• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.195-205
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• 2022

This study aims to investigate the relationship between Corporate Venture Capital(CVC) investments and firm innovation, exploring the moderating effect of corporate ESG risk on this relationship. First, adopting the organizational learning theory, I theorize a process in which a firm's relationship with a venture through CVC investments acts as an external innovation source for learning and ultimately short-term innovation. Also, based on the discussion of the stakeholder theory, I argue that when a firm is evaluated as having high ESG risk externally, this may have a negative moderating effect that weakens the relationship between CVC investments and innovative performance. In order to verify these hypotheses, panel data analysis was performed using CVC investments data, patent application data, and ESG risk scores of US high-tech firms from 1993 to 2018. As a result of the analysis, as expected, it was found that the more the firm invests in ventures through CVC, the more the firm's innovative performance increases. In addition, the social aspect of ESG risk of a firm, related to the local community and employees, were found to weaken the association between CVC investments and innovative performance. This study expands the understanding of existing research on CVC investments as a vehicle for learning and innovation. Focusing on the importance of relationship with ventures rather than the size of CVC investments, I empirically examined that the formation of CVC relationships with ventures is directly related to the short-term innovation of investing firms. Additionally, this study contributes to the CVC literature by including stakeholders in the current discussion in addition to investing firms and portfolio ventures. Finally, this study investigated how ESG issues, which are attracting attention as playing an important role in firm activities, are related to CVC investments.

• Health Policy and Management
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• v.34 no.1
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• pp.26-37
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• 2024

Background: The purpose of this study was to compare and analyze the differences in charges and length of stay per case between spine specialty hospitals and non-specialty hospitals, and to identify the factors that influenced them. Methods: This study used claims data from the Health Insurance Review and Assessment Service, including inpatient visits from January 2021 to December 2022. The healthcare facility status data was used to identify the characteristics of study hospitals. Multilevel analysis was conducted to identify factors associated with the charges and Poisson regression analysis was conducted to analyze the length of stay between spine specialty hospitals and non-specialty hospitals. There were 32,015 cases of spine specialty hospitals and 17,555 cases of non-specialty hospitals. Results: For four of five common spinal surgeries, specialty hospitals shaped longer length of stay than those of non-specialty hospitals. Multilevel and Poisson regression analysis revealed that regardless of the type of surgery, higher age and higher Charlson comorbidity index scores were significantly associated with an increase in both the charges per case and length of stay (p<0.05). However, when hospitals were located in metropolitan areas, there was a significant decrease (p<0.05). Conclusion: This study found that specialty hospital had higher inpatient charges and loner length of stay contrary to the previous study results. Further studies will be needed to find which contribute to the differences.

• Health Policy and Management
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• v.34 no.1
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• pp.87-93
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• 2024

Background: In recent years, studies have shown conflicting results regarding the benefits of dietary supplements in reducing healthcare expenditures. This study aimed to address this inconsistency by examining the association between supplement consumption and health expenditures using nationally representative data from the Korea Health Panel Survey (2019-2020). Methods: A 1:1 matched case-control dataset was established using propensity score matching technique based on supplement consumption. Then, total annual healthcare expenditures were compared between the two groups. In addition, a multivariate regression analysis (Proc Surveyreg) was performed to determine the association between the supplement consumption and medical costs. Results: The supplement user group spent about 1.72 million Korean won, while the non-user group spent about 1.43 million Korean won on medical services (p=0.0186). The results of multivariate regression showed that the costs were approximately 26.15% higher in the user group than in the non-user group (p=0.0004). Conclusion: Contrary to the previous studies that have shown the benefits of supplement use in reducing healthcare costs, this study showed that those who consistently consumed supplements spent more on medical services. This can be interpreted in the same context as previous studies suggesting that dietary supplement intake is a healthy behavior for managing one's health. However, we caution against drawing firm conclusions due to data limitations. Further analysis using patient-level epidemiologic data is needed.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.1-17
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• 2024

This study sought to investigate the effects of cooperative learning emphasizing interactions on science-gifted elementary students' scientific creativity. Thirty-four science-gifted elementary students were divided into an experimental class and a comparison class to compare their creativity scores quantitatively. The experimental class participated in cooperative learning emphasizing interactions, and the comparison class participated in whole class interactions. For qualitative analysis, the small group discussions were audiotaped and transcribed. The results of the study are as follows. First, cooperative learning emphasizing interactions had a positive educational effect on usefulness, which is one of the essential elements of scientific creativity. Second, as the cooperative learning progressed, the interaction between the small group members improved qualitatively. Third, the factors hindering the effectiveness of cooperative learning included negative task-unrelated statements from some of the small group members and the following operational statements to correct them. Based on these results, this study proposed some suggestions for effective cooperative learning emphasizing interactions.

• Animal Bioscience
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• v.37 no.6
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• pp.1110-1120
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• 2024

Objective: This study was conducted to evaluate the effect of offering (OSF) or not (NSF) supplemental feed at milking on temperament (TS), udder hygiene (UHS) and body condition (BCS) scores, and milk yield per milking (MYM), milk quality traits, and profitability of primiparous Anatolian buffalo cows at 90 days of lactation confined in closed-tied (CB) or semi-open free-stall (OB) barns. Methods: In Experiment I, 108 cows were selected to encompass four treatments (OBOSF, OB-NSF, CB-OSF, and CB-NSF) of 27 cows, considering barn type (OB and CB) and supplementary feed (OSF and NSF) at milking. In Experiment II, 60 OB cows were selected to encompass one of five groups of 12 cows each: i) no supplemental feed (CON), ii) commercial concentrate (CC), iii) CC + corn silage (CCS), iv) CCS + alfalfa hay (CSA), or v) CC + ryegrass silage (CRS) at milking. Results: The TS and UHS of the OB and OSF cows were lower (better) than those of the CB and NSF cows, respectively. The OSF increased milk protein, lactose, and solids-not-fat but decreased milk freezing point and electrical conductivity compared with the NSF. The MYM and milk fat of the OB-OSF cows were higher than those of the OB-NSF and CBNSF cows. The TS and UHS of the cows negatively correlated with MYM and some milk chemicals (fat, protein, and solids-not-fat), but BCS correlated positively. The TS and milk electrical conductivity of the CCS, CSA, and CRS cows were lower than those of the CON and CC cows, but BCS, MYM, and milk fat were higher. Partial budget analysis identified a higher net profit for supplemental feed-offered groups (OB-OSF, CCS, CSA, and CRS). Conclusion: Offering roughage with concentrates at milking for indoor primiparous buffalo cows is more conducive to well-being, milk yield, milk quality, and economy.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.706-713
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• 2021

Objective: To evaluate the impact of surgical simulation training using a three-dimensional (3D)-printed model of tetralogy of Fallot (TOF) on surgical skill development. Materials and Methods: A life-size congenital heart disease model was printed using a Stratasys Object500 Connex2 printer from preoperative electrocardiography-gated CT scans of a 6-month-old patient with TOF with complex pulmonary stenosis. Eleven cardiothoracic surgeons independently evaluated the suitability of four 3D-printed models using composite Tango 27, 40, 50, and 60 in terms of palpation, resistance, extensibility, gap, cut-through ability, and reusability of. Among these, Tango 27 was selected as the final model. Six attendees (two junior cardiothoracic surgery residents, two senior residents, and two clinical fellows) independently performed simulation surgeries three times each. Surgical proficiency was evaluated by an experienced cardiothoracic surgeon on a 1-10 scale for each of the 10 surgical procedures. The times required for each surgical procedure were also measured. Results: In the simulation surgeries, six surgeons required a median of 34.4 (range 32.5-43.5) and 21.4 (17.9-192.7) minutes to apply the ventricular septal defect (VSD) and right ventricular outflow tract (RVOT) patches, respectively, on their first simulation surgery. These times had significantly reduced to 17.3 (16.2-29.5) and 13.6 (10.3-30.0) minutes, respectively, in the third simulation surgery (p = 0.03 and p = 0.01, respectively). The decreases in the median patch appliance time among the six surgeons were 16.2 (range 13.6-17.7) and 8.0 (1.8-170.3) minutes for the VSD and RVOT patches, respectively. Summing the scores for the 10 procedures showed that the attendees scored an average of 28.58 ± 7.89 points on the first simulation surgery and improved their average score to 67.33 ± 15.10 on the third simulation surgery (p = 0.008). Conclusion: Inexperienced cardiothoracic surgeons improved their performance in terms of surgical proficiency and operation time during the experience of three simulation surgeries using a 3D-printed TOF model using Tango 27 composite.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.334-343
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• 2021

Objective: We aimed to develop a prediction model for diagnosing severe aortic stenosis (AS) using computed tomography (CT) radiomics features of aortic valve calcium (AVC) and machine learning (ML) algorithms. Materials and Methods: We retrospectively enrolled 408 patients who underwent cardiac CT between March 2010 and August 2017 and had echocardiographic examinations (240 patients with severe AS on echocardiography [the severe AS group] and 168 patients without severe AS [the non-severe AS group]). Data were divided into a training set (312 patients) and a validation set (96 patients). Using non-contrast-enhanced cardiac CT scans, AVC was segmented, and 128 radiomics features for AVC were extracted. After feature selection was performed with three ML algorithms (least absolute shrinkage and selection operator [LASSO], random forests [RFs], and eXtreme Gradient Boosting [XGBoost]), model classifiers for diagnosing severe AS on echocardiography were developed in combination with three different model classifier methods (logistic regression, RF, and XGBoost). The performance (c-index) of each radiomics prediction model was compared with predictions based on AVC volume and score. Results: The radiomics scores derived from LASSO were significantly different between the severe AS and non-severe AS groups in the validation set (median, 1.563 vs. 0.197, respectively, p < 0.001). A radiomics prediction model based on feature selection by LASSO + model classifier by XGBoost showed the highest c-index of 0.921 (95% confidence interval [CI], 0.869-0.973) in the validation set. Compared to prediction models based on AVC volume and score (c-indexes of 0.894 [95% CI, 0.815-0.948] and 0.899 [95% CI, 0.820-0.951], respectively), eight and three of the nine radiomics prediction models showed higher discrimination abilities for severe AS. However, the differences were not statistically significant (p > 0.05 for all). Conclusion: Models based on the radiomics features of AVC and ML algorithms may perform well for diagnosing severe AS, but the added value compared to AVC volume and score should be investigated further.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.983-993
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• 2021

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

• Korean Journal of Radiology
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• v.22 no.4
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• pp.652-662
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• 2021

Objective: To investigate the association between CT imaging features and survival outcomes in patients with primary invasive mucinous adenocarcinoma (IMA). Materials and Methods: Preoperative CT image findings were consecutively evaluated in 317 patients with resected IMA from January 2011 to December 2015. The association between CT features and long-term survival were assessed by univariate analysis. The independent prognostic factors were identified by the multivariate Cox regression analyses. The survival comparison of IMA patients was investigated using the Kaplan-Meier method and propensity scores. Furthermore, the prognostic impact of CT features was assessed based on different imaging subtypes, and the results were adjusted using the Bonferroni method. Results: The median follow-up time was 52.8 months; the 5-year disease-free survival (DFS) and overall survival rates of resected IMAs were 68.5% and 77.6%, respectively. The univariate analyses of all IMA patients demonstrated that 15 CT imaging features, in addition to the clinicopathologic characteristics, significantly correlated with the recurrence or death of IMA patients. The multivariable analysis revealed that five of them, including imaging subtype (p = 0.002), spiculation (p < 0.001), tumor density (p = 0.008), air bronchogram (p < 0.001), emphysema (p < 0.001), and location (p = 0.029) were independent prognostic factors. The subgroup analysis demonstrated that pneumonic-type IMA had a significantly worse prognosis than solitary-type IMA. Moreover, for solitary-type IMAs, the most independent CT imaging biomarkers were air bronchogram and emphysema with an adjusted p value less than 0.05; for pneumonic-type IMA, the tumors with mixed consolidation and ground-glass opacity were associated with a longer DFS (adjusted p = 0.012). Conclusion: CT imaging features characteristic of IMA may provide prognostic information and individual risk assessment in addition to the recognized clinical predictors.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1323-1331
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• 2021

Objective: To identify the association between renal tumor complexity and pathologic renal sinus invasion (RSI) and evaluate the usefulness of computed tomography tumor features for predicting RSI in patients with renal cell carcinoma (RCC). Materials and Methods: This retrospective study included 276 consecutive patients who underwent radical nephrectomy for RCC with a size of ≤ 7 cm between January 2014 and October 2017. Tumor complexity and anatomical renal sinus involvement were evaluated using two standardized scoring systems: the radius (R), exophytic or endophytic (E), nearness to collecting system or sinus (N), anterior or posterior (A), and location relative to polar lines (RENAL) nephrometry and preoperative aspects and dimensions used for anatomical classification (PADUA) system. CT-based tumor features, including shape, enhancement pattern, margin at the interface of the renal sinus (smooth vs. non-smooth), and finger-like projection of the mass, were also assessed by two independent radiologists. Univariable and multivariable logistic regression analyses were performed to identify significant predictors of RSI. The positive predictive value, negative predictive value (NPV), accuracy of anatomical renal sinus involvement, and tumor features were evaluated. Results: Eighty-one of 276 patients (29.3%) demonstrated RSI. Among highly complex tumors (RENAL or PADUA score ≥ 10), the frequencies of RSI were 42.4% (39/92) and 38.0% (71/187) using RENAL and PADUA scores, respectively. Multivariable analysis showed that a non-smooth margin and the presence of a finger-like projection were significant predictors of RSI. Anatomical renal sinus involvement showed high NPVs (91.7% and 95.2%) but low accuracy (40.2% and 43.1%) for RSI, whereas the presence of a non-smooth margin or finger-like projection demonstrated comparably high NPVs (90.0% and 91.3% for both readers) and improved accuracy (67.0% and 73.9%, respectively). Conclusion: A non-smooth margin or the presence of a finger-like projection can be used as a preoperative CT-based tumor feature for predicting RSI in patients with RCC.