• Journal of the Korean earth science society
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• v.18 no.6
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• pp.515-521
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• 1997

To investigate the nature of the waste materials in the Nanjido Landfill, we have conducted multivariate statistical analysis of geophysical data set comprised of magnetic, gravity, LandSat TM thermal band and surface depression measurement data. Because these data sets show different responses to the depth, we have transformed the observed total field magnetic data and gravity data to the residual reduced-to-pole(RTP) magnetic anomalies and the three dimensional density anomalies, respectively, and utilized the informations about the upper shallow part of the landfills only in the following process. For the statistical analysis at the points of depression measurement, the magnetic, density and LandSat data values at these points are determined by interpolation process. Since the multivarite statistical analysis technique utilizes a clustering algorithm for classification of data set and we have measured the dissimilarity between objects by using Euclidean distance, standardization was applied prior to distance calculation in order to eliminate any scaling effects due to different measurement unit of each data set. The hierarchial grouping technique was used to construct the dendrogram. The optimum number of statistical groups(clusters), which are classified on the basis of geophysical and geotechnical characteristics, appeared to be six on the resulting dendrogram. The result of this study suggests that the dimension and nature of the multicomponent waste landfills can be identified by application of the multivarite statistical analysis technique to integrated geophysical data sets.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.434-435
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• 2012

Plasma enhanced chemical vapor deposition (PECVD) silicon dioxide thin films have many applications in semiconductor manufacturing such as inter-level dielectric and gate dielectric metal oxide semiconductor field effect transistors (MOSFETs). Fundamental chemical reaction for the formation of SiO2 includes SiH4 and O2, but mixture of SiH4 and N2O is preferable because of lower hydrogen concentration in the deposited film [1]. It is also known that binding energy of N-N is higher than that of N-O, so the particle generation by molecular reaction can be reduced by reducing reactive nitrogen during the deposition process. However, nitrous oxide (N2O) gives rise to nitric oxide (NO) on reaction with oxygen atoms, which in turn reacts with ozone. NO became a greenhouse gas which is naturally occurred regulating of stratospheric ozone. In fact, it takes global warming effect about 300 times higher than carbon dioxide (CO2). Industries regard that N2O is inevitable for their device fabrication; however, it is worthwhile to develop a marginable nitrous oxide free process for university lab classes considering educational and environmental purpose. In this paper, we developed environmental friendly and material cost efficient SiO2 deposition process by substituting N2O with O2 targeting university hands-on laboratory course. Experiment was performed by two level statistical design of experiment (DOE) with three process parameters including RF power, susceptor temperature, and oxygen gas flow. Responses of interests to optimize the process were deposition rate, film uniformity, surface roughness, and electrical dielectric property. We observed some power like particle formation on wafer in some experiment, and we postulate that the thermal and electrical energy to dissociate gas molecule was relatively lower than other runs. However, we were able to find a marginable process region with less than 3% uniformity requirement in our process optimization goal. Surface roughness measured by atomic force microscopy (AFM) presented some evidence of the agglomeration of silane related particles, and the result was still satisfactory for the purpose of this research. This newly developed SiO2 deposition process is currently under verification with repeated experimental run on 4 inches wafer, and it will be adopted to Semiconductor Material and Process course offered in the Department of Electronic Engineering at Myongji University from spring semester in 2012.

• Journal of Animal Science and Technology
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• v.63 no.3
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• pp.531-544
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• 2021

Heat stress (HS) damages health and decreases performance variables in pigs, and if severe enough, causes mortality. However, metabolic changes under HS and recovery following HS are poorly understood. Therefore, this study was aimed to expose the essential mechanisms by which growing pigs respond to HS and the temporal pattern of plasma concentrations (PC) of amino acids (AAs) and metabolites. Crossbred male growing pigs were penned separately and allowed to adapt to thermal-neutral (TN) conditions (20℃ and 80% relative humidity; TN[-1D]). On the first day, all pigs were exposed to HS for 24 h (36℃ and 60% relative humidity), then to TN conditions for 5 days (TN[2D] to TN[5D]). All pigs had ad libitum access to water and 3 kg feed twice daily. Rectal temperature (RT) and feed intake (FI) were determined daily. HS pigs had higher RT (40.72℃) and lower (50%) FI than TN(-1D) pigs (p < 0.01). The PC of indispensable (threonine, valine, and methionine) and dispensable (cysteine and tyrosine) AAs were higher (p < 0.05) in HS than TN(-1D) pigs and remained increased during recovery time. Nonprotein α-aminobutyric acid and β-alanine concentrations were higher (p < 0.05) in HS than TN(-1D) pigs. The metabolite concentration of creatinine was higher (p < 0.01) under HS treatment than other treatments, but that of alanine and leucine remained increased (p < 0.05) through 5 d of recovery. In summary, some major differences were found in plasma AA profiles and metabolites between HS- and TN-condition pigs. This indicates that the HS pigs were forced to alter their metabolism, and these results provide information about mechanisms of acute HS responses relative to the recovery time.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8
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• pp.1095-1103
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• 2019

Objective: Among stress responses, the unfolded protein response (UPR) is a well-known mechanism related to endoplasmic reticulum (ER) stress. ER stress is induced by a variety of external and environmental factors such as starvation, ischemia, hypoxia, oxidative stress, and heat stress. Inositol requiring enzyme $1{\alpha}$ ($IRE1{\alpha}$)-X-box protein 1 (XBP1) is the most conserved pathway involved in the UPR and is the main component that mediates $IRE1{\alpha}$ signalling to downstream ER-associated degradation (ERAD)- or UPR-related genes. XBP1 is a transcription factor synthesised via a novel mechanism called 'frame switch splicing', and this process has not yet been studied in the horse XBP1 gene. Therefore, the aim of this study was to confirm the frame switch splicing of horse XBP1 and characterise its dynamics using Thoroughbred muscle cells exposed to heat stress. Methods: Primary horse muscle cells were used to investigate heat stress-induced frame switch splicing of horse XBP1. Frame switch splicing was confirmed by sequencing analysis. XBP1 amino acid sequences and promoter sequences of various species were aligned to confirm the sequence homology and to find conserved cis-acting elements, respectively. The expression of the potential XBP1 downstream genes were analysed by quantitative real-time polymerase chain reaction. Results: We confirmed that splicing of horse XBP1 mRNA was affected by the duration of thermal stress. Twenty-six nucleotides in the mRNA of XBP1 were deleted after heat stress. The protein sequence and the cis-regulatory elements on the promoter of horse XBP1 are highly conserved among the mammals. Induction of putative downstream genes of horse XBP1 was dependent on the duration of heat stress. We confirmed that both the mechanisms of XBP1 frame switch splicing and various binding elements found in downstream gene promoters are highly evolutionarily conserved. Conclusion: The frame switch splicing of horse XBP1 and its dynamics were highly conserved among species. These results facilitate studies of ER-stress in horse.

• Asia Marketing Journal
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• v.14 no.3
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• pp.27-48
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• 2012

Temperature and weather are all around us, quite literally. Furthermore, temperature and weather not only permeate our atmosphere, constantly affecting our visceral states of warmth and coldness, but they metaphorically permeate our language. People, products, and ideas can all be "hot" or "cold." Given this ubiquity, it is perhaps surprising that relatively little research has systematically examined the influence of temperature on choice and judgment. Temperature-related words such as "hot" and "cold" are often used to describe impulsive and calculated behaviors, respectively. These metaphoric connotations of thermal concepts raise the question as to whether temperature, psychological states and decision making are related to each other, and if so, how. The current research examines these questions and finds support for a relationship. Across one field study and one laboratory experiment, I demonstrate that both hot ambient room temperature (Spa) and hot temperature primes (words) trigger decision outcomes in line with the metaphoric association between hot temperature and impulsivity. In the field study, participants were recruited in hot (40-50 degrees Celsius) and cold (10 degrees Celsius) rooms at a spa. Participants were simply asked to indicate their willingness-to-pay (WTP) for three product categories (travel package, birthday dinner, and cell phone). The results showed that participants in the hot room in comparison to those in the cold room were willing to pay more for the same products. Next, I tested if our results would go beyond ambient temperature and would hold if I were to prime temperature concepts by using a different priming method (i.e., subliminal vs. supraliminal). In line with the previous findings in the spa, participants in the hot priming condition were more likely to choose the wrong answer for the bat and baseball question than those in the cold priming condition. In addition, product type (e.g., pleasure vs. necessity) can moderate the effect of hot temperature on impulsivity. Mood and arousal did not mediate participants' responses. My findings seem to suggest that the effects of temperature on decision outcomes can be attributed to metaphoric associations rather than incidental mood or arousal. The current research applies a novel perspective in understanding the relationship between temperature and judgment and decision making. Also, the results have practical implications for packaging, advertising, merchandising, and pricing of goods and services, as well as for public policy and awareness. One of the most natural implications of my findings would be that retailers would be better off carrying more impulse purchase items on hot days. Furthermore, point-of-purchase promotions encouraging impulse purchase is more likely to be effective in retail environments with higher temperature than with lower temperature. In addition, advertisements and product packages evoking hot temperature associations (e.g., beach, sunshine, summer) might lead consumers to pay higher price for the advertised product than those with cold temperature associations.

• Animal Bioscience
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• v.37 no.12
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• pp.2178-2188
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• 2024

Objective: The liver plays a dual role in regulating temperature and immune responses. Examining the influence of heat stress (HS) on liver T cells contributes significantly to understanding the intricate interplay between the immune system and hepatic tissues under thermal stress. This study focused on investigating the characteristics of the T-cell receptor (TCR) β chain CDR3 repertoire in bovine liver samples under both HS and pairfed (PF) environmental conditions. Methods: Sequencing data from six samples sourced from the GEO database underwent annotation. Utilizing immunarch and VDJtool software, the study conducted comprehensive analyses encompassing basic evaluation, clonality assessment, immune repertoire comparison, diversity estimation, gene usage profiling, VJ gene segment pairing scrutiny, clonal tracking, and Kmers analysis. Results: All four TCR chains, namely α, β, γ, and δ, were detected, with the α chains exhibiting the highest detection frequency, followed closely by the β chains. The prevalence of αβ TCRs in bovine liver samples underscored their crucial role in governing hepatic tissue's physiological functions. The TCR β CDR3 repertoire showcased substantial inter-individual variability, featuring diverse clonotypes exhibiting distinct amino acid lengths. Intriguingly, HS cattle displayed heightened diversity and clonality, suggesting potential peripheral T cell migration into the liver under environmental conditions. Notably, differential VJ gene pairings were observed in HS cattle compared to the PF, despite individual variations in V and J gene utilization. Additionally, while most high-frequency amino acid 5-mers remained consistent between the HS and PF, GELHF, and YDYHF were notably prevalent in the HS group. Across all samples, a prevalent trend of high-frequency 5mers skewed towards polar and hydrophobic amino acids was evident. Conclusion: This study elucidates the characteristics of liver TCR β chain CDR3 repertoire under HS conditions, enhancing our understanding of HS implications.

• Journal of Radiation Protection and Research
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• v.7 no.1
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• pp.23-33
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• 1982

The characteristic thermoluminescence responses of Teflon thermoluminescent dosimeters to radiations have been studied by the variation of radiation qualities as well as the high dose radiations. The change in the sensitivity of TLDs for different radiation qualities were studied through not only the photon energy dependence but also the change of supralinearity on the photon energy dependence, by exposing $^{60}Co$ gamma rays, the effective X-rays of 44keV, 69keV, 108keV, and thermal neutron of 0.04 eV. The results were as the following: The TL response of $T-CaSO_4$: Dy as a function of absorbed dose was linear up to about 5 Gy, and the response beyond 5Gy was supralinear for $^{60}Co$ gamma rays. The supralinearity of T-LiF-7 became noticeably apparent more than that of $T-CaSO_4$:Dy and also the lower the LET of radiation became the higher the supralinear effects were. No supralinearity appeared for the thermal neutron irradiations equivalent to 10Gy of $^{60}Co$ gamma rays. The relative sensitivities (Rs), which depended on the doses of $^{60}Co$ gamma rays to the TLDs of T-LiF-7 and T-$CaSO_4$:Dy could be, respectively, approximated to the following empirical formula fitted by the least square method: $$R_{LiF}=1.021-0.04581\;logD+0.402(logD)^2-0.405(logD)^3,\;\;5{\times}10^3{\geq}D{\geq}1(Gy)$$ $$R_{CaSO_4}=0.976-0.3241\;logD+0.262(logD)^2-0.298(logD)^3,\;5{\times}10^3{\geq}D{\geq}1(Gy)$$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.130-139
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• 2017

This study investigated the effect of heat stress on the performance and blood characteristics in commercial pig farms. A total of 180 growing pigs and 180 finishing pigs were assigned to two treatments consisting of thermal-neutral period(TNP) and high-temperature period(HTP) with three replications in floor pen, respectively. Feeding trials in the TNP and HTP were individually performed in autumn and summer seasons, respectively. Temperature-humidity index(THI) was calculated by temperature and humidity. Performance and physiological responses were identified per growth stages and feeding trial. Average temperature and THI were $16.8^{\circ}C$ and 61.4 at the TNP, and $25^{\circ}C$ and 74.3 at the HTP, respectively. Growing pigs in HTP exhibited lower BW, ADG and ADFI than in TNP(p<0.01). Similarly, finishing pigs showed lower growth parameters in HTP than in TNP(p<0.01). Lymphocytes and neutrophils of growing pigs were lower in HTP than in TNP(p<0.05). The serum T-PRO and NEFA in finishing pigs were higher in HTP than in TNP(p<0.05). In HTP, finishing pigs had higher cortisol levels than in TNP. Therefore, HTP can negatively influence growth performance and nutritional metabolism in pigs. Our results may provide useful information for developing feeding programs and diets to control heat stress for swine farms.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.