism are elusive. In the current study, we further investigated the role of BK channels in bone development and explored whether BK channels impacted the differentiation and proliferation of osteoblasts via the canonical Wnt signaling pathway. Our findings demonstrated that knockout of Kcnma1 disrupted the osteogenesis of osteoblasts and inhibited the stabilization of β-catenin. Western blot analysis showed that the protein levels of Axin1 and USP7 increased when Kcnma1 was deficient. Together, this study confirmed that BK ablation decreased bone mass via the Wnt/β-catenin signaling pathway. Our findings also showed that USP7 might have the ability to stabilize the activity of Axin1, which would increase the degradation of β-catenin in osteoblasts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1166-1186
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• 2022

Artistic font design has become an integral part of visual media. However, without prior knowledge of the font domain, it is difficult to create distinct font styles. When the number of characters is limited, this task becomes easier (e.g., only Latin characters). However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages. Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs). Existing methods rely heavily on reference fonts and perform font style conversions between different fonts. Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image. In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content. Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information. By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style. Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods. Additionally, we conducted ablation studies to validate our proposed network architecture.

• Smart Media Journal
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• v.11 no.4
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• pp.38-45
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• 2022

Object detection models have become the current tool of choice for plant disease detection in precision agriculture. Most existing research improves the performance by ameliorating networks and optimizing the loss function. However, the data-centric part of a whole project also needs more investigation. In this paper, we proposed a systematic strategy with three different annotation methods for plant disease detection: local, semi-global, and global label. Experimental results on our paprika disease dataset show that a single class annotation with semi-global boxes may improve accuracy. In addition, we also studied the noise factor during the labeling process. An ablation study shows that annotation noise within 10% is acceptable for keeping good performance. Overall, this data-centric numerical analysis helps us to understand the significance of annotation methods, which provides practitioners a way to obtain higher performance and reduce annotation costs on plant disease detection tasks. Our work encourages researchers to pay more attention to label quality and the essential issues of labeling methods.

• Journal of Korea Multimedia Society
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• v.25 no.5
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• pp.685-694
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• 2022

The goal of few-shot semantic segmentation is to build a network that quickly adapts to novel classes with extreme data shortage regimes. Most existing few-shot segmentation methods leverage single or multiple prototypes from extracted support features. Although there have been promising results for natural images, these methods are not directly applicable to the aerial image domain. A key factor in few-shot segmentation on aerial images is to effectively exploit information that is robust against extreme changes in background and object scales. In this paper, we propose a Mask-Guided Attention module to extract more comprehensive support features for few-shot segmentation in aerial images. Taking advantage of the support ground-truth masks, the area correlated to the foreground object is highlighted and enables the support encoder to extract comprehensive support features with contextual information. To facilitate reproducible studies of the task of few-shot semantic segmentation in aerial images, we further present the few-shot segmentation benchmark iSAID-, which is constructed from a large-scale iSAID dataset. Extensive experimental results including comparisons with the state-of-the-art methods and ablation studies demonstrate the effectiveness of the proposed method.

• Transactions on Electrical and Electronic Materials
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• v.1 no.1
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• pp.32-39
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• 2000

Langmuir probe measurements of electron density, electron temperature and potential are mad in the early stage (<5${\mu}$s) of a laser ablated plasma plume, in which a positive current form positive ions and a electron current are overlapped. The plasma wes produced by focusing the second harmonic, 532 nm, of Q-switched Nd:YAG laser on a high purity carbon target. Then the laser intensity on the target of ~1.6${\times}$10$\^$15/ W/$\textrm{cm}^2$. The measured electron desities and temperatures are ~2${\times}$10/sip 11/ cm$\^$-3/ and -3 eV. In particluar , the phenomenon that the electron temperature decreased and then increased was observed,. It could be well explained that this phenomenon occurred in the process of inverse Bremsstrahlung of free electrons in plasma. Additionally, the plasma potential(>11V) was higher than the published values.

• Journal of Veterinary Science
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• v.24 no.5
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• pp.61.1-61.12
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• 2023

Background: Percutaneous renal cyst sclerotherapy (PRCS) as a treatment for renal cysts is usually performed with a high concentration of ethanol (≥ 90%). This study reviewed cases in which a lower concentration of ethanol (83%) was used for the procedure in dogs. Methods: Records of cases of renal cysts treated by sclerotherapy using 83% ethanol in dogs were reviewed. Outcomes of the treatment were evaluated by comparing volumes of renal cysts before the procedure and the volumes after treatment, using ultrasound images with the volume reduction rates classified as follows: < 50% of initial volume (failed); ≥ 50% but < 80% of initial volume (partial success); ≥ 80% but < 95% of initial volume (great success); ≥ 95% of initial volume (complete success). Results: Out of nine dog kidneys, renal cysts sclerotherapy with 83% ethanol achieved partial success in one kidney, great success in four, and complete success in the other four. No side effect was observed. The mean of the volume-reduction rates was 90.00 ± 11.00 while the minimum and maximum reduction rates were 65% and 100%, respectively. Conclusions: The lower ethanol concentration (83%) is good for disinfecting kidneys in PRCS.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.436-443
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• 2023

With the advancement of robot intelligence, the concept of man and unmanned teaming (MUM-T) has garnered considerable attention in military research. In this paper, we present a transformer-based architecture for predicting the health status of agents, with the help of multi-head attention mechanism to effectively capture the dynamic interaction between friendly and enemy forces. To this end, we first introduce a framework for generating a dataset of battlefield situations. These situations are simulated on a virtual simulator, allowing for a wide range of scenarios without any restrictions on the number of agents, their missions, or their actions. Then, we define the crucial elements for identifying the battlefield, with a specific emphasis on agents' status. The battlefield data is fed into the transformer architecture, with classification headers on top of the transformer encoding layers to categorize health status of agent. We conduct ablation tests to assess the significance of various factors in determining agents' health status in battlefield scenarios. We conduct 3-Fold corss validation and the experimental results demonstrate that our model achieves a prediction accuracy of over 98%. In addition, the performance of our model are compared with that of other models such as convolutional neural network (CNN) and multi layer perceptron (MLP), and the results establish the superiority of our model.

• ETRI Journal
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• v.45 no.5
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• pp.795-810
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• 2023

Unmanned aerial vehicles (UAV) and ground vehicles (UGV) require advanced video analytics for various tasks, such as moving object detection and segmentation; this has led to increasing demands for these methods. We propose a zero-shot video object segmentation method specifically designed for UAV and UGV applications that focuses on the discovery of moving objects in challenging scenarios. This method employs a background memory model that enables training from sparse annotations along the time axis, utilizing temporal modeling of the background to detect moving objects effectively. The proposed method addresses the limitations of the existing state-of-the-art methods for detecting salient objects within images, regardless of their movements. In particular, our method achieved mean J and F values of 82.7 and 81.2 on the DAVIS'16, respectively. We also conducted extensive ablation studies that highlighted the contributions of various input compositions and combinations of datasets used for training. In future developments, we will integrate the proposed method with additional systems, such as tracking and obstacle avoidance functionalities.