• International Journal of Stem Cells
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• v.16 no.2
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• pp.244-249
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• 2023

Background and Objectives: To examine whether ischemic retinal ganglion cells (RGCs) will be salvaged from cell death by human adipose-derived mesenchymal stem cells (ADSCs) in an organotypic retina model. Methods and Results: Deprived of arterial oxygen supply, whole mice retinas were cultured as an ex vivo organotypic cultures on an insert membrane in a 24-well plate. The therapeutic potential of ADSCs was examined by co-culture with organotypic retinas. ADSCs were seeded on top of the RGCs allowing direct contact, or at the bottom of the well, sharing the same culture media and allowing a paracrine activity. The number of surviving RGCs was assessed using Brn3a staining and confocal microscopy. Cytokine secretion of ADSCs to medium was analyzed by cytokine array. When co-cultured with ADSCs, the number of surviving RGCs was similarly significantly higher in both treatment groups compared to controls. Analysis of ADSCs cytokines secretion profile, showed secretion of anti-apoptotic and pro-proliferative cytokines (threshold>1.4). Transplantation of ADSCs in a co-culture system with organotypic ischemic retinas resulted in RGCs recovery. Since there was no advantage to direct contact of ADSCs with RGCs, the beneficial effect seen may be related to paracrine activity of ADSCs. Conclusions: These data correlated with secretion profile of ADSCs' anti-apoptotic and pro-proliferative cytokines.

• Animal Bioscience
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• v.37 no.1
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• pp.16-27
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• 2024

Objective: The objective of this study was to investigate the effect of heat stress on the growth traits and genetic parameters of Thai native chickens. Methods: A total of 16,487 records for growth traits of Thai native chickens between 2017 and 2022 were used in this study. Data included the body weight at birth, body weight at 4, 8, and 12 weeks of age (BW0, BW4, BW8, BW12), average daily gain during 0 to 4, 4 to 8, and 8 to 12 weeks of age (ADG0-4, ADG4-8, ADG8-12), absolute growth rate at birth, at 4, 8, and 12 weeks of age (AGR0, AGR4, AGR8, AGR12). The repeatability test day model used the reaction-norm procedure to analyze the threshold point of heat stress, rate of decline of growth traits, and genetic parameters. Results: At temperature and humidity index (THI) of 76, Thai native chickens began to lose their growth traits, which was the onset of heat stress in this study. The estimated heritability, genetic correlation between animal and heat stress effect, and correlations between the intercept and slope of the permanent environmental effects were 0.27, -0.85, and -0.83 for BW, 0.17, -0.81, and -0.95 for ADG, 0.25, -0.61, and -0.83 for AGR, respectively. Male chickens are more affected by heat stress than female chickens with a greater reduction of BW, ADG, and AGR, values equal to -9.30, -0.23, -15.21 (in males) and -6.04, -0.21, -10.10 (in females) gram per 1 level increase of THI from the THI of 76. Conclusion: The influence of thermal stress had a strong effect on the decline in growth traits and genetic parameters in Thai native chickens. This study indicated that genetic models used in conjunction with THI data are an effective method for the analysis and assessment of the effects of heat stress on the growth traits and genetics of native chickens.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.125-137
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• 2024

Background: The Korea Risk Information Surveillance System (K-RISS) was developed to enable the early detection of food and drug safety-related issues. Its goal is to deliver real-time risk indicators generated from ongoing food and drug risk monitoring. However, the existing K-RISS system suffers under several limitations. Objectives: This study aims to augment K-RISS with more detailed indicators and establish a severity standard that takes into account structural changes in the daily time series of K-RISS values. Methods: First, a Delphi survey was conducted to derive the required weights. Second, a control chart, commonly used in statistical process controls, was utilized to detect outliers and establish caution, attention, and serious levels for K-RISS values. Furthermore, Bai and Perron's method was employed to determine structural changes in K-RISS time series. Results: The study incorporated 'closeness to life' and 'sustainability' indicators into K-RISS. It obtained the necessary weights through a survey of experts for integrating variables, combining indicators by data source, and aggregating sub K-RISS values. We defined caution, attention, and serious levels for both average and maximum values of daily K-RISS. Furthermore, when structural changes were detected, leading to significant variations in daily K-RISS values according to different periods, the study systematically verified these changes and derived respective severity levels for each period. Conclusions: This study enhances the existing K-RISS system and introduces more advanced indicators. K-RISS is now more comprehensively equipped to serve as a risk warning index. The study has paved the way for an objective determination of whether the food safety risk index surpasses predefined thresholds through the application of severity levels.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• 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.

• Korean Journal of Radiology
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• v.2 no.1
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• pp.28-36
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• 2001

Objective: To provide a systematic overview of the effects of various parameters on contrast enhancement within the same population, an animal experiment as well as a computer-aided simulation study was performed. Materials and Methods: In an animal experiment, single-level dynamic CT through the liver was performed at 5-second intervals just after the injection of contrast medium for 3 minutes. Combinations of three different amounts (1, 2, 3 mL/kg), concentrations (150, 200, 300 mgI/mL), and injection rates (0.5, 1, 2 mL/sec) were used. The CT number of the aorta (A), portal vein (P) and liver (L) was measured in each image, and time-attenuation curves for A, P and L were thus obtained. The degree of maximum enhancement (Imax) and time to reach peak enhancement (Tmax) of A, P and L were determined, and times to equilibrium (Teq) were analyzed. In the computed-aided simulation model, a program based on the amount, flow, and diffusion coefficient of body fluid in various compartments of the human body was designed. The input variables were the concentrations, volumes and injection rates of the contrast media used. The program generated the time-attenuation curves of A, P and L, as well as liver-to-hepatocellular carcinoma (HCC) contrast curves. On each curve, we calculated and plotted the optimal temporal window (time period above the lower threshold, which in this experiment was 10 Hounsfield units), the total area under the curve above the lower threshold, and the area within the optimal range. Results: A. Animal Experiment: At a given concentration and injection rate, an increased volume of contrast medium led to increases in Imax A, P and L. In addition, Tmax A, P, L and Teq were prolonged in parallel with increases in injection time The time-attenuation curve shifted upward and to the right. For a given volume and injection rate, an increased concentration of contrast medium increased the degree of aortic, portal and hepatic enhancement, though Tmax A, P and L remained the same. The time-attenuation curve shifted upward. For a given volume and concentration of contrast medium, changes in the injection rate had a prominent effect on aortic enhancement, and that of the portal vein and hepatic parenchyma also showed some increase, though the effect was less prominent. A increased in the rate of contrast injection led to shifting of the time enhancement curve to the left and upward. B. Computer Simulation: At a faster injection rate, there was minimal change in the degree of hepatic attenuation, though the duration of the optimal temporal window decreased. The area between 10 and 30 HU was greatest when contrast media was delivered at a rate of 2 3 mL/sec. Although the total area under the curve increased in proportion to the injection rate, most of this increase was above the upper threshould and thus the temporal window was narrow and the optimal area decreased. Conclusion: Increases in volume, concentration and injection rate all resulted in improved arterial enhancement. If cost was disregarded, increasing the injection volume was the most reliable way of obtaining good quality enhancement. The optimal way of delivering a given amount of contrast medium can be calculated using a computer-based mathematical model.

• Korean journal of applied entomology
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• v.55 no.2
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• pp.119-128
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• 2016

This study was conducted to develop temperature-driven models for a population model of turnip aphid, Lipaphis erysimi: nymphal development rate models and apterious adult's oviposition (larviparous) model. Nymphal development and the longevity and fecundity of adults were examined on cabbage at six constant temperatures (10, 15, 20, 25, 30, $35{\pm}1^{\circ}C$, 16L:8D). L. erysimi nymphs did not survive at $10^{\circ}C$. Development time of nymphs increased with increasing temperature up to $30^{\circ}C$ and thereafter slightly decreased, ranging from 18.5 d at $15^{\circ}C$ to 5.9 d at $30^{\circ}C$. The lower threshold temperature and thermal constant were estimated as $7.9^{\circ}C$ and 126.3 degree days, respectively. The nonlinear model of Lactin 2 fitted well for the relationship between the development rate and temperature of small (1+2 instar), large (3+4 instar) and total nymph (all instars). The Weibull function provided a good fit for the distribution of development times of each stage. Temperature affected the longevity and fecundity of L. erysimi. Adult longevity decreased as the temperature increased and ranged from 24.4 d at $20^{\circ}C$ to 16.4 d at $30.0^{\circ}C$ with abnormal longevity 18.2 d at $15^{\circ}C$, which was used to estimate adult aging rate model for the calculation of adult physiological age. L. erysimi showed a maximum fecundity of 91.6 eggs per female at $20^{\circ}C$. In this study, we provided three temperature-dependent components for an oviposition model of L. erysimi: total fecundity, age-specific cumulative oviposition rate, and age-specific survival rate.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.4
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• pp.158-166
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• 2008

The pumpkin fruit fly, Bactrocera depressa (Tephritidae: Diptera), is one of the most important pests in Cucurbitaceae plants. This study was conducted to investigate the basic ecology of B. depressa, and to develop a forecasting model for predicting the time of adult emergence in early season. In green pumpkin producing farms, the oviposition punctures caused by the oviposition of B. depressa occurred first between mid- and late July, peaked in late August, and then decreased in mid-September followed by disappearance of the symptoms in late September, during which oviposition activity of B. depressa is considered active. In full-ripened pumpkin producing farms, damaged fruits abruptly increased from early Auguest, because the decay of pumpkins caused by larval development began from that time. B. depressa produced a mean oviposition puncture of 2.2 per fruit and total 28.8-29.8 eggs per fruit. Adult emergence from overwintering pupae, which was monitored using a ground emergence trap, was first observed between mid- and late May, and peaked during late May to early June. The development times from overwintering pupae to adult emergence decreased with increasing temperature: 59.0 days at $15^{\circ}C$, 39.3 days at $20^{\circ}C$, 25.8 days at$25^{\circ}C$ and 21.4 days at $30^{\circ}C$. The pupae did not develop to adult at $35^{\circ}C$. The lower developmental threshold temperature was calculated as $6.8^{\circ}C$ by linear regression. The thermal constant was 482.3 degree-days. The non-linear model of Gaussian equation well explained the relationship between the development rate and temperature. The Weibull function provided a good fit for the distribution of development times of overwintering pupae. The predicted date of 50% adult emergence by a degree-day model showed one day deviation from the observed actual date. Also, the output estimated by rate summation model, which was consisted of the developmental model and the Weibull function, well pursued the actual pattern of cumulative frequency curve of B. depressa adult emergence. Consequently, it is expected that the present results could be used to establish the management strategy of B. depressa.

• Korean journal of applied entomology
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• v.42 no.1
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• pp.43-51
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• 2003

This study was carried out to develop the forecasting model of Pseudococcus comtocki Kuwana for timing spray. Field phonology and temperature-dependent development of p. comstocki were studied, and its stage transition models were developed. p comstocki occurred three generations a year in Suwon. The 1 st adults occurred during mid to late June, and the 2nd adults were abundant during mid to late August. The 3rd adults were observed after late October. The development times of each instar of p. comstocki decreased with increasing temperature up to 25$^{\circ}C$, and thereafter the development times increased. The estimated low-threshold temperatures were 14.5, 8.4, 10.2, 11.8, and 10.1$^{\circ}C$ for eggs, 1st+2nd nymphs, 3rd nymphs, preoviposition, and 1st nymphs to preoviposition, respectively. The degree-days (thermal constants) for completion of each instar development were 105 DD for egg,315 DD for 1st+2nd nymph, 143 DD for 3rd nymph, 143 DD for preoviposition, and 599 DD for 1 st nymph to preoviposition. The stage transition models of p. comstocki, which simulate the proportion of individuals shifted from a stage to the next stage, were constructed using the modified Sharpe and DeMichele model and the Weibull function. In field validation, degree-day models using mean-minus-base, sine wave, and rectangle method showed 2-3d, 1-7d, and 0-6 d deviation with actual data in predicting the peak oviposition time of the 1st and 2nd generation adults, respectively. The rate summation model, in which daily development rates estimated by biophysical model of Sharpe and DeMichele were accumulated, showed 1-2 d deviation with actual data at the same phonology predictions.

• Korean journal of applied entomology
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• v.55 no.4
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• pp.445-452
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• 2016

Exorista japonica is one of the major natural enemies of noctuid larvae, Mythimna separata and Spodoptera litura. The examined parasitoid was obtained from host species M. separata, collected at Gimje city and identified by DNA sequences (partial cytochrome oxidase I, 16S, 18S, and 28S). For purposed of this study, laboratory reared S. litura served as the host species for the development of the E. japonica. The developmental period of E. japonica immature stages were investigated at seven constant temperatures (16, 19, 22, 25, 28, 31, $34{\pm}1^{\circ}C$, RH 20~30%). Temperature-dependent developmental rates and development completion models were developed. E. japonica was successfully developed from egg to adult in $16{\sim}31^{\circ}C$ temperature regimes. Developmental duration was the shortest at $34^{\circ}C$ (8.3 days) and the longest at $16^{\circ}C$ (23.4 days) from egg to pupa development. Pupal development duration was the shortest at $28^{\circ}C$ (7.3 days). Total immature-stage development duration decreased with increasing temperature, and was the shortest at $31^{\circ}C$ (16.3 days) and the longest at $16^{\circ}C$ (45.4 days). The lower developmental threshold was $7.8^{\circ}C$ and thermal constant required to complete total immature-stage development was 370.4 degree days. Among four non-linear temperature-dependent developmental rate models, Briere 1 model had the highest adjusted R-squared (0.96). The distribution model of development completion for total immature stage development of E. japonica was well described by all model ($r^2_{adj}=0.90$) based on the standardized development duration. These results of study would be necessary not only to develop population dynamics model but also to understand fundamental biology of E. japonica.