It is frequently observed that consumers' behavior and performance in their weight control are greatly affected by the degree of self-control by the consumers themselves. In other words, effective weight control behavior is only possible when the consumers invest a substantial amount of endeavors and self-control. The present study empirically investigated the effect of the self-image congruence and subjective norm formed by self- concept reflected in weight control behavior on weight control attitude formation, actual behavior, and performance. For more in-depth research, rather than simply showing differences in performance based on self-control, the present study divided the subjects into high and low self-control groups for a comparative purpose. Based on empirical research employing general consumers and those who were engaged in an actual weight loss program at professional weight control centers as subjects, the study found the following results: First, for both high and low self-control groups, self-image congruence significantly affected attitude toward weight control, but not the actual weight control behavior. The results indicate that in weight control, the actual behavior must be preceded by the attitude. Second, subjective norm directly affected both attitude toward weight control, and behavior for the low self-control group while it affected the behavior only for the high self-control group. The results show that the lower self-control is, the more powerful the effect of referents is. Third, weight control attitude positively affected weight control behavior only for the high self-control group. Fourth, weight control behavior significantly affected the performance for both high and low self-control groups. Compared to the low group, the high self-control group showed more powerful effect of behavior, suggesting the crucial role of self-control in successful weight control. The results also imply that the role of referents is relatively more important for the low self-control group.
Previous research on the action effect had shown how simple action towards a stimulus can enhance the processing of that stimulus in subsequent visual search task (Buttaccio & Hahn, 2011; Weidler & Abrams, 2014). In four experiments, we investigated whether semantic representation of action word can induce the same attentional boost towards that stimulus and whether the type of action performed can modulate the action effect. In experiment 1, we replicated the same experimental paradigm displayed in previous studies. Participants were first shown an action word cue - "go" or "no". When the action cue was "go", participants were to press a designated key, but not to when the action cue was "no". Next, participants performed a visual search task, in which they reported the orientation of a tilted bar. The target could appear on top of the previously shown prime object (valid), or not (invalid). Reaction times (RTs) to the search task were measure for analysis and comparison, and the action effect had been replicated. In experiment 2, participants were instructed to respond with the keyboard for the action task, and to respond with the joystick for the visual search task. In experiment 3, participants were instructed not to press any key on the onset of prime, and then perform the visual search task to isolate the effect of semantic representation. Lastly, in experiment 4, participants were instructed to press separate keys for "go" and "no" on the onset of prime, and then perform the visual search task. Results indicate that semantic representation alone did not modulate the action effect, regardless of type of action and medium of action.
Su-Hyun Oh;Seung-Jun Kim;Sang-Ho Shin;Hong-Seok Oh;Jae-Chang Lee;Woo-Young Im;Na-Hyun Lee
Korean Journal of Psychosomatic Medicine
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v.31
no.2
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pp.165-172
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2023
Objectives : The purpose of this study is to determine whether there is a significant difference in the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio according to the history of suicide attempt in patients with psychiatric diseases. Methods : A medical record review was conducted on patients who had been hospitalized in Konyang University Hospital since 2021-03-01 to 2023-02-28 to collect demographic and clinical characteristics. T-test for continuous variables and Chi-square test for categorical variables were performed to determine demographic differences according to the history of suicide attempt, and the ANCOVA test was performed to compare the average value of peripheral inflammatory marker according to the history of suicide attempt with gender and age as covariates. One-way variance analysis was performed to determine whether the number of suicide attempt causes significant difference of the peripheral inflammatory marker. Results : The final analysis target of this study was 266 patients, 101 had history of suicide attempt, and 165 had no history of suicide attempt. The neutrophil-to-lymphocyte ratio (p<0.001) and platelet-to-lymphocyte ratio (p<0.001) were higher in patients with the history of suicide attempt than patients without the history of suicide attempt, but the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio were not significantly increased depending on the serial increase of number of suicide attempts. Conclusions : This study suggests that peripheral inflammatory markers are meaningful and easily accessible indicators for predicting the risk of suicide attempt in psychiatric patients. We expect that prospective follow-up study will be conducted with more subjects and controlled potential confounding variables.
The purpose of this research examines the factors that influence happiness among Korean adolescents by focusing on psychological resource (as measured by self-efficacy), relational resource (as measured by social support) and financial resource (as measured by family's monthly income). In addition, the influence of academic achievement on happiness is examined. To examine the influence of socio-economic status and family's monthly income, adolescents living in three different districts in Seoul (from working to middle to upper class districts) were randomly selected and interviewed in their home. A total of 190 elementary school, middle school, high school and university students (male=83, female=107) completed the resiliency of efficacy scale developed by Bandura (1995) and emotional support and happiness scale developed by the present researchers, in addition to background information. The results of the path analysis are as follows. First, the most important predictor of happiness among Korean adolescents is relational resources. In other words, emotional support received from significant others was most predictive of happiness; more than 60 times the effect of family's monthly income, three times the effect of academic achievement, and two times the effect of resiliency of efficacy. The second most important factor that predicted the happiness of Korean adolescents was psychological resource (i.e., resiliency of efficacy), which had 30 times the effect of family's monthly income. In addition resiliency of efficacy played a mediating role between emotional support on one hand and happiness on the other. Third, those respondents who had higher academic achievement reported higher levels of happiness, which had 20 times the effect of family's monthly income. Fourth, family monthly income did not predict happiness among Korean adolescents. Fifth, socio-economic status and school level did not have direct influence on happiness but had mediating influence through their influence on emotional support. In other words, those respondents with higher socio-economic status and elementary school students were more likely to receive social support from significant others, which in turn increased their happiness. These results indicate that the most important predictor of happiness among Korean adolescents is emotional support, followed by resiliency of effic acy and academic achievement, indicating that those adolescents from wealthy families are not necessarily happier.
Young Ik Lee;Ahtesham Hussain;Md Aziz Abdur Rahman;Ho Yong Sohn;Hye Jung Yoon;Jin Sook Cho
Journal of Life Science
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v.33
no.11
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pp.923-935
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2023
Rubus crataegifolius (RC), Ulmus macrocarpa (UM), and Gardenia jasminoides (GJ) are well-known folk medicines in Asia used to treat various gastrointestinal disturbances. The present study evaluated the gastroprotective effect of LS-RUG-com, a mixture of commercially prepared powders of RC, UM, and GJ with a ratio of 3:1:2(w/w/w) against HCl/ethanol-induced gastritis, indomethacin-induced ulcers, and esophageal reflux-induced esophageal mucosal damage and Helicobacter pylori infections. In addition, TNF-α and IL-1β expressions were also determined and measured in esophageal tissue. As to HCl/ethanol-induced gastritis, the LS-RUG-com treatment at a dose of 150 mg/kg showed a remarkable anti-gastritis effect. Regarding indomethacin-induced gastric ulcers, the LS-RUG-com treatment had a significant anti-gastric ulcer effect. Furthermore, in the gastroesophageal reflux disease (GERD) model experiment, the LS-RUG-com treatment resulted in the histological recovery of stomach damage and mucosal injuries. Furthermore, the LS-RUG-com treatment led to an increase in gastric content pH, an increase in mucus protection, and a decrease in gastric pepsin output with a significant decrease in TNF-α and IL-1β. As to the Helicobacter pylori infected animal model, LS-RUG-com had a notable inhibitory effect on Helicobacter growth. The use of RC, UM, or GJ in isolation or the LS-RUG-com treatment as whole had good effects in terms of anti-oxidation, anti-neutralization, gastric acid secretion inhibition, and anti-lipid peroxidation, which supported the use of natural products as systemic gastric protective agents. Our results suggest that the LS-RUG-com might be a significant systemic gastroprotective agent that could be utilized for the treatment and/or protection from gastric disturbances and related damage.
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.
This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.
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
/
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.
Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.
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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