Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
3,141
result(s) for
"Han, Chul"
Sort by:
Temperature Prediction Based on Bidirectional Long Short-Term Memory and Convolutional Neural Network Combining Observed and Numerical Forecast Data
Weather is affected by a complex interplay of factors, including topography, location, and time. For the prediction of temperature in Korea, it is necessary to use data from multiple regions. To this end, we investigate the use of deep neural-network-based temperature prediction model time-series weather data obtained from an automatic weather station and image data from a regional data assimilation and prediction system (RDAPS). To accommodate such different types of data into a single model, a bidirectional long short-term memory (BLSTM) model and a convolutional neural network (CNN) model are chosen to represent the features from the time-series observed data and the RDAPS image data. The two types of features are combined to produce temperature predictions for up to 14 days in the future. The performance of the proposed temperature prediction model is evaluated by objective measures, including the root mean squared error and mean bias error. The experiments demonstrated that the proposed model combining both the observed and RDAPS image data is better in all performance measures for all prediction periods compared with the BLSTM-based model using observed data and the CNN-BLSTM-based model using RDAPS image data alone.
Journal Article
Incorporation of multi-phase halogen chemistry into the Community Multiscale Air Quality (CMAQ) model
Halogen radicals (Cl, Br, and I) significantly influence atmospheric oxidation capacity, affecting both O3 formation and destruction. However, understanding of halogen chemistry remains limited. To better investigate comprehensive atmospheric halogen chemistry, we incorporated halogen processes into the Community Multi-scale Air Quality (CMAQ) model: (i) emissions of Cl2, HCl, Br2, and HBr from anthropogenic sources and Br2, I2, HOI, and halocarbons from natural sources and (ii) 177 multi-phase halogen reactions. Model performance was evaluated against observed ClNO2 levels and by comparison with reported ranges of BrO and IO levels. The updated model showed significant improvements in simulating ClNO2 mixing ratios, with the index of agreement (IOA) increasing from 0.41 to 0.66 and mean bias (MB) decreasing from −159.36 to −25.07 ppt at supersites. Furthermore, simulated BrO and IO levels fell within the ranges reported in previous studies. We found that these improvements were driven by four key reactions: (i) ClO self-reaction, (ii) heterogeneous HOBr chemistry, (iii) NO2 uptake, and (iv) revised N2O5 parameterization. Based on our modeling system, we found that the presence of halogen radicals led to changes in the net Ox production rate (P(Ox)), which increased from 3.08 to 3.33 ppb h−1 on land and decreased from 0.21 to 0.07 ppb h−1 over ocean. It was noted that levels of OH, HCHO, and NOx also increased by ∼0.007 ppt (5.5 %), ∼0.03 ppb (1.6 %), and ∼0.29 ppb (2.9 %), respectively, while levels of HO2 and volatile organic compounds (VOCs) decreased by ∼0.45 ppt (5.3 %) and ∼0.71 ppb (5.9 %). These results highlight the importance of accurately representing halogen processes in regional air quality models.
Journal Article
Concentration Trajectory Route of Air pollution with an Integrated Lagrangian model (C-TRAIL Model v1.0) derived from the Community Multiscale Air Quality Model (CMAQ Model v5.2)
This paper introduces a novel Lagrangian model (Concentration Trajectory Route of Air pollution with an Integrated Lagrangian model, C-TRAIL version 1.0) output from a Eulerian air quality model for validating the source–receptor direct link by following polluted air masses. To investigate the concentrations and trajectories of air masses simultaneously, we implement the trajectory-grid (TG) Lagrangian advection scheme in the CMAQ (Community Multiscale Air Quality) Eulerian model version 5.2. The TG algorithm follows the concentrations of representative air “packets” of species along trajectories determined by the wind field. The diagnostic output from C-TRAIL accurately identifies the origins of pollutants. For validation, we analyze the results of C-TRAIL during the KORUS-AQ campaign over South Korea. Initially, we implement C-TRAIL in a simulation of CO concentrations with an emphasis on the long- and short-range transport effects. The output from C-TRAIL reveals that local trajectories were responsible for CO concentrations over Seoul during the stagnant period (17–22 May 2016) and during the extreme pollution period (25–28 May 2016), highly polluted air masses from China were distinguished as sources of CO transported to the Seoul Metropolitan Area (SMA). We conclude that during the study period, long-range transport played a crucial role in high CO concentrations over the receptor area. Furthermore, for May 2016, we find that the potential sources of CO over the SMA were the result of either local transport or long-range transport from the Shandong Peninsula and, in some cases, from regions north of the SMA. By identifying the trajectories of CO concentrations, one can use the results from C-TRAIL to directly link strong potential sources of pollutants to a receptor in specific regions during various time frames.
Journal Article
مجتمع الشفافية /
يتناول كتاب (يذكر عنوان الكتاب) والذي قام بتأليفه (يذكر اسم المؤلف) يقع هذا الكتاب في 104 صفحات من القطع المتوسط موضوع (الضبط الاجتماعي)، يتضمن بالإضافة للتوطئة والفهرس تسعة محاور معنونة كالآتي : مجتمع الإيجابية، مجتمع العرض، مجتمع شاهد كي تصدق، مجتمع البورنوغرافيا، مجتمع التسارع، مجتمع الحميمية، مجتمع المعلوماتية، مجتمع اللا-تحجب مجتمع التحكم.
Book
C24 Ceramide Lipid Nanoparticles for Skin Wound Healing
Background/Objectives: C24 ceramide plays a crucial role in skin regeneration and wound healing; however, its hydrophobic nature limits its application in therapeutic formulations. This study aims to enhance the bioavailability and efficacy of C24 ceramide by developing ceramide-based lipid nanoparticles (C24-LNP) and evaluate their impact on skin regeneration and wound healing. Methods: C24-LNP was synthesized and characterized for aqueous stability and bioavailability. In vitro experiments were conducted to assess its effects on keratinocyte proliferation and migration. Molecular biological analysis examined key signaling pathways, including AKT and ERK1/2 phosphorylation. Additionally, an in vivo mouse wound model was utilized to evaluate wound healing efficacy, with histological analysis performed to assess epidermal and dermal regeneration. Results: C24-LNP exhibited improved aqueous stability and bioavailability compared to free C24 ceramide. In vitro studies demonstrated that C24-LNP significantly promoted keratinocyte proliferation and migration. Molecular analysis revealed activation of the AKT and ERK1/2 signaling pathways, which are critical for cell growth and skin regeneration. In vivo wound healing experiments showed that C24-LNP accelerated wound closure compared to the control group. Histological analysis confirmed enhanced epidermal and dermal regeneration, leading to improved structural and functional skin repair. Conclusion: The lipid nanoparticle formulation of C24 ceramide effectively increases its bioavailability and enhances its therapeutic efficacy in skin regeneration and wound healing. C24-LNP presents a scalable and cost-effective alternative to traditional growth factor-based therapies, offering significant potential for clinical applications in wound care and dermatological treatments.
Journal Article
Preliminary study for dose evaluation depending on dose range with optically stimulated luminescence dosimeter considering individual dosimeter sensitivity
The purpose of this study was to investigate dose evaluation depending on dose range using optically stimulated luminescence dosimeter (OSLD) and evaluate the possibility of high dose evaluation. This study investigated a commercial OSLD and used a Co-60 gamma irradiator for irradiation. The OSLDs (N = 26) were sampled in total OSLDs (N = 46) depending on the radiation sensitivity for this study. After irradiating doses from 0.5 to 40 Gy at fixed intervals in a standard environment, the dose response of a reference OSLD (N = 5) was determined through the reading process at each dose. The dose-response curves obtained from the reference OSLD were fitted according to the dose. In the dose range below 3 Gy, a linear function was used to determine the relationship between dose and the OSLD response. Quadratic and cubic functions were applied for dose ranges of up to 15 Gy and 40 Gy, respectively. Test OSLDs (N = 21) were evaluated at various doses (2.5 to 30 Gy) using different fitting functions, according to dose ranges. When doses from 0.5 Gy to 3.0 Gy were curve-fitted to the linear function, the relationship was y = 70278.0 x − 3125.3 (r 2 = 0.999). When doses of up to 15 Gy were curve-fitted to the quadratic function, the relationship was y = 628.6 x 2 + 70444.6 x − 6142.3 (r 2 = 0.999). Furthermore, when doses of up to 40 Gy were curve-fitted to the cubic function, the relation was y = −15.5 x 3 + 527.3 x 2 + 75059.6 x − 16260.3 (r 2 = 0.998). Test OSLDs were evaluated for various dose ranges based on the above equation. It was confirmed that the average difference was 0.86 ± 0.27%, and it was evaluated that the largest difference occurred at 30 Gy (2.24 ± 0.24%). In this study, we prove that measurements using the OSLD at various dose ranges, including high doses, will be possible through the application of an in-house software program and a correction process.
Journal Article