Recently, in the face of successive and unexpected global economic risks, ESG(Environmental, Social, and Governance) management has risen as an essential survival strategy for businesses. Particularly, the supply chain disruptions due to the COVID-19 pandemic have added to the uncertainty of risks, heightening the importance of ESG management in the distribution industry. In this context, the role of blockchain technology in strengthening and managing the connection between the distribution industry and ESG management has become increasingly significant. While there have been extensive proposals for business models that integrate blockchain technology into distribution, few studies have specifically focused on the feasibility and effectiveness of applying blockchain to ESG management in this field. Therefore, this study analyzed the relationship between blockchain and ESG management in the distribution industry by employing association analysis, a text mining technique, on Korean academic research. Through this, the study confirmed the possibility of implementing blockchain in the distribution industry's ESG management and presented keywords to guide future research directions. The findings obtained from this study are expected to be utilized as foundational research for future studies in constructing blockchain-based business models for ESG management in the distribution industry.
Purpose In the contemporary landscape, marked by the enduring impact of COVID-19 and the recent disruptions stemming from the conflict in Ukraine, the purpose of this study is to navigate the era characterized by pervasive risk and uncertainty. Specifically, the study aims to dissect the impact of the COVID-19 outbreak on digital transformation, exploring the factors influencing this process and considering the multifaceted dynamics at play. The focus extends to the post-COVID-19 landscape, scrutinizing the implications and meanings of digital transformation both before and after the pandemic. Additionally, the study delves into future digital trends, with particular attention to climate and environmental issues, emphasizing corporate responsibilities in averting crises similar to COVID-19. The overarching goal is to provide a holistic perspective, shedding light on both positive and negative facets of digital transformation, and advocating for regulatory enhancements and legal frameworks conducive to a balanced and resilient digital future. Design/methodology/approach This study employs a comprehensive approach to analyze the impact of the COVID-19 outbreak on digital transformation. It considers various facets, such as smart devices reshaping daily routines, transformative changes in corporate ecosystems, and the adaptation of government institutions to the digital era within the broader context of the Fourth Industrial Revolution. The analysis extends to the post-COVID-19 landscape, examining the implications and meanings of digital transformation. Future digital trends, especially those related to climate and environmental issues, are prognosticated. The methodology involves a proactive exploration of challenges associated with digital transformation, aiming to advocate for regulatory enhancements and legal frameworks that contribute to a balanced and resilient digital future. Findings The findings of this study reveal that the digital economy has gained momentum, accelerated by the proliferation of non-face-to-face industries in response to social distancing imperatives during the COVID-19 pandemic. Digital transformation, both preceding and succeeding the onset of the pandemic, has precipitated noteworthy shifts in various aspects of daily life. However, challenges persist, and the study highlights factors that either bolster or hinder the transformative process. In the post-COVID-19 era, corporate responsibilities in averting crises, particularly those resembling the pandemic, take center stage. The study emphasizes the need for a holistic perspective, acknowledging both positive and negative facets of digital transformation. Additionally, it calls for proactive measures, including regulatory enhancements and legal frameworks, to ensure a balanced and resilient digital future.
The school drop-out among the youth has grown to become a serious social problem since about 2000 and calls for an attention to its seriousness. Therefore, this study reviewed the statitistical reports and the previous empirical findings on the school drop-out and integrated to establish a comprehensive understanding of this social phenomenon. The main concepts and terminologies on school drop-out, the current statistics, the possible causal factors and the usual trajectory the youth take after dropping-out of school were discussed to conceptualize the issue. Analyses indicated 12 characteristics of the students who dropped out of school. Those 12 characteristics were restructured according to the ecological conceptual model. The social instability and the financial crisis in the 1990's has eroded the stability of the primary environments of adolescents such as family and school. The family breakdowns from divorce and other reasons weakened psychological and financial support for adolescents. The diminished authority of teachers and school over students exposed conflicts between teacher and students, students' loss of purpose and interest in academic attainment. The adolescents showed emotional reponses like increased level of depression, helplessness, aggression, indicated cognitive reponses such as the loss of purpose and interest in studying, a heightened sense of uncertainty of the future, and behavioral responses like sexual acting out behaviors, and bullying. The unmet psychological needs of adolescents result in run-away and school drop-out behaviors, which in turn progress into juvenile delinquency as the society fails to provide adequate and appropriate guidance and interventions. The intervention strategies at the national level were proposed and the limitations of the study were discussed.
Bentonite, predominantly consists of expandable clay minerals, is considered to be the suitable buffering material in high-level radioactive waste disposal repository due to its large swelling property and low permeability. Additionally, the bentonite has large cation exchange capacity and specific surface area, and thus, it effectively retards the transport of leaked radionuclides to surrounding environments. This study aims to review the thermodynamic sorption models for four radionuclides (U, Am, Se, and Eu) and eight bentonites. Then, the thermodynamic sorption models and optimized sorption parameters were precisely analyzed by considering the experimental conditions in previous study. Here, the optimized sorption parameters showed that thermodynamic sorption models were related to experimental conditions such as types and concentrations of radionuclides, ionic strength, major competing cation, temperature, solid-to-liquid ratio, carbonate species, and mineralogical properties of bentonite. These results implied that the thermodynamic sorption models suggested by the optimization at specific experimental conditions had large uncertainty for application to various environmental conditions.
Background: The thermoluminescent dosimeter (TLD) and Monte Carlo (MC) dosimetry are carried out to determine the occupational dose for personnel in the handling of 125I seed sources. Materials and Methods: TLDs were placed in different layers of the Alderson-Rando phantom in the thyroid, lung and also eyes and skin surface. An 125I seed source was prepared and its activity was measured using a dose calibrator and was placed at two distances of 20 and 50 cm from the Alderson-Rando phantom. In addition, the Monte Carlo N-Particle Extended (MCNPX 2.6.0) code and a computational phantom with a lattice-based geometry were used for organ dose calculations. Results and Discussion: The comparison of TLD and MC results in the thyroid and lung is consistent. Although the relative difference of MC dosimetry to TLD for the eyes was between 4% and 13% and for the skin between 19% and 23%, because of the existence of a higher uncertainty regarding TLD positioning in the eye and skin, these inaccuracies can also be acceptable. The isodose distribution was calculated in the cross-section of the head phantom when the 125I seed was at two distances of 20 and 50 cm and it showed that the greatest dose reduction was observed for the eyes, skin, thyroid, and lungs, respectively. The results of MC dosimetry indicated that for near the head positions (distance of 20 cm) the absorbed dose rates for the eye lens, eye and skin were 78.1±2.3, 59.0±1.8, and 10.7±0.7 µGy/mCi/hr, respectively. Furthermore, we found that a 30 cm displacement for the 125I seed reduced the eye and skin doses by at least 3- and 2-fold, respectively. Conclusion: Using a computational phantom to monitor the dose to the sensitive organs (eye and skin) for personnel involved in the handling of 125I seed sources can be an accurate and inexpensive method.
Young Nae Choi;Yoon ho Shin;Hwangeui Cho;Jung Bok Kim
Journal of Food Hygiene and Safety
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v.38
no.6
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pp.420-429
/
2023
GC-MS/MS using liquid-liquid extraction (LLE) and C18 cartridges was used to identify and quantify levels of chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin and permethrin in bulk raw milk. A calibration curve spanning 10 ng/mL to 200 ng/mL was obtained with a satisfactory correlation coefficient of 0.99. The limits of detection (LOD) and limits of quantitation (LOQ) for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in the matrix ranged from 0.06 to 1.81 ng/mL and 0.19 to 6.04 ng/mL, respectively. The recoveries of 5 pesticides from spiked samples at 37.5-125 ng/mL ranged from 86.1 to 102.1%. The measurement of uncertainty of the GC-MS/MS method for these five pesticides was developed based on the analytical process and quantification. An analysis method that is easier and faster than the method specified in the Korean food standards codes for analyzing these five pesticides in raw material milk was developed. Moreover, the analytical method for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in bulk raw milk by GC-MS/MS was established.
The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.
This study was conducted focusing on the innovative behavior necessary for the long-term survival of an organization in a business environment in which uncertainty and complexity are increasing. To this end, the relationship between issue leadership and innovative behavior of organizational members was investigated from the perspective of Signaling theory, Path-Goal theory and Job Demands-Resources theory. In addition, the mediating role of learning agility and sub-components of learning agility was empirically analyzed. For empirical analysis, a survey was conducted with a total of 252 team leaders and team members working in multinational companies (142 in Korea, 110 in the US). The results of this study are as follows. Issue leadership was analyzed to have a positive (+) effect on the innovative behavior of employees. Learning agility was found to play a mediating role between issue leadership and innovative behavior. On the other hand, the mediating effect was tested for each of the sub-components of learning agility, such as feedback seeking, information seeking, reflecting, experimenting, agility. As a result, all five sub-components were found to play a mediating role between issue leadership and innovative behavior. In particular, it was analyzed that the mediating effect of agility was the largest. Next, information seeking appeared to be large. Although there are some studies that have identified the mediating role of learning agility between issue leadership and innovative behavior, this study is considered to have academic implication as there are few cases of subdivided study. At the practical level, it is expected to provide implications for where to focus more when trying to improve an organization's learning agility and innovation behavior
The purpose of this study is to provide evidences throught scoping review of education intervention studies for post kidney transplantation management in the kidney transplant patients in Korea. Through the search engines RISS, KISS, DB pia and Pubmed, 13 articles were selected by searching for theses and academic journals published prior to the search date of May 21, 2023. According to the study result, relevant studies were 13, and the education programs provided to kidney transplant patients were classified into 1) overall health management after transplantation, 2) self-efficacy promotion exercise program, 3) exercise therapy, 4) drug education, and 5) stress coping. Knowledge, implementation, self-efficacy, anxiety, uncertainty, stress, and quality of life were confirmed as effects of the intervention. Based on the results of this study, it is necessary to develop integrated educational materials and systematic self-management programs that can manage various health problems that may occur after kidney transplantation, and it is suggeste that research on educational interventions for kidney transplant patients in nursing.
Juhyi Yim;Jae Hoon Jung;Seokwon Jeon;Ki-Il Song;Young Jin Shin
Tunnel and Underground Space
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v.33
no.5
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pp.312-338
/
2023
The underground disposal facility for spent nuclear fuel demands a specialized design, distinct from conventional practices, to ensure long-term thermal, mechanical, and hydraulic integrity, preventing the release of radioactive isotopes from high-temperature spent nuclear fuel. SKB has established design criteria for such facilities and executed practical design implementations for Forsmark. Moreover, in response to subsurface uncertainty, SKB has proposed an empirical approach involving monitoring and adaptive design modifications, alongside stepwise development. SKB has further introduced a unique support system, categorizing ground types and behaviors and aligning them with corresponding support types to confirm safety through comparative analyses against existing systems. POSIVA has pursued a comparable approach, developing a support system for Onkalo while accounting for distinct geological characteristics compared to Forsmark. This demonstrates the potential for domestic implementation of spent nuclear fuel disposal facility designs and the establishment of a support system adapted to national attributes.
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