• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.324-333
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• 2023

Background: Human exposure to phthalates in indoor environments occurs via dermal absorption, oral ingestion of indoor dust, and inhalation of indoor air. However, systematic studies to investigate the exposure rate to phthalates among the three exposure routes in indoor environments are currently limited. Objectives: A theoretical exposure ratio between inhalation and oral exposure was calculated based on the total amount of di(2-ethyl-hexyl) phthalate (DEHP) emitted into indoor air and deposited into floor dust in a test house. Methods: Flooring and wallpaper containing DEHP were installed in a test house and the concentration of DEHP in both indoor air and floor dust were monitored for five months. Based on the measured DEHP concentrations, the theoretical total amount ratio of DEHP that could be exposed through inhalation and oral ingestion was calculated. Results: Considering the period of operation in the test house, the theoretical total amount of DEHP through inhalation and oral ingestion exposures in the entire test house space was calculated to be 0.014 mg and 5.5 mg, respectively. The exposure ratio of the two routes between inhalation and oral exposure corresponding to the total DEHP amount in flooring and wallpaper was 6.0×10^-7% and 2.3×10^-4%, indicating that theoretical oral exposure to DEHP is approximately 380 times higher than inhalation. Conclusions: Monitoring results from a test house has shown that oral exposure is the main exposure route for DEHP in indoor environments. The experimental design employed in this study and theoretical exposure ratio obtained can be applied to investigate actual exposure to DEHP and to determine the exposure characteristics of various types of semi-volatile organic compounds.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.459-471
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• 2023

This study identified the characteristics of changes in forest areas of North Korea's major regions (Gaesong, Goseong, Pyongyang, and Hyesan·Samsu) using data on degraded lands collected via monitoring by the National Institute of Forest Science. The data, spanning 1999 to 2018, were cross-analyzed to determine trends in land cover change, and hotspot analysis was conducted to confirm evident changes in the forest areas. The results showed that the areas of interest substantially transitioned to other land use types from 1999 to 2008. Contrastingly, the range of changes decreased from 2008 to 2018, with some areas regenerating into forests. Nevertheless, the hotspot analysis indicated that hotspots occurred more intensively in the outskirts of cities and forest edges from 2008 to 2018 than from 1999 to 2008. The analysis also showed that the aforementioned changes were caused by various aspects, depending on regional characteristics and social factors. This study can be used as a basic reference for decision-making on the selection of basic forest restoration targets and restoration methods in inter-Korean forest cooperation initiatives.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1111-1123
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• 2023

In recent times, semantic image segmentation methods using deep learning models have been widely used for monitoring changes in surface attributes using remote sensing imagery. To enhance the performance of various UNet-based deep learning models, including the prominent UNet model, it is imperative to have a sufficiently large training dataset. However, enlarging the training dataset not only escalates the hardware requirements for processing but also significantly increases the time required for training. To address these issues, transfer learning is used as an effective approach, enabling performance improvement of models even in the absence of massive training datasets. In this paper we present three transfer learning models, UNet-ResNet50, UNet-VGG19, and CBAM-DRUNet-VGG19, which are combined with the representative pretrained models of VGG19 model and ResNet50 model. We applied these models to building extraction tasks and analyzed the accuracy improvements resulting from the application of transfer learning. Considering the substantial impact of learning rate on the performance of deep learning models, we also analyzed performance variations of each model based on different learning rate settings. We employed three datasets, namely Kompsat-3A dataset, WHU dataset, and INRIA dataset for evaluating the performance of building extraction results. The average accuracy improvements for the three dataset types, in comparison to the UNet model, were 5.1% for the UNet-ResNet50 model, while both UNet-VGG19 and CBAM-DRUNet-VGG19 models achieved a 7.2% improvement.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.726-734
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• 2023

Objective : Chronic subdural hematoma (CSDH) patients using antithrombotic agents (AT) at high risk for cardiovascular disease are increasing. The authors aimed to analyze the factors influencing outcome by targeting patients using AT and to establish a desirable treatment strategy. Methods : A retrospective analysis was performed on data from 462 patients who underwent burr hole trephination (BHT) surgery for CSDH at five hospitals from March 2010 to June 2021. Outcomes included incidence of postoperative acute bleeding, recurrence rate, and morbidity or mortality rate. Patients were divided into the following four groups based on their history of AT use : no AT. Only antiplatelet agents (AP), only anticoagulants (AC), both of AP and AC. In addition, a concurrent literature review was conducted alongside our cohort study. Results : Of 462 patients, 119 (119/462, 25.76%) were using AT. AP prescription did not significantly delay surgery (p=0.318), but AC prescription led to a significant increase in the time interval from admission to operation (p=0.048). After BHT, AP or AC intake significantly increased the period required for an in-dwelling drain (p=0.026 and p=0.037). The use of AC was significantly related to acute bleeding (p=0.044), while the use of AP was not (p=0.808). Use of AP or AC had no significant effect on CSDH recurrence (p=0.517 and p=1.000) or reoperation (p=0.924 and p=1.000). Morbidity was not statistically correlated with use of either AP or AC (p=0.795 and p=0.557, respectively), and there was no significant correlation with mortality for use of these medications (p=0.470 and p=1.000). Conclusion : Elderly CSDH patients may benefit from maintenance of AT therapy during BHT due to reduced thromboembolic risk. However, the use of AC necessitates individualized due to potential postoperative bleeding. Careful post-operative monitoring could mitigate prognosis and recurrence impacts.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.337-346
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• 2023

Although wildlife bridge are built as a way to reduce habitat fragmentation caused by road construction, there is still a lot of debate about their effectiveness. Monitoring methods such as footprint traps and camera traps are used evaluate the effectiveness of wildlife bridge, but there is a limit to evaluate of effectiveness. In this study, the degree of use the wildlfe bridge was surveyed by striped field mouse that is likely use the wildlife bridge and surrounding as a habitat with capture-mark-recapture method.(Apodemus agraius). The distance and route of movement were identified by connecting the capture points, and the environmental factors on the use of the wildlife bridge implemented a generalized linear model(GLM) with the capture number of captured as a dependent variable. Consequently of capture, no individuals crossing the wildlife bridge, striped field mouse use the wildlife bridge as a habitat.The environmental factors affecting the use of mice were vegetation cover(1~2m, 2~8m, over 8m), vegetation construction, maximum diameter at breast height were positively correlated and slope was nagatively correlated. In conclusion, it is expected that the effectiveness of the wildlife bridge will be further improved by planting shrubs and trees and preventing high slope and cut slope increasing the utilization of the rat, such as being used as a food source in the ecosystem.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.195-208
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• 2023

The nodular diaphragm wall (NDW) is a novel type of foundation with favorable engineering characteristics, which has already been utilized in high-rise buildings and high-speed railways. Compared to traditional diaphragm walls, the NDW offers significantly improved vertical bearing capacity due to the presence of nodular parts while reducing construction time and excavation work. Despite its potential, research on the vertical bearing characteristics of NDW requires further study, and the investigation and visualization of its displacement pattern and failure mode are scant. Meanwhile, the measurement of the force component acting on the nodular parts remains challenging. In this paper, the vertical bearing characteristics of NDW are studied in detail through the indoor model test, and the displacement and failure mode of the foundation is analyzed using particle image velocimetry (PIV) technology. The principles and methods for monitoring the force acting on the nodular parts are described in detail. The research results show that the nodular part plays an essential role in the bearing capacity of the NDW, and its maximum load-bearing ratio can reach 30.92%. The existence of the bottom nodular part contributes more to the bearing capacity of the foundation compared to the middle nodular part, and the use of both middle and bottom nodular parts increases the bearing capacity of the foundation by about 9~12% compared to a single nodular part of the NDW. The increase in the number of nodular parts cannot produce a simple superposition effect on the resistance born by the nodular parts since the nodular parts have an insignificant influence on the exertion and distribution of the skin friction of NDW. The existence of the nodular part changes the displacement field of the soil around NDW and increases the displacement influence range of the foundation to a certain extent. For NDWs with three different nodal arrangements, the failure modes of the foundations appear to be local shear failures. Overall, this study provides valuable insights into the performance and behavior of NDWs, which will aid in their effective utilization and further research in the field.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.2
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• pp.1-12
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• 2023

In the current era of the global mobile smart device revolution, electronic devices are required in all spaces that people interact with. The establishment of the internet of things (IoT) among smart devices has been recognized as a crucial objective to advance towards creating a comfortable and sustainable future society. In-mold electronic (IME) processes have gained significant industrial significance due to their ability to utilize conventional high-volume methods, which involve printing functional inks on 2D substrates, thermoforming them into 3D shapes, and injection-molded, manufacturing low-cost, lightweight, and functional components or devices. In this article, we provide an overview of IME and its latest advances in application. We review biomimetic nanomaterials for constructing self-supporting biosensor electronic materials on the body, energy storage devices, self-powered devices, and bio-monitoring technology from the perspective of in-mold electronic devices. We anticipate that IME device technology will play a critical role in establishing a human-machine interface (HMI) by converging with the rapidly growing flexible printed electronics technology, which is an integral component of the fourth industrial revolution.

• Journal of Preventive Medicine and Public Health
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• v.56 no.5
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• pp.467-474
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• 2023

Objectives: Diabetes mellitus (DM) is a serious public health issue that places a heavy financial, social, and health-related burden on individuals, families, and healthcare systems. Self-reported health-related quality of life (HRQoL) is extensively used for monitoring the general population's health conditions and measuring the effectiveness of interventions. Therefore, this study investigated HRQoL and associated factors among patients with type 2 DM at a primary healthcare center in Indonesia. Methods: A cross-sectional study was conducted in Klaten District, Central Java, Indonesia, from May 2019 to July 2019. In total, 260 patients with DM registered with National Health Insurance were interviewed. HRQoL was measured with the EuroQol Group's validated Bahasa Indonesia version of the EuroQoL 5-Dimension 5-Level (EQ-5D-5L) with the Indonesian value set. Multivariate regression models were used to identify factors influencing HRQoL. Results: Data from 24 patients were excluded due to incomplete information. Most participants were men (60.6%), were aged above 50 years (91.5%), had less than a senior high school education (75.0%), and were unemployed (85.6%). The most frequent health problems were reported for the pain/discomfort dimension (64.0%) followed by anxiety (28.4%), mobility (17.8%), usual activities (10.6%), and self-care (6.8%). The average EuroQoL 5-Dimension (EQ-5D) index score was 0.86 (95% confidence interval [CI], 0.83 to 0.88). In the multivariate ordinal regression model, a higher education level (coefficient, 0.08; 95% CI, 0.02 to 0.14) was a significant predictor of the EQ-5D-5L utility score. Conclusions: Patients with diabetes had poorer EQ-5D-5L utility values than the general population. DM patients experienced pain/discomfort and anxiety. There was a substantial positive relationship between education level and HRQoL.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.16-24
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• 2024

Background: Indoor PM_2.5 concentrations in residential houses can be affected by various factors depending on the season. This is because not only do the climate characteristics depend on the season, but the activity patterns of occupants are also different. Objectives: The purpose of this study is to compare factors affecting indoor PM_2.5 concentrations in apartments and detached houses in Daegu according to seasonal changes. Methods: This study included 20 households in Daegu, South Korea. The study was conducted during the summer (from July 10 to August 10, 2023) and the autumn (from September 11 to October 9, 2023). A sensor-based instrument for PM_2.5 levels was installed in the living room of each residence, and measurements were taken continuously for 24 hours at intervals of one minute during the measurement period. Based on the air quality monitoring system data in Daegu, outdoor PM_2.5 concentrations were estimated using ordinary kriging (OK) in Python. In addition, the indoor activities of the occupants were investigated using a time-activity pattern diary. The affecting factors of indoor PM_2.5 concentration were analyzed using multiple regression analysis. Results: Indoor and outdoor PM_2.5 concentrations of the residences during summer were 15.27±11.09 ㎍/m³ and 11.52±7.56 ㎍/m³, respectively. Indoor and outdoor PM_2.5 concentrations during autumn were 13.82±9.61 ㎍/m³ and 9.57±5.50 ㎍/m³, respectively. The PM_2.5 concentrations were higher in summer compared to autumn both indoors and outdoors. The primary factor affecting indoor PM_2.5 concentration in summer was occupant activity. On the other hand, during the autumn season, the primary affecting factor was outdoor PM_2.5 concentration. Conclusions: Indoor PM_2.5 concentration in residential houses is affected by occupant activity such as the inflow of outdoor PM_2.5 concentration, cooking, and cleaning, as found in previous studies. However, it was revealed that there were differences depending on the season.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.6-15
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• 2024

Background: People's activities have been restricted due to the COVID-19 pandemic. These changes in activity patterns may lead to a decrease in fine particulate matter (PM_2.5) concentrations. Additionally, the level of population exposure to PM_2.5 may be changed. Objectives: This study aimed to analyze the impact of population movement and meteorological factors on the distribution of PM_2.5 concentrations before and after the outbreak of COVID-19. Methods: The study area was Guro-gu in Seoul. The research period was selected as January to March 2020, a period of significant population movement changes caused by COVID-19. The evaluation of the dynamic population was conducted by calculating the absolute difference in population numbers between consecutive hours and comparing them to determine the daily average. Ambient PM_2.5 concentrations were estimated for each grid using ordinary kriging in Python. For the population exposure assessment, the population-weighted average concentration was calculated by determining the indoor to outdoor population for each grid and applying the indoor to outdoor ratio to the ambient PM_2.5 concentration. To assess the factors influencing changes in the ambient PM_2.5 concentration, a statistical analysis was conducted, incorporating population mobility and meteorological factors. Results: Through statistical analysis, the correlation between ambient PM_2.5 concentration and population movement was positive on both weekends and weekdays (r=0.71, r=0.266). The results confirmed that most of the relationships were positive, suggesting that a decrease in human activity can lead to a decrease in PM_2.5 concentrations. In addition, when population-weighted concentration averages were calculated and the exposure level of the population group was compared before and after the COVID-19 outbreak, the proportion of people exceeding the air quality standard decreased by approximately 15.5%. Conclusions: Human activities can impact ambient concentrations of PM_2.5, potentially altering the levels of PM_2.5 exposure in the population.