This study is to quantify α-quartz, cristobalite and kaolinite using by FTIR in respirable dust generated in the mining workplace. Various minerals in mines can interfere with peaks when quantifying respirable crystalline silica by FTIR. Therefore, for accurate quantification, it is necessary to remove interfering substances or correct the peaks that cause interference. To confirm the peaks occurring in α-quartz, cristobalite and kaolinite, each standard material was diluted with KBr and scanned in the range of 400 cm-1 to 4000 cm-1 using by FTIR. As a result of scanning the analytes, it was decided to use the peaks of 797.66 cm-1 and 695.25 cm-1 for α-quartz, 621.58 cm-1 for cristobalite, and 3696.47 cm-1 for kaolinite. When the above materials are mixed, interference occurs at the peak for quantification, which is corrected by the calculation formula. The analysis of the mixture of α-quartz and cristobalite shows the average bias (%) of 2.64 (corrected) at α-quartz (797.66 cm-1), 5.61 (uncorrected) at α-quartz (695.25 cm-1) and 1.51 (uncorrected) at cristobalite (621.58 cm-1). The analysis of the mixture of α-quartz and kaolinite shows the average bias(%) of 1.79(corrected) at α-quartz (797.66 cm-1), 3.92 (corrected) at α-quartz (695.25 cm-1) and 2.58 (uncorrected) at kaolinite (3696.47 cm-1). The analysis of the mixture of cristobalite and kaolinite shows the average bias (%) of 2.15 (corrected) at cristobalite (621.58 cm-1), 4.32 (uncorrected) at kaolinite (3696.47 cm-1). The analysis of the mixture of αquartz and cristobalite and kaolinite shows the average bias (%) of 1.93(corrected) at α-quartz (797.66 cm-1), 6.47 (corrected) at α-quartz (695.25 cm-1) and 1.77 (corrected) at cristobalite (621.58 cm-1) and 2.61 (uncorrected) at kaolinite (3696.47 cm-1). The experimental results showed that the deviation caused by peak interference by two or three substances could be corrected to less than 6 % of the average deviation. This study showed the possibility of correcting and quantifying when various interfering substances that are difficult to remove are mixed.
The benzo[a]pyrene in edible oils is extracted using methods such as Liquid-liquid, soxhlet and ultrasound-assisted extraction. However these extraction methods have significant drawbacks, such as long extraction time and large amount of solvent usage. To overcome these drawbacks, this study attempted to improve the current complex benzo[a]pyrene analysis method by applying the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method that can be analyzed in a simple and short time. The QuEChERS method applied in this study includes extraction of benzo[a]pyrene into n-hexane saturated acetonitrile and n-hexane. After extraction and distribution using magnesium sulfate and sodium chloride, benzo[a]pyrene is analyzed by liquid chromatography with fluorescence detector (LC/FLR). As a result of method validation of the new method, the limit of detection (LOD) and quantification (LOQ) were 0.02 ㎍/kg and 0.05 ㎍/kg, respectively. The calibration curves were constructed using five levels (0.1~10 ㎍/kg) and coefficient (R2) was above 0.99. Mean recovery ratio was ranged from 74.5 to 79.3 % with a relative standard deviation (RSD) between 0.52 to 1.58 %. The accuracy and precision were 72.6~79.4 % and 0.14~7.20 %, respectively. All results satisfied the criteria ranges requested in the Food Safety Evaluation Department guidelines (2016) and AOAC official method of analysis (2023). Therefore, the analysis method presented in this study was a relatively simple pretreatment method compared to the existing analysis method, which reduced the analysis time and solvent use to 92 % and 96 %, respectively.
Jintaek Kang;Chiung Ko;Jeongmuk Park;Jongsu Yim;Sun-Jeong Lee;Myoungsoo Won
Journal of Korean Society of Forest Science
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v.112
no.4
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pp.472-489
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2023
This study was conducted to derive the optimal estimation equations for deriving the green and dry weights of Larix kaempferi (Japanese larch) and Pinus rigida (Rigida pine), which are major coniferous tree species in South Korea. The equations were then used to develop weight tables. Table development began with the sampling of 150 L. kaempferi and 90 P. rigida trees distributed throughout the national scale, after which green weights were measured on-site. Samples from each stand were then collected, and their dry weights were measured in a laboratory. The equation used to calculate green and dry weights was divided into a one-variable formula that uses only the diameter at breast height (DBH) and a two-variable equation that employs DBH and height. The equations used to estimate the green and dry weights of logs were divided into one- and two-variable equations using DBH. Statistical data, such as the fitness index (FI), root mean square error, standard error of estimation, and residual diagram, were used to verify the suitability of the estimation equations. Applicability was examined by calculating weights using the derived optimal equations. The equation W = bD+cD2 was used in measurements involving only DBH, whereas the equation W = aDbHc was employed in cases involving both diameter and height at breast height. The FI of W = bD+cD2 was 0.91, while that of W = aDbHc was 0.95, both of which are high values. With these estimation formulas, weight tables for the green and dry weights of L. kaempferi and P. rigida were prepared and compared with weight tables created 20 years ago. The green and dry weight tables of both species were larger.
Suyoung Jung;Kwangsoo Lee;Hyunsoo Kim; Joonhyung Park;Jaeyeop Kim;Chunhee Park;Yeongmo Son
Journal of Korean Society of Forest Science
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v.112
no.4
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pp.417-425
/
2023
The aim of this study was to derive stem taper equations for Quercus acuta, one of main evergreen broad-leaved tree species found in warm temperate regions, and to prepare a stem volume table using those stem taper equations. A total of 688 individual trees were used in the analysis, which were collected from Jeonnam-do, Gyeongnam-do, and Jeju-do. The stem taper models applied to derive the stem curve pattern were the Max and Burkhart, Kozak, and Lee models. Among the three stem taper models, the best explanation of the stem curve shape of Q. acuta was found to be given by the Kozak model, which showed a fitness index of 0.9583, bias of 0.0352, percentage of estimated standard error of 1.1439, and mean absolute deviation of 0.6751. Thus, the stem taper of Q. acuta was estimated using the Kozak model. Moreover,thestemvolumecalculationwasperforme d by applying the Smalian formula to the diameter and height of each stem interval. In addition, an analysis of variance (ANOVA) was conducted to compare the two existing Q. acuta stem volume tables (2007 and 2010) and the newly created stem volume table (2023). This analysis revealed that the stem volume table constructed in the Wando region in 2007 included about twice as much as the stem volume tables constructed in 2010 and 2023. The stem volume table (2023) developed in this study is not only based on the regional collection range and number of utilized trees but also on a sound scientific basis. Therefore, it can be used at the national level as an official stem volume table for Q. acuta.
Forest fires are becoming more frequent and larger around the world due to climate change. Remote sensing such as satellite images can be used as an alternative or assistance data because it reduces various difficulties of field survey. Forest burn severity (differenced normalized burn ratio, dNBR) is calculated through the difference in normalized burn ratio (NBR) before and after a forest fire. The images used in the NBR formula are based on Landsat's near-infrared (NIR) and short-wavelength infrared (SWIR) bands. South Korea's satellite images don't have a SWIR band. So domestic studies related to forest burn severity calculated dNBR using overseas images or indirectly using the normalized difference vegetation index (NDVI) using South Korea's satellite images. Therefore, in this study, dNBR was calculated by substituting the mid-wavelength infrared (MWIR) band of Kompsat-3A (K3A) instead of the SWIR band in the NBR formula. The results were compared with the dNBR results obtained through Landsat which is the standard for dNBR formula. As a result, it was shown that dNBR using K3A's MWIR band has a wider range of values and can be expressed in more detail than dNBR using Landsat's SWIR band. Therefore, it is considered that K3A images will be highly useful in surveying burn areas and severity affected by forest fires. In addition, this study used the K3A's MWIR band images degraded to 30 m. It is considered that much better results will be obtained if a higher-resolution MWIR band is used.
The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R2), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R2 and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.
The HR policy in the public sector was closed and operated mainly on written tests, but in 2006, a new evaluation, promotion and education system based on competence was introduced in the promotion and selection system of civil servants. In particular, the seniority-oriented promotion system was evaluated based on competence by operating an Assessment Center related to promotion. Competency evaluation is known to be the most reliable and valid evaluation method among the evaluation methods used to date and is also known to have high predictive feasibility for performance. In 2001, 19 government standard competency models were designed. In 2006, the competency assessment was implemented with the implementation of the high-ranking civil service team system. In the public sector, the purpose of the competency evaluation is mainly to select third-grade civil servants, assign fourth-grade civil servants, and promotion fifth-grade civil servants. However, competency assessments in the public sector differ in terms of competency assessment objectives, assessment processes and competency assessment programmes compared to those in the private sector. For the purposes of competency assessment, the public sector is for the promotion of candidates, and the private sector focuses on career development and fostering. Therefore, it is not continuously developing capabilities than the private sector and is not used to enhance performance in performing its duties. In relation to evaluation items, the public sector generally operates a system that passes capacity assessment at 2.5 out of 5 for 6 competencies, lacks feedback on what competencies are lacking, and the private sector uses each individual's competency score. Regarding the selection and operation of evaluators, the public sector focuses on fairness in evaluation, and the private sector focuses on usability, which is inconsistent with the aspect of developing capabilities and utilizing human resources in the right place. Therefore, the public sector should also improve measures to identify outstanding people and motivate them through capacity evaluation and change the operation of the capacity evaluation system so that they can grow into better managers through accurate reports and individual feedback
In study, we investigated changes on growth and chlorophyll concentration on sprouted barley by fractionated X-ray irradiation (FXI). Group was divided into the control group (CG), 1-time irradiation group (30 Gy once), 2-time irradiation group (15 Gy 2 times), and 3-time irradiation group (10 Gy 3 times), and 20 grains were used per group. Experimental group (EG) was exposed by using linear accelerator (Clinac IS, VERIAN, USA), by 6 MV X-ray, SSD 100 cm, 18×10 cm2, 600 MU/min. Length was measured every day until 9th day, and chlorophyl was analyzed using spectrophotometer(uv-1800, shimadzu, japan) in 9th day. Data analysis was performed the One-way ANOVA using SPSS ver 26.0(Chicago, IL, USA). In the pre-germination irradiation group (Pre-GIG), the CG had greater length than the EG on all measurement days, and as the number of FXI increased, the length became shorter. In the post-germination irradiation group (Post-GIG), the length of the CG was statistically significantly greater than that of the EG on all measurement days, and as the number of FXI increased, the length also became longer. The chlorophyll concentration was higher in the Post-GIG than in the Pre-GIG, and chlorophyll concentrations of EG was higher in the Pre-GIG than in the CG, as well as and Post-GIG. In addition, the smaller the number of FXI, the higher the chlorophyll concentration in both groups. FXI was found to affect the growth and chlorophyll concentration of sprouted barley.
DNA barcoding without assessing reliability and validity causes taxonomic errors of species identification, which is responsible for disruptions of their conservation and aquaculture industry. Although DNA barcoding facilitates molecular identification and phylogenetic analysis of species, its availability in clariid catfish lineage remains uncertain. In this study, DNA barcoding was developed and validated for clariid catfish. 2,970 barcode sequences from mitochondrial cytochrome c oxidase I (COI) and cytochrome b (Cytb) genes and D-loop sequences were analyzed for 37 clariid catfish species. The highest intraspecific nearest neighbor distances were 85.47%, 98.03%, and 89.10% for COI, Cytb, and D-loop sequences, respectively. This suggests that the Cytb gene is the most appropriate for identifying clariid catfish and can serve as a standard region for DNA barcoding. A positive barcoding gap between interspecific and intraspecific sequence divergence was observed in the Cytb dataset but not in the COI and D-loop datasets. Intraspecific variation was typically less than 4.4%, whereas interspecific variation was generally more than 66.9%. However, a species complex was detected in walking catfish and significant intraspecific sequence divergence was observed in North African catfish. These findings suggest the need to focus on developing a DNA barcoding system for classifying clariid catfish properly and to validate its efficacy for a wider range of clariid catfish. With an enriched database of multiple sequences from a target species and its genus, species identification can be more accurate and biodiversity assessment of the species can be facilitated.
Sejeong Bae ;Bokyung Son ;Taejun Sung ;Yeonsu Lee ;Jungho Im ;Yoojin Kang
Korean Journal of Remote Sensing
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v.39
no.5_3
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pp.1009-1029
/
2023
Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R2 of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R2 of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.
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