Due to the growing concern over forecasting extreme weather events such as droughts caused by climate change, there has been a rising interest in seasonal meteorological forecasts that offer ensemble predictions for the upcoming seven months. Nonetheless, limited research has been conducted in South Korea, particularly in assessing their effectiveness at the catchment-scale. In this study, we assessed the accuracy of ECMWF's seasonal forecasts (including precipitation, temperature, and evapotranspiration) for the period of 2011 to 2020. We focused on 12 multi-purpose reservoir catchments and compared the forecasts to climatology data. Continuous Ranked Probability Skill Score method is adopted to assess the forecast skill, and the linear scaling method was applied to evaluate its impact. The results showed that while the seasonal meteorological forecasts have similar skill to climatology for one month ahead, the skill decreased significantly as the forecast lead time increased. Compared to the climatology, better results were obtained in the Wet season than the Dry season. In particular, during the Wet seasons of the dry years (2015, 2017), the seasonal meteorological forecasts showed the highest skill for all lead times.
Objectives: The purpose of this study was to provide clinical evidence to support the use of auricular blood-letting therapy (ABT) for headaches. Methods: Studies were identified by a comprehensive search of five databases. Randomized controlled trials (RCTs) that investigated the effects of the ABT for headaches were included. Two authors independently extracted the data and assessed the methodological quality of the included studies using Cochrane's risk-of-bias tool. If two or more studies reported the same outcome, a meta-analysis was performed. Meta-analysis results for dichotomous variables are expressed as risk ratios (RRs) and 95% confidence intervals (CIs). Results: A total of eight RCTs were included in this review. The total effective rate (TER) was the most commonly used outcome measurement. Among the eight RCTs, five were included in the metaanalysis. The TER was not statistically significantly different in the ABT group compared to the medication group (two studies, n=55, RR=1.24, 95% CI: 0.78 to 1.96, p=0.36, I2 =86%). However, the TER of the combined ABT and medication group was significantly different compared to the medication alone group (four studies, n=159, RR=1.23, 95% CI: 1.12 to 1.35, p<0.0001, I2 = 0%). Pain and mental health-related outcomes in the combined ABT and medication group were significantly different from the control groups. The methodological quality of the included RCTs was generally low. Conclusions: ABT combined with medication may be effective for treating headaches. However, the number of studies included was small, so the results were insufficient, and statistically significant effects were not confirmed for a single implementation of ABT. Thus, well-designed further studies based on the findings of this study are recommended.
Life expectancy is increasing due to the aging of the population, which is in turn exacerbating problems such as the prevalence of various geriatric diseases. This study was established to provide basic data for the expansion of forest healing activities for the elderly by systematically analyzing the literature on how such activities affect this age group. For the collection of studies, the Korean databases RISS, KISS, Korea Med, and Science On were used, while PubMed, Cochrane Central, MDPI, and Google Scholar were used to identify reports published elsewhere. To assess the quality of the methodology used in the collected studies, the risk of bias was analyzed using Cochrane's RoB2 and RoBANS. Among 1,856 reports initially identified, 21 were finally selected for analysis in this study, which were limited to research papers on forest healing activities for the elderly published between 2000 and January 2022. In this review, the subjects were those aged 60 or older, with a total of 750 participants, ranging from at least 7 to a maximum of 88 per study. The analysis showed that the most frequently performed tests in each category were on depression as a psychological indicator in 7 studies, MMSE(Mini Mental State Examination) as a cognitive indicator in 2 studies, on blood pressure as a physiological indicator in 4 studies, on melatonin as a biochemical indicator in 2 studies, and on body fat and muscle strength as physical indicators in 3 studies. Of the 21 studies, 19 used two or more test items, with psychological indicators being most commonly measured. For the future application of forest healing activities for the elderly, various forest healing programs to prevent cognitive function decline should be developed and distributed, and follow-up studies should be continuously presented to provide the basis for forest healing activities.
The objective of this paper is to develop volume equation of street tree and its carbon stock for urban forest in Seoul. To develop the volume equation by major species in Seoul, data for street trees were obtained from four-species (e.g. Gingko biloba, Platanus occidentalis, Zelkova serrata, and Metasequoia glyptostroboides), which accounted for 79% all street trees in Seoul. This study used a variable based on diameter on breast height and four equation for calculating volume. The coefficient of determination, bias, and root mean square error were used to evaluate the precision of four equations. From these methods, the most suitable equations for Platanus occidentalis was aDb, the other was aD+bD2; coefficient of determination upper on 0.873. From the volume equation developed in this research, the estimated carbon stock were derived as about 33,760tC for four-species of urban forest in Seoul. The results of this paper offered volume equation and carbon stock that present growth information for street trees in urban forestry and these can be made available for evaluating the management for carbon in settlement.
Objective: This study was conducted to investigate the preventive effect of herbal medicines on restenosis after percutaneous coronary intervention (PCI) by reviewing randomized controlled trials (RCTs). Methods: RCTs were searched for herbal medicine treatment after PCI using eight online databases (PubMed, CNKI, Wanfang, J-STAGE, OASIS, ScienceON, KTKP, and KISS). Studies that confirmed restenosis through coronary angiography at follow-up were selected according to the inclusion and exclusion criteria. The primary outcome was the restenosis rate, and the secondary outcome was the angina recurrence rate. Data were extracted from the final selected studies according to the research methodology and then analyzed with Review Manager 5.4.1. Study quality was assessed using Cochrane's risk-of-bias (RoB) tool. Results: Of the 252 papers obtained through the primary search, nine studies that met the selection criteria were finally selected. In these nine studies, herbal medicine combined with western medicine was used for the experimental group, and western medicine treatment was used alone for the control group. The meta-analysis result revealed that the restenosis rate and angina recurrence rate were significantly lower in the experimental group than in the control group (RR=0.34, 95% CI: 0.22-0.53, p<0.00001, I2=0% and RR=0.47, 95% CI: 0.29-0.78, p=0.004, I2=0%, respectively). Furthermore, the quality of studies assessed by Cochrane's RoB was low. Conclusions: This study showed that the combined treatment of herbal medicine and western medicine was effective in preventing restenosis and angina after PCI. As the number of papers included in this study was small, a large number of high-quality clinical studies should be considered in the future.
Hyo Sang Lee;Yeongkuk Kim;Doo Ho Lee;Dongwon Seo;Dong Jae Lee;Chang Hee Do;Phuong Thanh N. Dinh;Waruni Ekanayake;Kil Hwan Lee;Duhak Yoon;Seung Hwan Lee;Yang Mo Koo
Journal of Animal Science and Technology
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v.65
no.4
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pp.720-734
/
2023
In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (Me) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between Me and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between Me and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the Me, the higher the accuracy of EBV.
The study examines the effects of parameters that define the characteristics of raindrops on the simulated precipitation during the summer season over Korea using the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) cloud microphysics scheme. Prescribed parameters, defining the characteristics of hydrometeors in the WDM6 scheme such as aR, bR, and fR in the fall velocity (VR) - diameter (DR) relationship and shape parameter (𝜇R) in the number concentration (NR) - DR relationship, presents different values compared to the observed data from Two-Dimensional Video Disdrometer (2DVD) at Boseong standard meteorological observatory during 2018~2019. Three experiments were designed for the heavy rainfall event on August 8, 2022 using WRF version 4.3. These include the control (CNTL) experiment with original parameters in the WDM6 scheme; the MUR experiment, adopting the 50th percentile observation value for 𝜇R; and the MEDI experiment, which uses the same 𝜇R as MUR, but also includes fitted values for aR, bR, and fR from the 50th percentile of the observed VR - DR relationship. Both sensitivity experiments show improved precipitation simulation compared to the CNTL by reducing the bias and increasing the probability of detection and equitable threat scores. In these experiments, the raindrop mixing ratio increases and its number concentration decreases in the lower atmosphere. The microphysics budget analysis shows that the increase in the rain mixing ratio is due to enhanced source processes such as graupel melting, vapor condensation, and accretion between cloud water and rain. Our study also emphasizes that applying the solely observed 𝜇R produces more positive impact in the precipitation simulation.
A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.
The accuracy and error characteristics of microwave Sea Surface Temperature (SST) measurements in the Northwest Pacific were analyzed by utilizing 162,264 collocated matchup data between GCOM-W1/AMSR2 data and oceanic in-situ temperature measurements from July 2012 to August 2016. The AMSR2 SST measurements had a Root-Mean-Square (RMS) error of about $0.63^{\circ}C$ and a bias error of about $0.05^{\circ}C$. The SST differences between AMSR2 and in-situ measurements were caused by various factors, such as wind speed, SST, distance from the coast, and the thermal front. The AMSR2 SST data showed an error due to the diurnal effect, which was much higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. In addition, the RMS error tended to be large in the winter because the emissivity of the sea surface was increased by high wind speeds and it could induce positive deviation in the SST retrieval. Low sensitivity at colder temperature and land contamination also affected an increase in the error of AMSR2 SST. An analysis of the effect of the thermal front on satellite SST error indicated that SST error increased as the magnitude of the spatial gradient of the SST increased and the distance from the front decreased. The purpose of this study was to provide a basis for further research applying microwave SST in the Northwest Pacific. In addition, the results suggested that analyzing the errors related to the environmental factors in the study area must precede any further analysis in order to obtain more accurate satellite SST measurements.
Won Hyong-kyu;Jeong Jin-Hyun;Koo Kyo-Sang;Song Myung Hee;Shin Man Yong
Korean Journal of Agricultural and Forest Meteorology
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v.7
no.2
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pp.132-140
/
2005
This study was conducted to develop regional site index equations for main tree species in Gangwon, Gyunggi-Chungcheong, Gyungsang, and Jeolla area of Korea, using environmental and soil factors obtained from a digital forest site map. Using the large data set obtained from the digital forest map, a total of 28 environmental and soil factors were regressed on site index by tree species for developing the best site index equations for each of the regions. The selected main tree species were Larix 1eptolepis, Pinus koraiensis, Pinus densiflora, Pinus thunbergii, and Quercus acutissima. Finally, four to five environmental and soil factors by species were chosen as independent variables in defining the best regional site index equations with the highest coefficients of determination $(R^2)$. For those site index equations, three evaluation statistics such as mean difference, standard deviation of difference and standard error of difference were applied to the data sets independently collected from fields within the region. According to the evaluation statistics, it was found that the regional site index equations by species developed in this study conformed well to the independent data set, having relatively low bias and variation. It was concluded that the regional site index equations by species had sufficient capability for the estimation of site productivity.
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