The development of Aphidoletes aphidimyza, an aphidophagous gall midge, was studied at various constant temperatures ranging from 15 to
Sulfur dioxide (SO2) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO2 can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO2 crucial. In South Korea, SO2 monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO2 concentrations. Thus, this research estimated spatially continuous ground-level SO2 concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO2 estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO2 concentrations based on the proposed model agreed with the general seasonality of SO2 and the temporal patterns of emission sources.
The purpose of this study was to excavate the items of the comprehensive maintenance plan for scenic sites considering sustainability and analyze the needs of them. In this sense, based on 35 reports of the comprehensive maintenance plan established between 2006, when scenic sites started to be designated, and 2017, the items used in 'investigation field' and 'planning field' were examined, and then a survey regarding the needs of the items was conducted using a "5-point Likert Scale", targeting officials at 60 local governments in the whole country. Of 60 local governments, opinions from 48 officials at 45 local governments were analyzed. In order to verify the consistency of their opinions, "Reliability Analysis" was conducted, and Cronbach's alpha coefficient was 0.968 and 0.970 for 'investigation field' and 'planning field', respectively, showing high reliability. As a result of the survey, most opinions generally expressed the needs of 6 items of 'investigation field' of the comprehensive maintenance plan. Especially, the needs to investigate 'historical environment', 'natural environment', 'humanistic environment', and 'landscape' turned out to be high. In addition, as for 'general environment' and 'users', the needs of specific items such as 'distribution of main cultural properties and historic sites' (4.04) and 'acceptance of opinions from local residents and interested parties' (4.15) were found to be high. Besides, the items of 'planning field' also turned out to be needed in general (4.0). Particularly, the needs of 'enhancement of designated value and status' (4.26) and 'the comprehensive maintenance plan for designated areas of cultural properties and historic and cultural environment preservation areas' (4.25) in 'historical environment', 'maintenance of historic buildings at scenic sites' (4.28) in 'humanistic environment', and 'landscape trail planning' (4.28) in 'landscape' were found to be high. In conclusion, the practical items related to investigation and planning of the comprehensive maintenance plan for scenic sites are expected to contribute to effective conservation and management of scenic sites in the future.
The mobility and transport of radioactive cesium are crucial factors to consider for the safety assessment of high-level radioactive waste disposal sites in granite. The retardation of radionuclides in the fractured crystalline rock is mainly controlled by the hydrochemical condition of groundwater and surface reactions with minerals present in the fractures. This paper reports the experimental results of cesium sorption to the Wonju Granite, a typical Mesozoic granite in Korea, performed in an anaerobic chamber that mimics the anoxic environment of a deep disposal site. We measured the rates and amounts of cesium (133Cs) removed by crushed granite samples in different electrolyte (NaCl, KCl, and CaCl2) solutions and a synthetic groundwater solution, with variations in the initial cesium concentration (10-5, 5×10-6, 10-6, 5×10-7 M). The cesium sorption kinetic and isotherm data were successfully simulated by the pseudo-second-order kinetic model (r2= 0.99) and the Freundlich isotherm model (r2= 0.99), respectively. The sorption distribution coefficient of granite increased almost linearly with increasing biotite content in granite samples, indicating that biotite is an effective cesium scavenger. The cesium removal was minimal in KCl solution compared to that in NaCl or CaCl2 solution, regardless of the ionic strength and initial cesium concentration that we examined, showing that K+ is the most competitive ion against cesium in sorption to granite. Because it is the main source mineral of K+ in fracture fluids, biotite may also hinder the sorption of cesium, which warrants further research.
Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.
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.
Introduction As consumers' purchase behavior change into a rational and practical direction, the discount store industry came to have keen competition along with rapid external growth. Therefore as a solution, distribution businesses are concentrating on developing PB(Private Brand) which can realize differentiation and profitability at the same time. And as improvement in customer loyalty beyond customer satisfaction is effective in surviving in an environment with keen competition, PB is being used as a strategic tool to improve customer loyalty. To improve loyalty among PB users, it is necessary to develop PB by examining properties of a customer group, first of all, quality level perceived by consumers should be met to obtain customer satisfaction and customer trust and consequently induce customer loyalty. To provide results of systematic analysis on relations between antecedents influenced perceived quality and variables affecting customer loyalty, this study proposed a research model based on causal relations verified in prior researches and set 16 hypotheses about relations among 9 theoretical variables. Data was collected from 400 adult customers residing in Seoul and the Metropolitan area and using large scale discount stores, among them, 375 copies were analyzed using SPSS 15.0 and Amos 7.0. The findings of the present study followed as; We ascertained that the higher company reputation, brand reputation, product experience and brand familiarity, the higher perceived quality. The study also examined the higher perceived quality, the higher customer satisfaction, customer trust and customer loyalty. The findings showed that the higher customer satisfaction and customer trust, the higher customer loyalty. As for moderating effects between PB and NB in terms of influences of perceived quality factors on perceived quality, we can ascertain that PB was higher than NB in the influences of company reputation on perceived quality while NB was higher than PB in the influences of brand reputation and brand familiarity on perceived quality. These results of empirical analysis will be useful for those concerned to do marketing activities based on a clearer understanding of antecedents and consecutive factors influenced perceived quality. At last, discussions about academical and managerial implications in these results, we suggested the limitations of this study and the future research directions. Research Model and Hypotheses Test After analyzing if antecedent variables having influence on perceived quality shows any difference between PB and NB in terms of their influences on them, the relation between variables that have influence on customer loyalty was determined as Figure 1. We established 16 hypotheses to test and hypotheses are as follows; H1-1: Perceived price has a positive effect on perceived quality. H1-2: It is expected that PB and NB would have different influence in terms of perceived price on perceived quality. H2-1: Company reputation has a positive effect on perceived quality. H2-2: It is expected that PB and NB would have different influence in terms of company reputation on perceived quality. H3-1: Brand reputation has a positive effect on perceived quality. H3-2: It is expected that PB and NB would have different influence in terms of brand reputation on perceived quality. H4-1: Product experience has a positive effect on perceived quality. H4-2: It is expected that PB and NB would have different influence in terms of product experience on perceived quality. H5-1: Brand familiarity has a positive effect on perceived quality. H5-2: It is expected that PB and NB would have different influence in terms of brand familiarity on perceived quality. H6: Perceived quality has a positive effect on customer satisfaction. H7: Perceived quality has a positive effect on customer trust. H8: Perceived quality has a positive effect on customer loyalty. H9: Customer satisfaction has a positive effect on customer trust. H10: Customer satisfaction has a positive effect on customer loyalty. H11: Customer trust has a positive effect on customer loyalty. Results from analyzing main effects of research model is shown as