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This study investigates the enhancement of impact resistance in reinforced concrete (RC) beams using ultra-high-performance fiber-reinforced concrete (UHPFRC). Three types of steel fibers and two fiber volume fractions (0.75% and 1.5%) were considered. UHPFRC-strengthened RC beams exhibited an increase in flexural strength by approximately 6% at a fiber volume fraction of 1.5% compared to plain RC beams, due to effective crack suppression. Steel fibers in the UHPFRC strengthening layer inhibited the deep propagation of cracks into the compressive zone, resulting in a more gradual decrease in the neutral axis depth of RC beams. Under impact loading, UHPFRC-strengthened beams showed up to 7% lower deflection, with straight steel fibers providing superior impact resistance. RC beams strengthened with UHPFRC including straight steel fibers demonstrated improved residual flexural strength at higher fiber volumes. This highlights UHPFRC's effectiveness in enhancing impact resistance of RC beams according to the fiber type and volume fraction.

This study evaluated the health risks and chemical composition of PM1.0 and PM2.5 in Incheon, South Korea, emphasizing the critical role of particle size in public health impacts. The average concentrations were 10.89 μg/m³ for PM2.5 and 8.11 μg/m³ for PM1.0. PM1.0 displayed higher proportions of carbonaceous components and water-soluble ions, predominantly formed through photochemical reactions and atmospheric chemistry processes. Health risk assessments, using the Benzo [a]pyrene toxic equivalency factor, mutagenic and carcinogenic potential, risk index, and oxidative potential (DTT-OP), indicated that PM1.0 poses significantly higher health risks per unit mass compared to PM2.5. Key components in PM1.0, such as levoglucosan and terephthalic acid (TPA), indicate significant contributions from combustion sources like biomass burning and plastic incineration, particularly at night. PM1.0 showed higher carcinogenic and mutagenic risks than PM2.5. The correlation between levoglucosan, PAHs, and TPA supports common combustion origins. Effective management of combustion-related emissions is crucial for reducing health risks associated with PM1.0. The overall average risk index for PM1.0 is 1.30 times higher than PM2.5, implying that, on average, PM1.0 poses a 30 % higher health risk across the measured indices compared to PM2.5. This study emphasizes the need for targeted management of combustion emissions, particularly those from plastic and fuel combustion, to mitigate the health risks posed by PM1.0. Effective control of the precursors contributing to PM1.0 formation is crucial for reducing the adverse health impacts of air pollution.

We present a novel data-efficient semi-supervised framework to improve the generalization of image captioning models. Constructing a large-scale labeled image captioning dataset is expensive in terms of labor, time, and cost. In contrast to manually annotating all the training samples, separately collecting uni-modal datasets is immensely easier, e.g., a large-scale image dataset and a sentence dataset. We leverage such massive unpaired image and caption data upon standard paired data by learning to associate them. To this end, our novel semi-supervised learning method assigns pseudo-labels to unpaired images and captions in an adversarial learning fashion, where the joint distribution of image and caption is learned. This approach shows noticeable performance improvement even in challenging scenarios, including out-of-task data and web-crawled data. We also show that our proposed method is theoretically well-motivated and has a favorable global optimal property. Our extensive and comprehensive empirical results on captioning datasets, followed by a comprehensive analysis of the scarcely-paired COCO dataset, demonstrate the consistent effectiveness of our method compared to competing ones.

Abstract This study aimed to identify the factors causing NH3 emissions in the South Korean Peninsula and West Sea region. To analyze the trends of NH3 and other air pollutants, such as NOx, CO, and NR-PM1, we collected samples from six supersites across the peninsula, a roadside in Seoul, and the West Sea over different sampling periods, ranging from 1 month to 1 year. The highest NH3 concentrations were found at rural areas, ascribed to agricultural activities, particularly NH4NO3 decomposition at high summer temperatures. Areas with low population densities recorded the lowest NH3 concentrations, attributed to the lack of anthropogenic activities. A roadside field experiment confirmed the close link between ambient NH3 and vehicle emissions in urban regions by showing a strong correlation between CO and NOx concentrations and that of NH3. Moreover, we examined oceanic emissions near the eastern coast of South Korea in the West Sea. Long-range transportation studies confirmed that most of the pollutants (NH3, CO, and PM1) were transported by wind from the northeastern region of China. A maritime origin study showed that oceanic emissions and NH4NO3 decomposition in the atmosphere owing to high temperatures were the causing NH3 pollution. These findings provided valuable insights into the emission sources of NH3 in primary air pollutants in South Korea, highlighting the contributions of land-based and oceanic sources. Our study can help inform policymakers and stakeholders for developing effective regional air pollution control strategies.

Abstract We conducted spatiotemporal assessments of ozone in South Korea from 1990–2020 to evaluate trends and compare changes in compliance based on South Korean, US, and EU standards. Observational data from nationwide air-quality monitoring stations were collected and converted to the maximum daily 8 hr ozone average (MDA8O3). Seasonal ozone variations displayed an overall increase across most of South Korea and a noticeably high rate of 0.86 ppbv/yr in Seoul, with an even higher rate 1.2 ppbv/yr for the fourth-highest MDA8O3. Recent air-quality regulations to reduce NOx emissions have been estimated to weaken NO titration effects, leading to higher ozone levels for VOC-limited urban areas in South Korea while decreasing ozone concentrations elsewhere. In recent years, nearly all monitoring stations have exceeded the South Korean MDA8O3 standard, leading to debate regarding the adequacy of current standards for monitoring changes in nonattainment. Comparison with EU and US standards showed that implementing these could significantly lower nonattainment events due to the easing of target threshold values by either percentile or concentration values. Relative distances in nonattainment percentages between South Korean and other standards indicated that the EU ozone guideline was most suitable for tracing recent ozone changes not apparent when using the South Korean or US standards.

We propose a joint super resolution (SR) and frame interpolation framework that can perform both spatial and temporal super resolution. We identify performance variation according to permutation of inputs in video super-resolution and video frame interpolation. We postulate that favorable features extracted from multiple frames should be consistent regardless of input order if the features are optimally complementary for respective frames. With this motivation, we propose a permutation invariant deep architecture that makes use of the multi-frame SR principles by virtue of our order (permutation) invariant network. Specifically, given two adjacent frames, our model employs a permutation invariant convolutional neural network module to extract “complementary” feature representations facilitating both the SR and temporal interpolation tasks. We demonstrate the effectiveness of our end-to-end joint method against various combinations of the competing SR and frame interpolation methods on challenging video datasets, and thereby we verify our hypothesis.

The high spatial resolution NO2 vertical column densities (VCDs) were measured from the airborne observations using the low-cost Hyperspectral Imaging Sensor (HIS) at three industrial areas (i.e., Chungnam, Jecheon, and Pohang) in Korea, where point sources (i.e., power plant, petrochemical complex, steel yard, and cement Kiln) with significant NO2 emissions are located. An innovative and versatile approach for NO2 VCD retrieval, hereafter referred to as the Modified Wavelength Pair (MWP) method, was developed to overcome the excessively variable radiometric and spectral characteristics of the HIS attributed to the absence of temperature control during the flight. The newly developed MWP method was designed to be insensitive to broadband spectral features, including the spectral dependency of surface and aerosol reflectivity, and can be applied to observations with relatively low spectral resolutions. Moreover, the MWP method can be implemented without requiring precise radiometric calibration of the instrument (i.e., HIS) by utilizing clean pixel data for non-uniformity corrections and is also less sensitive to the optical properties of the instrument and offers computational cost competitiveness. In the experimental flights using the HIS, NO2 plumes emitted from steel yards were particularly conspicuous among the various NO2 point sources, with peak NO2 VCD of 2.0 DU at Chungnam and 1.8 DU at Pohang. The typical NO2 VCD uncertainties ranged between 0.025-0.075 DU over the land surface and 0.10-0.15 DU over the ocean surface, and the discrepancy can be attributable to the lower signal-to-noise ratio over the ocean and higher sensitivity of the MWP method to surface reflectance uncertainties under low-albedo conditions. The NO2 VCDs retrieved from the HIS with the MWP method showed a good correlation with the collocated TROPOMI data (R=0.73, mean absolute error=0.106 DU). However, the temporal disparities between the HIS frames and the TROPOMI overpass, as well as the different observation geometries under complex vertical wind fields, limited the correlation. The comparison of TROPOMI and HIS NO2 VCD further demonstrated that the satellite sub-grid variability could be intensified near the point sources, with more than a threefold increase in HIS NO2 VCD variability (e. g., difference between 25th and 75th quantiles) over the TROPOMI footprints with NO2 VCD values exceeding 0.8 DU compared to footprints with NO2 VCD values below 0.6 DU. [ABSTRACT FROM AUTHOR]