In NPP (nuclear power plant), boric acid is used as a neutron absorbent. So radioactive boric acid waste are generated from various waste streams such as discharge or leakage of reactor coolant water, floor drains, drainage of equipment for operation or maintenance, reactor letdown flows and etc. Depending on KHNP, 20,015 drum (200 L drum) of concentrated boric acid waste were stored in KOREA NPP until 2019. In previous study, our group suggested the waste upcycling process synthesizing B4C neutron absorber using boric acid waste and activated carbon waste to innovatively reduce radioactive wastes. Radioactive activated carbon waste was utilized in off gas treatment system of NPP to capture nuclide such as I-131, C-14 and H-3. Activated carbon waste is treated as low-level radioactive waste and pre-treatment system for removing nuclide from the activated carbon waste is needed to use B4C up-cycling process. In this study, microwave treatment system is suggested to treat the activated carbon waste. Activated carbon waste was exposed to microwave for a few minutes and temperature of the waste was dramatically increased over 400°C. Nuclide in the activated carbon waste were selectively removed from the waste without massive production of secondary off gas waste.

Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

In NPP (nuclear power plant), boric acid is used as a neutron absorbent. So radioactive boric acid waste are generated from various waste streams such as discharge or leakage of reactor coolant water, floor drains, drainage of equipment for operation or maintenance, reactor letdown flows and etc. Depending on KHNP, 20,015 drum (200 L drum) of concentrated boric acid waste were stored in KOREA NPP until 2019. In previous study, our group suggested the waste up-cycling process synthesizing B4C neutron absorber using boric acid waste and activated carbon waste to innovatively reduce radioactive wastes. Radioactive activated carbon waste was utilized in off gas treatment system of NPP to capture nuclide such as I-131, C-14 and H-3. Activated carbon waste is treated as low-level radioactive waste and pre-treatment system for removing nuclide from the activated carbon waste is needed to use B4C up-cycling process. In this study, microwave treatment system is suggested to treat the activated carbon waste. Activated carbon waste was exposed to microwave for a few minutes and temperature of the waste was dramatically increased over 400°C. Nuclide in the activated carbon waste were selectively removed from the waste without massive production of secondary off gas waste.

Mesenchymal stem cell (MSC) based cell therapy has emerged as a promising therapeutic approach for treatment of several degenerative, infectious and non-infectious diseases. Numerous studies have demonstrated the remarkable immunosuppressive and antibacterial effects of MSCs both in vitro and in vivo, in animal models and in humans. However, the antibacterial effects of MSCs rely heavily on their paracrine factors rather than direct cell-to-cell contact and the effect is specific to disease and site of infection or injury. Furthermore, recent studies have demonstrated the double-edged sword effect of MSCs in bacterial infectious diseases. Despite their inherent potential for repair of damaged tissues, immunosuppression, and alleviation of various autoimmune as well as infectious diseases, MSCs also play a critical role in promoting persistent bacterial infection and disease progression. Therapeutic administration of MSCs successfully inhibited the bacterial growth and enhances survival by improved clearance of pathogenic bacteria in sepsis and pneumonic conditions. However, due to their abnormal transformation, they assist in long lasting survival and persistent infection of Mycobacterium tuberculosis (M. tuberculosis) and may also be responsible for progression of gastric cancer. This review focuses on recent advances that have broadened our understanding of MSC based therapy for bacterial diseases and provides new insight into the possible therapeutic targets of fatal bacterial diseases.

본 연구는 다목적함수를 고려한 입자군집최적화(Particle Swarm Optimization, PSO) 알고리즘을 Python으로 개발하고, Soil and Water Assessment Tool (SWAT) 모형에 적용하여 자동보정 알고리즘의 적용 가능성을 평가하였다. SWAT 모형의 유출 해석은 안성천의 공도 수위 관측소 상류유역(364.8 km2)을 대상으로 하였으며, 공도 지점의 2000년부터 2015년까지의 일 유량 자료를 이용하였다. PSO 자동보정은 결정계수 (coefficient of determination, R2), 평균제곱근오차(RMSE), NSE 모형효율계수(Nash-Sutcliffe Efficiency, NSEQ), 특히 중간유출과 기저유출의 보정을 위해 NSEINQ (Inverse Q)를 활용하여 SWAT을 보정하였다. PSO을 통한 SWAT 모형의 자동보정과 수동보정의 유출해석 결과, 각각 R2 는 0.64, 0.55, RMSE는 0.59, 0.58, NSEQ는 0.78, 0.75, NSEINQ는 0.45, 0.09의 상관성 분석결과를 보였다. PSO 자동보정 알고리즘은 수동보정에 비하여 높은 향상을 보였는데 특히 유출의 감수곡선을 개선시켰으며 적절한 매개변수 추가(RCHRG_DP)와 매개변수 범위의 설정으로 수동 보정의 한계를 보완하였다.

In order to uncover gene regulatory networks clustering of co-expressing genes was performed using a rice micorarray dataset of 155 gene expression omnibus sample (GSM) plates in NCBI, generating a total of 1660 clusters. One cluster with 85 co-expressing genes was measured with the correlation coefficient between pairs, resulting in an average r value of 0.66 with a range of -0.08 to 0.98. This result might support the notion that genes included in each cluster play common functional role(s). We also retrieved 23 Affymetrix GeneChip spots IDs corresponding to each of candidate genes related to abiotic stresses obtained from the P1antQTL-GE database and subsequently detected 23 clusters including co-expressing genes with each of the genes. Expression profiles of co-expressing genes revealed some degree of tissue-specific expression patterns, probably reflecting the existence of, at least partial, parallel versions of stress-related networks with evolutionary process, such as subfuntionalization. The finding that several cis-elements related to abiotic stresses was detected by differences in frequency between co-expressing genes and randomly selected genes. Clustering, expression profiles, and putative cis-acting regulatory elements of co-expressing genes related to abiotic stresses may provide clues to shed further light on the gene regulatory network of stress-responsive pathway.

This study estimate the degree of contamination in the streamwater around the Sudokwon landfill site. It was sampled at 10 sites in Jan., Apr., Jul. and Oct., 1996. There were analyzed five kinds of toxic chemical material-CN, ABS, PCB, As, Org-P, and four kinds of heavy metal-Pb, Hg, Cd, C_r^+6. The result are 1)The COD was generally increased to compare before landfill, 2)The Org-P and PCB were not detected at all points, 3)The concentrations of Pb, C_r^+6 and As were lower than the environmental criteria values, 4)The CN, Hg and Cd were over envirommental criteria values, and so emergent regulation is needed, 5)The effects of the streamwater contamination were not only the leachate of the landfill, but also the small factories and agricultural land around the landfill.

In order to analyze the water quality variation of surface water around the Sudokwon landfill site, seasonal variations of water temperature, pH, DO, BOD, COD, SS, NH_3-N. NO_2-N, and NO_3-N were examined at 10 sites from January to December, 1996. It was found that the estimates of COD, DO, SS, and NH_3-N were increased compared with the results of environmental impact assessment carried out in 1988. Higher estimates of COD, DO, and SS were due to industrial and agricultural wastewater, and the increase of NH_3-N at Jangdo reservoir site was due to the leachate from the landfill. In particular, the estimate of SS was found to be increased by the soil wash from the landfill during the heavy rainy days.