Seung-Ji Yang;Young-june Park;Sung-Eun Kim;Jun-Geol Ahn;Hyun-Ik Yang
Composites Research
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v.37
no.1
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pp.7-14
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2024
Due to the structural characteristic of a double roller, the double roller can have various deformation behaviors depending on a gap block design, even if dimensions and loading conditions for the double roller are the same. Based on this feature, we propose a strategy for designing the gap block of the carbon-fiber reinforced plastic (CFRP) double roller to minimize defects (e.g., sagging and wrinkling), which can be raised during the product conveying process, with the pursue of the lightweight design. In the suggested strategy, analysis cases are first selected by considering main design parameters and engineering tolerances of the gap block, and then deformation behaviors of these selected cases are extracted using the finite element method (FEM). Here, to obtain the optimal gap block parameters that satisfy the purpose of this study, deformation deviations in the contact area are calculated and compared using the extracted deformation behaviors. Note that the contact area in this work is located between the product and the roller. As a result, through the design method of the gap block proposed in this work, it is possible to construct the CFRP double roller that can significantly decrease the defects without changing the overall sizes of the roller. A detailed method is suggested herein, and the results are evaluated in a numerical way.
The development of transportation methods has improved human transportation convenience and made it possible to expand the travel radius of people with disabilities who have difficulty moving. However, in the case of WAV (wheelchair Accessible Vehicle), the safety that may occur in a vehicle accident is still lower than that of regular passenger seats. In particular, in the case of a rear-end collision that may occur in a defenseless situation, it can cause fatal neck injuries to disabled passengers. Therefore, a more detailed design plan must be reflected in the headrest to be applied to WAV. In this study, a multi-cell headrest was proposed to implement local compression characteristic distribution of the headrest during rear-end collision of WAV. Afterwards, a correlation analysis was performed between the passenger's NIC (Neck Injury Criterion) and impact energy absorption using the data set construction through analysis and the clustering results using k-means clustering. As a result of clustering, it was confirmed that data clusters with similar characteristics were formed, and a correlation analysis between NIC and impact energy absorption through the characteristics of each cluster was performed. As a result of the analysis, it was confirmed that the softer the cell compression characteristics in Mid3 and Mid6, the more impact energy absorption increases, and the harder the cell compression characteristics in Front2, Mid3, and Mid6, the more effective it is in reducing NIC.
Cigarette smoke extract (CSE)-treated mouse airway epithelial cells (MAECs)-derived exosomes accelerate the progression of chronic obstructive pulmonary disease (COPD) by upregulating triggering receptor expressed on myeloid cells 1 (TREM-1); however, the specific mechanism remains unclear. We aimed to explore the potential mechanisms of CSE-treated MAECs-derived exosomes on M1 macrophage polarization and pyroptosis in COPD. In vitro, exosomes were extracted from CSE-treated MAECs, followed by co-culture with macrophages. In vivo, mice exposed to cigarette smoke (CS) to induce COPD, followed by injection or/and intranasal instillation with oe-TREM-1 lentivirus. Lung function and pathological changes were evaluated. CD68+ cell number and the levels of iNOS, TNF-α, IL-1β (M1 macrophage marker), and pyroptosis-related proteins (NOD-like receptor family pyrin domain containing 3, apoptosis-associated speck-like protein containing a caspase-1 recruitment domain, caspase-1, cleaved-caspase-1, gasdermin D [GSDMD], and GSDMD-N) were examined. The expression of maternally expressed gene 3 (MEG3), spleen focus forming virus proviral integration oncogene (SPI1), methyltransferase 3 (METTL3), and TREM-1 was detected and the binding relationships among them were verified. MEG3 increased N6-methyladenosine methylation of TREM-1 by recruiting SPI1 to activate METTL3. Overexpression of TREM-1 or METTL3 negated the alleviative effects of MEG3 inhibition on M1 polarization and pyroptosis. In mice exposed to CS, EXO-CSE further aggravated lung injury, M1 polarization, and pyroptosis, which were reversed by MEG3 inhibition. TREM-1 overexpression negated the palliative effects of MEG3 inhibition on COPD mouse lung injury. Collectively, CSE-treated MAECs-derived exosomal long non-coding RNA MEG3 may expedite M1 macrophage polarization and pyroptosis in COPD via the SPI1/METTL3/TREM-1 axis.
Journal of Practical Agriculture & Fisheries Research
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v.25
no.4
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pp.78-83
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2024
This study was carried out to analyze the effect of changes in the light environment caused by the daylight disturbance on the growth, flowering, and cut flower quality of spray chrysanthemums. The spray chrysanthemum 'Yellow Cap' and 'Pitch PangPang' cultivars for cut flowers were artificially shaded to interfere with 66% of sunlight compared to the non-shading, and then the growing and flowering characteristics, and cut flower yield were investigated accordingly. There was no significant difference in the cut flower yield per unit area between the shading and the non-shading treatments. However, the number of days to flowering was 72.1 days for the 'Yellow Cap' and 65.2 days for the 'Pitch PangPang', which were delayed by 14.1 and 8.9 days, respectively, compared to the non-shading light. In the shading treatment, the flower diameter and the number of flowers also decreased by 10% and 15%, and 30% and 28% for both 'Yellow Cap' and 'Pitch PangPang', respectively. The stem length also decreased by 10% and 20%, the stem diameter by 23% and 37%, and fresh weight by 32% and 33%, respectively. The shading treatment delayed the flowering of chrysanthemums and reduced the growth such as flower diameter, number of flowers, and the length and weight of cut flowers. Based on these results, the daylight disturbance by artificial buildings is expected to reduce the productivity and quality of cut flowers by limiting the light intensity needed for chrysanthemum growth, flower bud differentiation, and flower development. Therefore, further research is needed on the rate of decrease in yield and market value according to the degree of shading to relieve damage to chrysanthemum growers caused by the daylight disturbance.
With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.
Changsoo Woo;Kwan Hyeong Jo;Beomseok Sohn;Kisung Park;Hojin Cho;Won Jun Kang;Jinna Kim;Seung-Koo Lee
Korean Journal of Radiology
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v.24
no.1
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pp.51-61
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2023
Objective: To develop and test a machine learning model for classifying human papillomavirus (HPV) status of patients with oropharyngeal squamous cell carcinoma (OPSCC) using 18F-fluorodeoxyglucose (18F-FDG) PET-derived parameters in derived parameters and an appropriate combination of machine learning methods in patients with OPSCC. Materials and Methods: This retrospective study enrolled 126 patients (118 male; mean age, 60 years) with newly diagnosed, pathologically confirmed OPSCC, that underwent 18F-FDG PET-computed tomography (CT) between January 2012 and February 2020. Patients were randomly assigned to training and internal validation sets in a 7:3 ratio. An external test set of 19 patients (16 male; mean age, 65.3 years) was recruited sequentially from two other tertiary hospitals. Model 1 used only PET parameters, Model 2 used only clinical features, and Model 3 used both PET and clinical parameters. Multiple feature transforms, feature selection, oversampling, and training models are all investigated. The external test set was used to test the three models that performed best in the internal validation set. The values for area under the receiver operating characteristic curve (AUC) were compared between models. Results: In the external test set, ExtraTrees-based Model 3, which uses two PET-derived parameters and three clinical features, with a combination of MinMaxScaler, mutual information selection, and adaptive synthetic sampling approach, showed the best performance (AUC = 0.78; 95% confidence interval, 0.46-1). Model 3 outperformed Model 1 using PET parameters alone (AUC = 0.48, p = 0.047) and Model 2 using clinical parameters alone (AUC = 0.52, p = 0.142) in predicting HPV status. Conclusion: Using oversampling and mutual information selection, an ExtraTree-based HPV status classifier was developed by combining metabolic parameters derived from 18F-FDG PET/CT and clinical parameters in OPSCC, which exhibited higher performance than the models using either PET or clinical parameters alone.
Xu Yang;Xia Lu;Jun Liu;Ying Kan;Wei Wang;Shuxin Zhang;Lei Liu;Jixia Li;Jigang Yang
Korean Journal of Radiology
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v.23
no.4
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pp.466-478
/
2022
Objective: 18F-fluorodeoxyglucose (FDG) PET/CT is often used for detecting malignancy in patients with newly diagnosed hemophagocytic lymphohistiocytosis (HLH), with acceptable sensitivity but relatively low specificity. The aim of this study was to improve the diagnostic ability of 18F-FDG PET/CT in identifying malignancy in patients with HLH by combining 18F-FDG PET/CT and clinical parameters. Materials and Methods: Ninety-seven patients (age ≥ 14 years) with secondary HLH were retrospectively reviewed and divided into the derivation (n = 71) and validation (n = 26) cohorts according to admission time. In the derivation cohort, 22 patients had malignancy-associated HLH (M-HLH) and 49 patients had non-malignancy-associated HLH (NM-HLH). Data on pretreatment 18F-FDG PET/CT and laboratory results were collected. The variables were analyzed using the Mann-Whitney U test or Pearson's chi-square test, and a nomogram for predicting M-HLH was constructed using multivariable binary logistic regression. The predictors were also ranked using decision-tree analysis. The nomogram and decision tree were validated in the validation cohort (10 patients with M-HLH and 16 patients with NM-HLH). Results: The ratio of the maximal standardized uptake value (SUVmax) of the lymph nodes to that of the mediastinum, the ratio of the SUVmax of bone lesions or bone marrow to that of the mediastinum, and age were selected for constructing the model. The nomogram showed good performance in predicting M-HLH in the validation cohort, with an area under the receiver operating characteristic curve of 0.875 (95% confidence interval, 0.686-0.971). At an appropriate cutoff value, the sensitivity and specificity for identifying M-HLH were 90% (9/10) and 68.8% (11/16), respectively. The decision tree integrating the same variables showed 70% (7/10) sensitivity and 93.8% (15/16) specificity for identifying M-HLH. In comparison, visual analysis of 18F-FDG PET/CT images demonstrated 100% (10/10) sensitivity and 12.5% (2/16) specificity. Conclusion: 18F-FDG PET/CT may be a practical technique for identifying M-HLH. The model constructed using 18F-FDG PET/CT features and age was able to detect malignancy with better accuracy than visual analysis of 18F-FDG PET/CT images.
Minjae Kim;Jeong Hyun Lee;Leehi Joo;Boryeong Jeong;Seonok Kim;Sungwon Ham;Jihye Yun;NamKug Kim;Sae Rom Chung;Young Jun Choi;Jung Hwan Baek;Ji Ye Lee;Ji-hoon Kim
Korean Journal of Radiology
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v.23
no.11
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pp.1078-1088
/
2022
Objective: To develop and validate a model using radiomics features from apparent diffusion coefficient (ADC) map to diagnose local tumor recurrence in head and neck squamous cell carcinoma (HNSCC). Materials and Methods: This retrospective study included 285 patients (mean age ± standard deviation, 62 ± 12 years; 220 male, 77.2%), including 215 for training (n = 161) and internal validation (n = 54) and 70 others for external validation, with newly developed contrast-enhancing lesions at the primary cancer site on the surveillance MRI following definitive treatment of HNSCC between January 2014 and October 2019. Of the 215 and 70 patients, 127 and 34, respectively, had local tumor recurrence. Radiomics models using radiomics scores were created separately for T2-weighted imaging (T2WI), contrast-enhanced T1-weighted imaging (CE-T1WI), and ADC maps using non-zero coefficients from the least absolute shrinkage and selection operator in the training set. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of each radiomics score and known clinical parameter (age, sex, and clinical stage) in the internal and external validation sets. Results: Five radiomics features from T2WI, six from CE-T1WI, and nine from ADC maps were selected and used to develop the respective radiomics models. The area under ROC curve (AUROC) of ADC radiomics score was 0.76 (95% confidence interval [CI], 0.62-0.89) and 0.77 (95% CI, 0.65-0.88) in the internal and external validation sets, respectively. These were significantly higher than the AUROC values of T2WI (0.53 [95% CI, 0.40-0.67], p = 0.006), CE-T1WI (0.53 [95% CI, 0.40-0.67], p = 0.012), and clinical parameters (0.53 [95% CI, 0.39-0.67], p = 0.021) in the external validation set. Conclusion: The radiomics model using ADC maps exhibited higher diagnostic performance than those of the radiomics models using T2WI or CE-T1WI and clinical parameters in the diagnosis of local tumor recurrence in HNSCC following definitive treatment.
Jae-young Park;Jung Hwan Lee;Mo-Yeol Kang;Tae-Won Jang;Hyoung-Ryoul Kim;Se-Yeong Kim;Jongin Lee
Annals of Occupational and Environmental Medicine
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v.35
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pp.24.1-24.15
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2023
Background: The construction workers are vulnerable to fatigue due to high physical workload. This study aimed to investigate the relationship between overwork and heart rate in construction workers and propose a scheme to prevent overwork in advance. Methods: We measured the heart rates of construction workers at a construction site of a residential and commercial complex in Seoul from August to October 2021 and develop an index that monitors overwork in real-time. A total of 66 Korean workers participated in the study, wearing real-time heart rate monitoring equipment. The relative heart rate (RHR) was calculated using the minimum and maximum heart rates, and the maximum acceptable working time (MAWT) was estimated using RHR to calculate the workload. The overwork index (OI) was defined as the cumulative workload evaluated with the MAWT. An appropriate scenario line (PSL) was set as an index that can be compared to the OI to evaluate the degree of overwork in real-time. The excess overwork index (EOI) was evaluated in real-time during work performance using the difference between the OI and the PSL. The EOI value was used to perform receiver operating characteristic (ROC) curve analysis to find the optimal cut-off value for classification of overwork state. Results: Of the 60 participants analyzed, 28 (46.7%) were classified as the overwork group based on their RHR. ROC curve analysis showed that the EOI was a good predictor of overwork, with an area under the curve of 0.824. The optimal cut-off values ranged from 21.8% to 24.0% depending on the method used to determine the cut-off point. Conclusion: The EOI showed promising results as a predictive tool to assess overwork in real-time using heart rate monitoring and calculation through MAWT. Further research is needed to assess physical workload accurately and determine cut-off values across industries.
Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a worldwide public health threat. Recently, Klebsiella pneumoniae carbapenemase-2 (KPC-2)-producing sequence type (ST) 307 was identified main clone of CRKP, and dissemination of ST307 was reported in South Korea. This study examined the molecular characteristic and antimicrobial resistance pattern of 50 CRKP isolated from a tertiary hospital in Daejeon, from March 2020 to December 2021. Epidemiological relationship was analyzed by Multilocus sequence typing (MLST) and antimicrobial susceptibility test was determined using disk-diffusion method. PCR and DNA sequence analysis were performed to identify carbapenemase genes. CRKP infections were significantly more frequent in males and the patients aged ≥ 60 years. Among the 50 CRKP isolates, 46 isolates (92.0%) were multidrug-resistant (MDR), and 44 isolates (88.0%) were carbapenemase-producing K. pneumoniae (CPKP). The major carbapenemase type was KPC-2 (36 isolates, 72.0%) and New Delhi metalloenzyme-1 (NDM-1) and NDM-5 were identified in 7 isolates (14.0%) and 1 isolate (2.0%), respectively. In particular, 88.9% (32/36) of KPC-2-producing K. pneumoniae belonged to ST307, whereas 87.5% (7/8) of NDM-1,-5-producing K. pneumoniae belonged to non-ST307. These results suggest that proper infection control and effective surveillance network need to prevent not olny the spread of ST307, but also the development of non-ST307.
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