Recently, as social distancing have been raised due to the re-spread of COVID-19, the number of serial entrepreneurs who are closing their business is rapidly increasing. Learning from failure is a source of success, but business failure can result in psychological and economic losses and negative emotions of the serial entrepreneur. At this point, it is very important to find a way to recover the negative emotions caused by business failures of serial entrepreneurs. Recently, a strategic model has emerged to deal with the negative emotions of grief caused by business failures of serial entrepreneurs. This study identified the recovery factors from the grief of business failures of serial entrepreneurs and analyzed Shepherd's(2003) three areas: loss orientation, restoration orientation, and dual process. To this end, individual in-depth interviews were conducted with 12 small business serial entrepreneurs who challenged re-startup to identify the attributes of recovery factors that were not identified with quantitative data. As a result of the study, first, recovery factors were investigated in three areas: individual orientation, family orientation, and network orientation. It was found to help improve recovery in nine categories: self-esteem, persistence, personal competence, hobbies, self-confidence, family support, networks, religion, and social support. Second, recovery obstacle factors were investigated in three areas: psychological, economic, and environmental factors. Nine categories including family, health, social network, business partner, competitor, partner, fund, external environment, and government policy were found to persist negative emotions. Third, the emotional processing process for grief was investigated in three areas: loss orientation, restoration orientation, and dual process. Ten categories such as family, partner support, social member support, government support, hobbies, networks, change of business field, moving, third-party perspective, and meditation were confirmed to enhance rapid recovery in the emotional processing process for grief. The implications of this study are as follows. The process of recovering from the grief caused by business failures of serial entrepreneurs was attempted by a qualitative study. By extending the theory of Shepherd(2003), This study can be applied to help with recovery research. In addition, conceptual models and propositions for future empirical research were presented, which can be discussed in carious academic ways.
Forest biomass is used as a representative indicator of forest size, maturity, and productivity. Therefore, quantitative evaluation is important for management and harvest as well as the evaluation of ecosystem functions and services including CO2 absorption. The allometric equation is a widely used method for estimating the value of each component through the relative growth rate of plants. Recently, studies indicated that the relative growth of trees is changing because of the increased CO2 concentration in the atmosphere and the resulting climate change, raising the need to review the previously developed relative growth models and coefficients. In this study, the height-diameter at breast height (DBH) relationships of four major tree species in Korea [(Pinus densiflora (PD), Larix kaempferi (LK), Quercus variabilis (QV), and Quercus mongolica (QM)] were analyzed using the 5th-7th National Forest Inventory (NFI) data. Furthermore, these results were compared with the present yield table from the National Institute for Forest Science. This analysis revealed that the expected height for the same DBH increased as the NFI progressed. For example, in model analysis, the expected heights for PD, LK, QV, and QM for DBH of 25 cm were 12.48, 19.17, 14.47, and 13.19 m, respectively, in the 5th NFI data. In the 7th NFI data, these values were estimated as 13.61 (+9.1%), 21.58 (+12.7%), 15.76 (+8.9%), and 13.93 m (+5.6%), respectively. These results indicate that the major tree species in South Korean forests currently are more vigorous in height growth than in diameter growth when compared to the height-DBH development trends by tree species identified through past survey data.
Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.
Purpose: The balance between synthesis and degradation of proteins plays a critical role in the maintenance of skeletal muscle mass. Mitochondrial dysfunction has been closely associated with skeletal muscle atrophy caused by aging, cancer, and chemotherapy. Polygalacin D is a saponin derivative isolated from Platycodon grandiflorum (Jacq.) A. DC. This study aimed to investigate the effects of polygalacin D on myoblast differentiation and muscle atrophy in association with mitochondrial function in in vitro and in zebrafish models in vivo. Methods: C2C12 myoblasts were cultured in differentiation media containing different concentrations of polygalacin D, followed by the immunostaining of the myotubes with myosin heavy chain (MHC). The mRNA expression of markers related to myogenesis, muscle atrophy, and mitochondrial function was determined by real-time quantitative reverse transcription polymerase chain reaction. Wild type AB* zebrafish (Danio rerio) embryos were treated with 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI) with or without polygalacin D, and immunostained to detect slow and fast types of muscle fibers. The Tg(Xla.Eef1a1:mitoEGFP) zebrafish expressing mitochondria-targeted green fluorescent protein was used to monitor mitochondrial morphology. Results: The exposure of C2C12 myotubes to 0.1 ng/mL of polygalacin D increased the formation of MHC-positive multinucleated myotubes (≥ 8 nuclei) compared with the control. Polygalacin D significantly increased the expression of MHC isoforms (Myh1, Myh2, Myh4, and Myh7) involved in myoblast differentiation while it decreased the expression of atrophic markers including muscle RING-finger protein-1 (MuRF1), mothers against decapentaplegic homolog (Smad)2, and Smad3. In addition, polygalacin D promoted peroxisome proliferator-activated receptor-gamma coactivator (Pgc1α) expression and reduced the level of mitochondrial fission regulators such as dynamin-1-like protein (Drp1) and mitochondrial fission 1 (Fis1). In a zebrafish model of FOLFIRI-induced muscle atrophy, polygalacin D improved not only mitochondrial dysfunction but also slow and fast muscle fiber atrophy. Conclusion: These results demonstrated that polygalacin D promotes myogenesis and alleviates chemotherapy-induced muscle atrophy by improving mitochondrial function. Thus, polygalacin D could be useful as nutrition support to prevent and ameliorate muscle wasting and weakness.
The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.
Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.
Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
Purpose: With the aging of the population, the attack rate of osteoporotic vertebral compression fracture is in the increasing trend, and percutaneous vertebroplasty (PVP) is the most commonly performed standardized treatment. Although there is a research report of the excellence of usefulness of the SPECT/CT examination in terns of the exact diagnosis before and after the procedure, the bone cement material used in the procedure influences the image quality by forming an artifact in the CT image. Therefore, the objective of the research lies on evaluating the effect the bone cement gives to a SPECT/CT image. Materials and Methods: The images were acquired by inserting a model cement to each cylinder, after setting the background (3.6 kBq/mL), hot cylinder (29.6 kBq/mL) and cold cylinder (water) to the NEMA-1994 phantom. It was reconstructed with Astonish (Iterative: 4 Subset: 16), and non attenuation correction (NAC), attenuation correction (AC+SC-) and attenuation and scatter correction (AC+SC+) were used for the CT correction method. The mean count by each correction method and the count change ratio by the existence of the cement material were compared and the contrast recovery coefficient (CRC) was obtained. Additionally, the bone/soft tissue ratio (B/S ratio) was obtained after measuring the mean count of the 4 places including the soft tissue(spine erector muscle) after dividing the vertebral body into fracture region, normal region and cement by selecting the 20 patients those have performed PVP from the 107 patients diagnosed of compression fracture. Results: The mean count by the existence of a cement material showed the rate of increase of 12.4%, 6.5%, 1.5% at the hot cylinder of the phantom by NAC, AC+SC- and AC+SC+ when cement existed, 75.2%, 85.4%, 102.9% at the cold cylinder, 13.6%, 18.2%, 9.1% at the background, 33.1%, 41.4%, 63.5% at the fracture region of the clinical image, 53.1%, 61.6%, 67.7% at the normal region and 10.0%, 4.7%, 3.6% at the soft tissue. Meanwhile, a relative count reduction could be verified at the cement adjacent part at the inside of the cylinder, and the phantom image on the lesion and the count increase ratio of the clinical image showed a contrary phase. CRC implying the contrast ratio and B/S ratio was improved in the order of NAC, AC+SC-, AC+SC+, and was constant without a big change in the cold cylinder of the phantom. AC+SC- for the quantitative count, and AC+SC+ for the contrast ratio was analyzed to be the highest. Conclusion: It is considered to be useful in a clinical diagnosis if the application of AC+SC+ that improves the contrast ratio is combined, as it increases the noise count of the soft tissue and the scatter region as well along with the effect of the bone cement in contrast to the fact that the use of AC+SC- in the spine SPECT/CT examination of a PVP performed patient drastically increases the image count and enables a high density of image of the lesion(fracture).