• Korean Journal of Child Education & Care
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• v.18 no.4
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• pp.213-225
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• 2018

Objective: Research on children's death concepts requires an approach considering social and cultural context. A qualitative method is necessary to explore children's cognitive process of understanding death. Thus, this study, to overcome the limitations of the quantitative approach based on the deductive logic led by adult researchers, adopted a qualitative research method. Methods: The data collection, referring to the theories of Corr and Balk (2010) and Smilansky (1987), used Death Concept Questionnaire. Each structured question was followed by open follow-up questions to explore how children understood each concept of death. Results: The results showed that participant children were still lacking in the acquisition of death sub-concepts. The qualitative result from open interview showed how children can and can not acquire the concepts of death. Conclusion/Implications: The study could be used in future development of death education programs for children. Based on the results of this research, it is necessary to develop programs for children's death education, which would help them coping with death related anxiety and loss experiences.

• Korean Journal of Plant Resources
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• v.32 no.2
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• pp.201-206
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• 2019

Alien invasive species are introduced with or without intent and spreading all over Korea. They are known to have negative effects on biodiversity such as economic and environmental damage and causing decrease or loss of native species. The habitats like wetland, reservoir and riverside are especially in danger of being invaded by alien species due to stress and disturbance. Therefore, Korea National Arboretum is steadily working on research and studies on managing alien invasive species. This research aims to collect basic information of Ludwigia peploides subsp. montevidensis (Spreng.) P.H. Raven which was found near riverside in Suwon-si and is concerned to become an invasive alien species. We expect the description, diagram and pictures of this taxon will be helpful for early detection and effective management.

• Laboraroty Animal Research
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• v.34 no.4
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• pp.176-184
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• 2018

In this study, we observed chronological changes in the immunoreactivity and expression level of myelin basic protein (MBP), one of the most abundant proteins in the central nervous system, in the hippocampus of Zucker diabetic fatty (ZDF) rats and their control littermates (Zucker lean control; ZLC). In the ZLC group, body weight steadily increased with age; the body weight of the ZDF group, however, peaked at 30 weeks of age, and subsequently decreased. Based on the changes of body weight, animals were divided into the following six groups: early (12-week), middle (30-week), and chronic (52-week) diabetic groups and their controls. MBP immunoreactivity was found in the alveus, strata pyramidale, and lacunosum-moleculare of the CA1 region, strata pyramidale and radiatum of the CA3 region, and subgranular zone, polymorphic layer, and molecular layer of the dentate gyrus. MBP immunoreactivity was lowest in the hippocampus of 12-week-old rats in the ZLC group, and highest in 12-week-old rats in the ZDF group. Diabetes increased MBP levels in the 12-week-old group, while MBP immunoreactivity decreased in the 30-week-old group. In the 52-week-old ZLC and ZDF groups, MBP immunoreactivity was detected in the hippocampus, similar to the 30-week-old ZDF group. Western blot results corroborated with immunohistochemical results. These results suggested that changes in the immunoreactivity and expression of MBP in the hippocampus might be a compensatory response to aging, while the sustained levels of MBP in diabetic animals could be attributed to a loss of compensatory responses in oligodendrocytes.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.24 no.1
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• pp.7-18
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• 2021

Purpose: The long-term efficacy and safety of infliximab (IFX) in children with ulcerative colitis (UC) have not been well-evaluated. Here, we reviewed the long-term durability and safety of IFX in our single center pediatric cohort with UC. Methods: This retrospective study included 20 children with UC who were administered IFX. Results: For induction, 5 mg/kg IFX was administered at weeks 0, 2, and 6, followed by every 8 weeks for maintenance. The dose and interval of IFX were adjusted depending on clinical decisions. Corticosteroid (CS)-free remission without dose escalation (DE) occurred in 30% and 25% of patients at weeks 30 and 54, respectively. Patients who achieved CS-free remission without DE at week 30 sustained long-term IFX treatment without colectomy. However, one-third of the patients discontinued IFX treatment because of a primary nonresponse, and one-third experienced secondary loss of response (sLOR). IFX durability was higher in patients administered IFX plus azathioprine for >6 months. Four of five patients with very early onset UC had a primary nonresponse. Infusion reactions (IRs) occurred in 10 patients, resulting in discontinuation of IFX in four of these patients. No severe opportunistic infections occurred, except in one patient who developed acute focal bacterial nephritis. Three patients developed psoriasis-like lesions. Conclusion: IFX is relatively safe and effective for children with UC. Clinical remission at week 30 was associated with long-term durability of colectomy-free IFX treatment. However, approximately two-thirds of the patients were unable to continue IFX therapy because of primary nonresponse, sLOR, IRs, and other side effects.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.455-461
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• 2021

Cardiomegaly is one of the most common diseases seen on chest X-rays, but if it is not detected early, it can cause serious complications. In view of this, in recent years, many researches on image analysis in which deep learning algorithms using artificial intelligence are applied to medical care have been conducted with the development of various science and technology fields. In this paper, we would like to evaluate whether the Inception V3 deep learning model is a useful model for the classification of Cardiomegaly using chest X-ray images. For the images used, a total of 1026 chest X-ray images of patients diagnosed with normal heart and those diagnosed with Cardiomegaly in Kyungpook National University Hospital were used. As a result of the experiment, the classification accuracy and loss of the Inception V3 deep learning model according to the presence or absence of Cardiomegaly were 96.0% and 0.22%, respectively. From the research results, it was found that the Inception V3 deep learning model is an excellent deep learning model for feature extraction and classification of chest image data. The Inception V3 deep learning model is considered to be a useful deep learning model for classification of chest diseases, and if such excellent research results are obtained by conducting research using a little more variety of medical image data, I think it will be great help for doctor's diagnosis in future.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Animal Bioscience
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• v.36 no.1
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• pp.29-42
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• 2023

Objective: Pigs, an ideal biomedical model for human diseases, suffer from about 50% early embryonic and fetal death, a major cause of fertility loss worldwide. However, identifying the causal variant remains a huge challenge. This study aimed to detect single nucleotide polymorphisms (SNPs) and candidate genes for the number of mummified (NM) piglets using the imputed whole-genome sequence (WGS) and validate the potential candidate genes. Methods: The imputed WGS was introduced from genotyping-by-sequencing (GBS) using a multi-breed reference population. We performed genome-wide association studies (GWAS) for NM piglets at birth from a Landrace pig populatiGWAS peak located on SSC11: 0.10 to 7.11 Mbp (Top SNP, SSC11:1,889,658 bp; p = 9.98E-13) was identified in cyclin dependent kinase on. A total of 300 Landrace pigs were genotyped by GBS. The whole-genome variants were imputed, and 4,252,858 SNPs were obtained. Various molecular experiments were conducted to determine how the genes affected NM in pigs. Results: A strong GWAS peak located on SSC11: 0.10 to 7.11 Mbp (Top SNP, SSC11:1,889,658 bp; p = 9.98E-13) was identified in cyclin dependent kinase 8 (CDK8) gene, which plays a crucial role in embryonic retardation and lethality. Based on the molecular experiments, we found that Y-box binding protein 1 (YBX1) was a crucial transcription factor for CDK8, which mediated the effect of CDK8 in the proliferation of porcine ovarian granulosa cells via transforming growth factor beta/small mother against decapentaplegic signaling pathway, and, as a consequence, affected embryo quality, indicating that this pathway may be contributing to mummified fetal in pigs. Conclusion: A powerful imputation-based association study was performed to identify genes associated with NM in pigs. CDK8 was suggested as a functional gene for the proliferation of porcine ovarian granulosa cells, but further studies are required to determine causative mutations and the effect of loci on NM in pigs.

• Journal of the Korean Burn Society
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• v.23 no.2
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• pp.54-59
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• 2020

Purpose: A fourth degree burn is a full-thickness burn of the skin usually accompanied by damage to deep structures and commonly results in extensive damage to surrounding tissues which makes the treatment of the wound difficult. Coverage of these wound using free flap is known to effective but not commonly used. The purpose of our study is to review our experience and suggest early application of free flap surgery. Methods: A retrospective review was performed from 2010 to 2019, on a total of 34 fourth degree burn patients undergone free flap surgery as primary treatment in our hospital. We reviewed the location of the injury, etiology, TBSA (%), Presence of osteomyelitis, flap choice, complications, period of injury to surgery and healing. Results: Using free flap as a primary reconstrcuction, the outcome is satisfactory. The treatment period was shortened, and there was less loss of function due to complications. Also the incidence of osteomyelitis and amputation was significantly low. Conclusion: Applying free flap surgery as soon as possible in fourth degree burns is effective, such as reducing complications such as infection, reducing amputation, shortening treatment period, and preventing severe sequelae.

• Korean Journal of Environmental Biology
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• v.40 no.3
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• pp.239-246
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• 2022

Lactuca scariola L. is one of ecosystem-disturbance plants that grow everywhere such as roadsides, grasslands, railroads, banks, and fields. L. scariola usually occurs in autumn. It overwinters in rosette form. It flowers and produces seeds in early summer of the next year. Seeds of L. scariola can germinate immediately without dormancy when the temperature is over 20℃. Due to endogenous bacteria in seeds of L. scariola, it has a strong drought tolerance. Thus, it can grow well on roadsides. L. scariola should be controlled as it can result in 60-80% of soybean yield loss at densities above 50 plants m^-2. It is advisable to remove L. scariola as it competes with native plants by acting as a pioneer to other ecosystem-disturbance plants. Among various control methods, chemical control is the most effective method that is widely used. Soil treatment with herbicides such as oxyfluorfen EC and pendimethalin EC can inhibit the development of L. scariola. Foliar treatment herbicides glyphosate and glufosinateammonium are widely used. L. scariola is resistant to 2,4-D, dicamba, and MCPA among foliar treatment herbicides. Thus, it is recommended to apply herbicides with different modes of action.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.227-241
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• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.