• Journal of Korean Society of Disaster and Security
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• v.14 no.1
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• pp.9-21
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• 2021

Recently, the importance of eco-friendly power generation facility using renewable energy has newly appeared. Hydropower plant is a very important source of electricity generation and supply which is very important to secure safety because it is commonly connected with multi facility and operated on a large scale. In this study, a scenario-based analysis method was suggested to assess vulnerability of a penstock system caused by water hammer commonly occurred in the operation of hydropower plants. A hypothetical hydropower plant was used to demonstrate the applicability of a transient analysis model. In order to verify reliability of the model, the prediction of pressure behaviors were compared with the results of commercial model (SIMSEN) and measured data, then a real hydroelectric power plant was applied to develop all potential water hammer scenarios during the actual operation. The scenario-based simulation and vulnerability assessment for water hammer in the penstock system were performed with internal and external load conditions. The simulation results indicated that the vulnerability of a penstock system was varied with the operating conditions of hydropower facilities and significantly affected by load combination consisting of different load scenarios. The proposed numerical method could be an useful tool for the vulnerabilityty assessment of the hydropower plants due to water hammer.

• Journal of Bio-Environment Control
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• v.32 no.3
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• pp.181-189
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• 2023

Hydrogen has gained attention as an environmentally friendly energy source among various renewable options, however, its application in agriculture remains limited. This study aims to apply the hydrogen fuel cell triple heat-combining system, originally not designed for greenhouses, to greenhouses in order to save energy and reduce greenhouse gas emissions. This system can produce heating, cooling, and electricity from hydrogen while recovering waste heat. To implement a hydrogen fuel cell triple heat-combining system in a greenhouse, it is crucial to evaluate the greenhouse's heating and cooling load. Accurate analysis of these loads requires considering factors such as greenhouse configuration, existing heating and cooling systems, and specific crop types being cultivated. Consequently, this study aimed to estimate the cooling and heating load using building energy simulation (BES). This study collected and analyzed meteorological data from 2012 to 2021 for semi-enclosed greenhouses cultivating tomatoes in Jeonju City. The covering material and framework were modeled based on the greenhouse design, and crop energy and soil energy were taken into account. To verify the effectiveness of the building energy simulation, we conducted analyses with and without crops, as well as static and dynamic energy analyses. Furthermore, we calculated the average maximum heating capacity of 449,578 kJ·h^-1 and the average cooling capacity of 431,187 kJ·h^-1 from the monthly maximum cooling and heating load analyses.

• Journal of Plant Biotechnology
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• v.33 no.3
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• pp.195-207
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• 2006

Stem cells are the primordial, initial cells which usually divide asymmetrically giving rise to on the one hand self-renewals and on the other hand progenitor cells with potential for differentiation. Zygote (fertilized egg), with totipotency, deserves the top-ranking stem cell - he totipotent stem cell (TSC). Both the ICM (inner cell mass) taken from the 6 days-old human blastocyst and ESC (embryonic stem cell) derived from the in vitro cultured ICM have slightly less potency for differentiation than the zygote, and are termed pluripotent stem cells. Stem cells in the tissues and organs of fetus, infant, and adult have highly reduced potency and committed to produce only progenitor cells for particular tissues. These tissue-specific stem cells are called multipotent stem cells. These tissue-specific/committed multipotent stem cells, when placed in altered environment other than their original niche, can yield cells characteristic of the altered environment. These findings are certainly of potential interest from the clinical, therapeutic perspective. The controversial terminology 'somatic stem cell plasticity' coined by the stem cell community seems to have been proved true. Followings are some of the recent knowledges related to the stem cell. Just as the tissues of our body have their own multipotent stem cells, cancerous tumor has undifferentiated cells known as cancer stem cell (CSC). Each time CSC cleaves, it makes two daughter cells with different fate. One is endowed with immortality, the remarkable ability to divide indefinitely, while the other progeny cell divides occasionally but lives forever. In the cancer tumor, CSC is minority being as few as 3-5% of the tumor mass but it is the culprit behind the tumor-malignancy, metastasis, and recurrence of cancer. CSC is like a master print. As long as the original exists, copies can be made and the disease can persist. If the CSC is destroyed, cancer tumor can't grow. In the decades-long cancer therapy, efforts were focused on the reducing of the bulk of cancerous growth. How cancer therapy is changing to destroy the origin of tumor, the CSC. The next generation of treatments should be to recognize and target the root cause of cancerous growth, the CSC, rather than the reducing of the bulk of tumor, Now the strategy is to find a way to identify and isolate the stem cells. The surfaces of normal as well as the cancer stem cells are studded with proteins. In leukaemia stem cell, for example, protein CD 34 is identified. In the new treatment of cancer disease it is needed to look for protein unique to the CSC. Blocking the stem cell's source of nutrients might be another effective strategy. The mystery of sternness of stem cells has begun to be deciphered. ESC can replicate indefinitely and yet retains the potential to turn into any kind of differentiated cells. Polycomb group protein such as Suz 12 repress most of the regulatory genes which, activated, are turned to be developmental genes. These protein molecules keep the ESC in an undifferentiated state. Many of the regulator genes silenced by polycomb proteins are also occupied by such ESC transcription factors as Oct 4, Sox 2, and Nanog. Both polycomb and transcription factor proteins seem to cooperate to keep the ESC in an undifferentiated state, pluripotent, and self-renewable. A normal prion protein (PrP) is found throughout the body from blood to the brain. Prion diseases such as mad cow disease (bovine spongiform encephalopathy) are caused when a normal prion protein misfolds to give rise to PrP$^{SC}$ and assault brain tissue. Why has human body kept such a deadly and enigmatic protein? Although our body has preserved the prion protein, prion diseases are of rare occurrence. Deadly prion diseases have been intensively studied, but normal prion problems are not. Very few facts on the benefit of prion proteins have been known so far. It was found that PrP was hugely expressed on the stem cell surface of bone marrow and on the cells of neural progenitor, PrP seems to have some function in cell maturation and facilitate the division of stem cells and their self-renewal. PrP also might help guide the decision of neural progenitor cell to become a neuron.

• Journal of Animal Environmental Science
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• v.16 no.3
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• pp.205-215
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• 2010

Geothermal heat pump system (GHPS) is an energy-efficient technology that use the relatively constant and renewable energy stored in the earth to provide heating and cooling. With the aim of using GHPS as a heating source, it's possibilities of application in farrowing house were examined by measuring environmental assessment and sow's performance. A total of 96 sows were assigned to 2 pig housings (GHPS and conventional housing) with 48 for four weeks in winter season. During the experimental period, indoor maximum temperature in GHPS-housing was measured up to $26.7^{\circ}C$, average temperature could maintain $21.2^{\circ}C$. The mean value of dust levels and $CO_2$, $NH_3$ and $H_2S$ gas emissions were decreased in GHPS-housing compare with those of conventional housing. Litter size, birth weight, parity and weaning weight did not differ between housings. However, feed intake of sow in GHPS-housing was lower than that of conventional housing. In energy consumption for heating, electric power consumption increased in GHPS-housing than the conventional housing, a 2,250 kwh increase, whereas there is no fuel usage for heater in GHPS-housing. Amount of ground water circulated for heating in cold weather for earth heat exchanger was 8.4-12.9 ton per day. In conclusion, GHPS may have environmental benefits and effectiveness of heating in farrowing housing and affect the performance in sows.

• Applied Chemistry for Engineering
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• v.30 no.2
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• pp.226-232
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• 2019

The biological wastewater treatment is more eco-friendly and can be used effectively in wastewater for a variety of purposes than that of the conventional treatment. In particular, the wastewater treatment using microalgae in biological treatment processes has attracted great attention due to its ability to remove economically nutrients from wastewater and have many advantages as a renewable energy source. This study was investigated to establish the optimal growth conditions for microalga Scenedesmus obliquus. Additionally, the removal efficiencies of nutrients (N, P) and heavy metals (Cu, Zn) from the synthetic wastewater were evaluated. As a results, the optimal growth conditions were established at $28^{\circ}C$, pH 7, and light and dark cycle of 14 : 10 h. In the evaluation of nutrient removal efficiencies at each concentrations of 500, 1,000, 5,000, and 10,000 mg/L, the removal rates were 17.6~70% N and 8.4~34% P in the single treatment and 12.0~58.0% N and 3.0~40.3% P in the binary mixture treatment. In addition, the evaluation of heavy metal removal efficiencies at each concentrations of 10, 30 and 50 mg/L, the removal rates were 13.7~40.3% Cu and 10.0~30.0% Zn in the single treatment and 16.0~40.0% Cu and 12.0~20.0% Zn in the binary mixture treatment. Based on the results of the study, it appears that Scenedesmus obliquus can be used for the removal of nutrients and heavy metals from the swine wastewater.

• Clean Technology
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• v.27 no.1
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• pp.1-8
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• 2021

Due to the negative impacts of microplastics (MPs) on the ecosystem, the investigation of its occurrence and its treatment from sewage and wastewater treatment plants (WWTPs) have received a lot of attention in the recent years. Most MPs are precipitated and removed with the sludge during the treatment process. Proper sludge management is immensely necessary to avoid MP exposure in the environment. However, the domestic research on this aspect is limited. This study reviews appropriate sludge management approaches to decrease environmental MP exposure. This can be achieved through investigating sludge generation and treatment, regulation laws and government policy trends with an emphasis on WWTPs. The ratio of sludge in sewage treatment plants has been observed to be highest in recycling followed by incineration and landfills. Recycling is the highest in fuel followed by construction materials and composting. For WWTPs, the highest ratio is in recycling followed by fuel and landfills, and recycling is confirmed in the following order: incineration > after composting > after solidification > earthworm breeding. Treatment approaches that can increase the exposure of MPs to the ecosystem are considered to be used in landfills and agricultural fields. However, this method is not appropriate given the insufficient capacity of domestic landfills and the sufficient supply of existing chemical and animal manure fertilizers. Instead, it would be rational in terms of environmental preservation to expand the use of fuel and energy in connection with the new and renewable energy policy, and to actively seek the use of sub-materials for construction materials. In order to secure the basic data for the effectiveness of future planning and revision of related laws, it is required to perform an in-depth investigation of the sludge supply and demand status along with the environmental and economic effects.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• Korean journal of applied entomology
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• v.61 no.4
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• pp.605-614
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• 2022

Two major problems currently threaten human survival on Earth: climate change and the rapid aging of the population in developed countries. Climate change is a result of the increase in greenhouse gas (GHG) concentrations in the atmosphere due to the increase in the use of fossil fuels owing to economic and transportation development. The rapid increase in the age of the population is a result of the rise in life expectancy due to the development of biomedical science and technology and the improvement of personal hygiene in developed countries. To avoid irreversible global climate change, it is necessary to quickly transition from the current fossil fuel-based economy to a zero-carbon renewable energy-based economy that does not emit GHGs. To achieve this goal, the dairy and livestock industry, which generates the most GHGs in the agricultural sector, must transition to using low-carbon emission production methods while simultaneously increasing consumers' preference for low-carbon diets. Although 77% of currently available arable land globally is used to produce livestock feed, only 37% and 18% of the proteins and calories that humans consume come from dairy and livestock farming and industry. Therefore, using edible insects as a protein source represents a good alternative, as it generates less GHG and reduces water consumption and breeding space while ensuring a higher feed conversion rate than that of livestock. Additionally, utilizing the functionality of medicinal insects, such as silkworms, which have been proven to have certain health enhancement effects, it is possible to develop functional foods that can prevent or delay the onset of currently incurable degenerative diseases that occur more frequently in the elderly. Insects are among the first animals to have appeared on Earth, and regardless of whether humans survive, they will continue to adapt, evolve, and thrive. Therefore, the use of various edible and medicinal insects, including silkworms, in industry will provide an important foundation for human survival and prosperity on Earth in the near future by resolving the current two major problems.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.41-50
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• 2024

Plant Microbial Fuel Cells (P-MFCs) are biomass-based energy technologies that generate electricity from plant and root microbial communities and are suitable for natural fundamental solutions considering sustainable environments. In order to develop P-MFC technology suitable for domestic waterfront space, it is necessary to analyze international research trends first. Therefore, in this study, 700 P-MFC-related research papers were investigated in Web of Science, and the core keywords were derived using VOSviewer, a word analysis program, and the research trends were analyzed. First, P-MFC-related research has been on the rise since 1998, especially since the mid to late 2010s. The number of papers submitted by each country was "China," "U.S." and "India." Since the 2010s, interest in P-MFCs has increased, and the number of publications in the Philippines, Ukraine, and Mexico, which have abundant waterfront space and wetland environments, is increasing. Secondly, from the perspective of research trends in different periods, 1998-2015 mainly carried out microbial fuel cell performance verification research in different environments. The 2016-2020 period focuses on the specific conditions of microbial fuel cell use, the structure of P-MFC and how it develops. From 2021 to 2023, specific research on constraints and efficiency improvement in the development of P-MFC was carried out. The P-MFC-related international research trends identified through this study can be used as useful data for developing technologies suitable for domestic waterfront space in the future. In addition to this study, further research is needed on research trends and levels in subsectors, and in order to develop and revitalize P-MFC technologies in Korea, research on field applicability should be expanded and policies and systems improved.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.