• Animal Bioscience
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• v.37 no.4
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• pp.689-696
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• 2024

Objective: Our study examined the impact of propriety blends of Bacillus strain probiotics on the performance, egg quality, and faecal microflora of laying hens. Methods: A total of 183 Institut de selection Animale (ISA) brown laying hens aged 23 weeks with an average body weight of 1,894±72 g were randomly allocated into 3 groups as control (corn-soybean meal based diet, CON), 0.5 g/kg Enterosure probiotics (ET1, 3×10⁸ colony-forming unit [CFU]/kg feed), and 5 g/kg Enterosure probiotics (ET2, 3×10⁹ CFU/kg feed) administered in mashed form. At the completion of each phase hen day egg production (HDEP), average egg weight (AEW), feed intake, and faecal microbiota were evaluated. Results: HDEP and AEW were higher (p<0.05) in the ET2-supplemented diet in phase 3 (week 9 to 12) compared with CON. Egg mass (EM) was higher (p<0.05) in phase 2 at ET2, and also higher (p<0.05) in phase 3 at the ET1 and ET2-supplemented diets compared with CON. Feed conversion ratio was lower (p<0.05) in phase 3 at the ET1 and ET2-supplemented diets, with ET2 being the lowest compared with ET1 and CON. Yolk colour was higher (p<0.05) in the ET-supplemented diets at phase 3 compared with CON. Bifidobacterium spp. was higher (p<0.05) in the ET2- supplemented diet compared with CON in phase 2, while in In phase 3, Lactobacillus spp. and Bifidobacterium spp. were higher (p<0.05) in the ET-supplemented diets compared with CON. Coliforms were lower (p<0.05) in the ET-supplemented diets compared with CON in phase 3. Conclusion: The propriety blends of Bacillus strain probiotics supplements at 0.5 g/kg and 5 g/kg could improve the production and quality of eggs with more significance at 5 g/kg for HDEP, AEW and EM, which was achieved via the increase of beneficial microbiomes such as Lactobacillus spp., Bifidobacterium spp., and the decrease of pathogenic microbiomes like Escherichia coli and Coliforms which was speculated to improve gut barrier function and the reproductive hormone.

• Animal Bioscience
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• v.37 no.5
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• pp.862-874
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• 2024

Objective: This study evaluated the effect of Andrographis paniculata (A. paniculata) supplementation in sow diets before and after farrowing on the sow and piglets' performances during early postpartum period and on sows' backfat and longissimus muscle losses during lactation. Methods: Seventy Landrace×Yorkshire sows and their offspring (1,186 piglets) were distributed into three groups: control (n = 31), treatment-250 (n = 18), and treatment-1000 (n = 21). From 110.2±0.7 days of gestation until farrowing (5.8 days) and throughout the lactation period (25.2 days), sows in the control group were given the conventional lactation diet, while sows in the treatment-250 and treatment-1000 groups received supplements of 250 ppm and 1,000 ppm of A. paniculata, respectively. Results: In sows with parity 3-5, piglets from the treatment-1000 group had higher colostrum intake than the control and treatment-250 groups (p<0.05), but not in sows with parity 6-9. Colostrum immunoglobulin G (IgG) increased in treated sows versus controls for parity 6-9 (p<0.05), but was consistent for parity 3-5. Piglet performance until day 3 postnatal was similar across groups (p>0.05). Treatment-250 sows had higher feed intake post-farrowing than treatment-1000 sows (p<0.05). Longissimus loss was less in both treatment groups than control (p<0.05), but backfat loss was similar across groups (p>0.05). Post-partum complications were consistent across groups (p>0.05). Farrowing duration and piglet birth intervals in sows with parity 6-9 were prolonged in the treatment-1000 group. Conclusion: Supplementing with 1,000 ppm A. paniculata for 5.8 days pre-farrowing and 25.2 days post-farrowing enhanced sow colostrum IgG and piglet colostrum intake, while also reducing longissimus loss in sows. However, for sows of parity 6-9, this supplementation led to prolonged farrowing, increased intervals between piglet births, increased stillbirth, and reduced piglet birth weight. These effects should be considered when using A. paniculata supplementation.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1172-1184
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• 2021

Objective: The purposes of this study were to analyze the radiation doses for pediatric abdominopelvic and chest CT examinations from university hospitals in Korea and to establish the local diagnostic reference levels (DRLs) based on the body weight and size. Materials and Methods: At seven university hospitals in Korea, 2494 CT examinations of patients aged 15 years or younger (1625 abdominopelvic and 869 chest CT examinations) between January and December 2017 were analyzed in this study. CT scans were transferred to commercial automated dose management software for the analysis after being de-identified. DRLs were calculated after grouping the patients according to the body weight and effective diameter. DRLs were set at the 75th percentile of the distribution of each institution's typical values. Results: For body weights of 5, 15, 30, 50, and 80 kg, DRLs (volume CT dose index [CTDI_vol]) were 1.4, 2.2, 2.7, 4.0, and 4.7 mGy, respectively, for abdominopelvic CT and 1.2, 1.5, 2.3, 3.7, and 5.8 mGy, respectively, for chest CT. For effective diameters of < 13 cm, 14-16 cm, 17-20 cm, 21-24 cm, and > 24 cm, DRLs (size-specific dose estimates [SSDE]) were 4.1, 5.0, 5.7, 7.1, and 7.2 mGy, respectively, for abdominopelvic CT and 2.8, 4.6, 4.3, 5.3, and 7.5 mGy, respectively, for chest CT. SSDE was greater than CTDI_vol in all age groups. Overall, the local DRL was lower than DRLs in previously conducted dose surveys and other countries. Conclusion: Our study set local DRLs in pediatric abdominopelvic and chest CT examinations for the body weight and size. Further research involving more facilities and CT examinations is required to develop national DRLs and update the current DRLs.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1213-1224
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• 2021

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.178-185
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• 2007

Myrionecta rubra Jankowski 1976(=Mesodinium rubrum Lohmann 1908), a mixotrophic ciliate, is very common and often causes recurrent red tides in diverse marine environments. Since the report on the first laboratory strain of this species in 2000, papers on its novel ecological role and evolutionary importance have been high lighted. This review paper is prepared to promote the de novo recognition M. rubra as a marine mixotrophic species. M. rubra is a ciliate which is able to photosynthesize using plastids originated from cryptophyte (including Teleaulax sp. and Geminigera sp.) prey cells (i.e. kleptoplastidic ciliate). Recently, novel bacterivory of M. rubra was firstly reported. Thus, the nutritional modes of M. rubra include photosynthesis, bacterivory, and algivory. In turn, M. rubra was reported as the prey species of metazoan predators such as calanoid copepods, mysids, larvae of ctenophore and anchovy, and spats of bivalves. In addition, it was reported that dinoflagellate Dinophysis causing diarrhetic shellfish poisoning is one among the predators of M. rubra. Thus, M. rubra, a marine mixotrophic ciliate, may play a pivotal role as a common linking ciliate for the flow of energy and organic material in pelagic food webs.

• Computers and Concrete
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• v.33 no.5
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• pp.497-507
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• 2024

In squat reinforced concrete walls, the displacement capacity for lateral deformation is low and the ability to resist the axial load can quickly be lost, generating collapse. This work consists of testing two squat reinforced concrete walls. One of the specimens is built with conventional detailing of reinforced concrete walls, while the second specimen is built applying an alternative design, including stirrups along the diagonal of the wall to improve its ductility. This solution differs from the detailing of beams or coupling elements that suggest building elements equivalent to columns located diagonally in the element. The dimensions of both specimens correspond to a wall with a low aspect ratio (1:1), where the height and length of the specimen are 1.4 m, with a thickness of 120 mm. The alternative wall included stirrups placed diagonally covering approximately 25% of the diagonal strut of the wall with alternative detailing. The walls were tested under a constant axial load of 0.1f'cAg and a cyclic lateral displacement was applied in the upper part of the wall. The results indicate that the lateral strength is almost identical between both specimens. On the other hand, the lateral displacement capacity increased by 25% with the alternative detailing, but it was also able to maintain the 3 complete hysteretic cycles up to a drift of 2.5%, reaching longitudinal reinforcement fracture, while the base specimen only reached the first cycle of 2% with rapid degradation due to failure of the diagonal compression strut. The alternative design also allows 46% more energy dissipation than the conventional design. A model was used to capture the global response, correctly representing the observed behavior. A parametric study with the model, varying the reinforcement amount and aspect ratio, was performed, indicating that the effectiveness of the alternative detailing can double de drift capacity for the case with a low aspect ratio (1.1) and a large longitudinal steel amount (1% in the web, 5% in the boundary), which decreases with lower amounts of longitudinal reinforcement and with the increment of aspect ratio, indicating that the alternative detailing approach is reasonable for walls with an aspect ratio up to 2, especially if the amount of longitudinal reinforcement is high.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.96-109
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• 2024

The purpose of this study is to propose a method for evaluating the similarity of Show gardens using Deep Learning models, specifically VGG-16 and ResNet50. A model for judging the similarity of show gardens based on VGG-16 and ResNet50 models was developed, and was referred to as DRG (Deep Recognition of similarity in show Garden design). An algorithm utilizing GAP and Pearson correlation coefficient was employed to construct the model, and the accuracy of similarity was analyzed by comparing the total number of similar images derived at 1st (Top1), 3rd (Top3), and 5th (Top5) ranks with the original images. The image data used for the DRG model consisted of a total of 278 works from the Le Festival International des Jardins de Chaumont-sur-Loire, 27 works from the Seoul International Garden Show, and 17 works from the Korea Garden Show. Image analysis was conducted using the DRG model for both the same group and different groups, resulting in the establishment of guidelines for assessing show garden similarity. First, overall image similarity analysis was best suited for applying data augmentation techniques based on the ResNet50 model. Second, for image analysis focusing on internal structure and outer form, it was effective to apply a certain size filter (16cm × 16cm) to generate images emphasizing form and then compare similarity using the VGG-16 model. It was suggested that an image size of 448 × 448 pixels and the original image in full color are the optimal settings. Based on these research findings, a quantitative method for assessing show gardens is proposed and it is expected to contribute to the continuous development of garden culture through interdisciplinary research moving forward.

• The Korean Society of Law and Medicine
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• v.25 no.1
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• pp.193-222
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• 2024

From a global trend, discussions on the patient's death with dignity are gradually progressing from the issue of withdrawal of life-sustaining treatment to the issue of whether to allow assisted death and its requirements. Several states in the United States and Western European countries such as Canada, Belgium, and the Netherlands have institutionalized treatment to accelerate the time of death through the assistance of doctors. In France, after a long period of raising and reviewing issues, discussions on related legislation are taking place at a slower pace than in other European countries. In France, social discussions and legislative attempts on death with dignity have been actively conducted since the late 20th century. The Leonetti Act of 2005 prohibited the continuation of meaningless treatment against the will of patients, and after the Clay-Leonetti Act of 2016, it was legalized to administer intensive and continuous sedatives to patients until death. However, unlike many neighboring European countries, treatment that speeds up the time of death itself is still prohibited in France, even if the patient wants. As the existential and universal question of whether to allow dying patients to die painlessly with the help of a doctor has recently emerged as an important issue, a number of lawmakers have submitted legislation to legalize assisted death. This paper examines the legislative process developed in relation to patients' rights to dignified death in France, and compares and reviews French legislation that attempts to legalize assisted death with the amendment to the Korean Life-Sustaining Treatment Act.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.137-142
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• 2024

Recently, deep learning technology has become those methods as de facto standards in the area of medical data representation. But, deep learning inherently requires a large amount of training data, which poses a challenge for its direct application in the medical field where acquiring large-scale data is not straightforward. Additionally, brain signal modalities also suffer from these problems owing to the high variability. Research has focused on designing deep neural network structures capable of effectively extracting spectro-spatio-temporal characteristics of brain signals, or employing self-supervised learning methods to pre-learn the neurophysiological features of brain signals. This paper analyzes methodologies used to handle small-scale data in emerging fields such as brain-computer interfaces and brain signal-based state prediction, presenting future directions for these technologies. At first, this paper examines deep neural network structures for representing brain signals, then analyzes self-supervised learning methodologies aimed at efficiently learning the characteristics of brain signals. Finally, the paper discusses key insights and future directions for deep learning-based brain signal analysis.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.243-256
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• 2024

Objective: We aimed to investigate whether 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[¹⁸F]FDG PET/CT) can aid in evaluating the risk of malignancy in ampullary tumors detected by endoscopy. Materials and Methods: This single-center retrospective cohort study analyzed 155 patients (79 male, 76 female; mean age, 65.7 ± 12.7 years) receiving 2-[¹⁸F]FDG PET/CT for endoscopy-detected ampullary tumors 5-87 days (median, 7 days) after the diagnostic endoscopy between June 2007 and December 2020. The final diagnosis was made based on histopathological findings. The PET imaging parameters were compared with clinical data and endoscopic features. A model to predict the risk of malignancy, based on PET, endoscopy, and clinical findings, was generated and validated using multivariable logistic regression analysis and an additional bootstrapping method. The final model was compared with standard endoscopy for the diagnosis of ampullary cancer using the DeLong test. Results: The mean tumor size was 17.1 ± 7.7 mm. Sixty-four (41.3%) tumors were benign, and 91 (58.7%) were malignant. Univariable analysis found that ampullary neoplasms with a blood-pool corrected peak standardized uptake value in earlyphase scan (SUVe) ≥ 1.7 were more likely to be malignant (odds ratio [OR], 16.06; 95% confidence interval [CI], 7.13-36.18; P < 0.001). Multivariable analysis identified the presence of jaundice (adjusted OR [aOR], 4.89; 95% CI, 1.80-13.33; P = 0.002), malignant traits in endoscopy (aOR, 6.80; 95% CI, 2.41-19.20; P < 0.001), SUVe ≥ 1.7 in PET (aOR, 5.43; 95% CI, 2.00-14.72; P < 0.001), and PET-detected nodal disease (aOR, 5.03; 95% CI, 1.16-21.86; P = 0.041) as independent predictors of malignancy. The model combining these four factors predicted ampullary cancers better than endoscopic diagnosis alone (area under the curve [AUC] and 95% CI: 0.925 [0.874-0.956] vs. 0.815 [0.732-0.873], P < 0.001). The model demonstrated an AUC of 0.921 (95% CI, 0.816-0.967) in candidates for endoscopic papillectomy. Conclusion: Adding 2-[¹⁸F]FDG PET/CT to endoscopy can improve the diagnosis of ampullary cancer and may help refine therapeutic decision-making, particularly when contemplating endoscopic papillectomy.