In our previous study, we developed a CFD thermal analysis model for a CANDU spent fuel dry storage silo. The purpose of this model is to reasonably predict the thermal behavior within the silo, particularly Peak Cladding Temperature (PCT), from a safety perspective. The model was developed via two steps, considering optimal thermal analysis and computational efficiency. In the first step, we simplified the complex geometry of the storage basket, which stored 2,220 fuel rods, by replacing it with an equivalent heat conductor with effective thermal conductivity. Detailed CFD analysis results were utilized during this step. In the second step, we derived a thermal analysis model that realistically considered the design and heat transfer mechanisms within the silo. We developed an uncertainty quantification method rooted in the widely adopted Best Estimate Plus Uncertainty (BEPU) method in the nuclear industry. The primary objective of this method is to derive the 95/95 tolerance limits of uncertainty for critical analysis outcomes. We initiated by assessing the uncertainty associated with the CFD input mesh and the physical model applied in thermal analysis. And then, we identified key parameters related to the heat transfer mechanism in the silo, such as thermal conductivity, surface emissivity, viscosity, etc., and determined their mean values and Probability Density Functions (PDFs). Using these derived parameters, we generated CFD inputs for uncertainty quantification, following the principles of the 3rd order Wilks’ formula. By calculating inputs, A database could be constructed based on the results. And this comprehensive database allowed us not only to quantify uncertainty, but also to evaluate the most conservative estimates and assess the influence of parameters. Through the aforementioned method, we quantified the uncertainty and evaluated the most conservative estimates for both PCT and MCT. Additionally, we conducted a quantitative evaluation of parameter influences on both. The entire process from input generation to data analysis took a relatively short period of time, approximately 5 days, which shows that the developed method is efficient. In conclusion, our developed method is effective and efficient tool for quantifying uncertainty and gaining insights into the behavior of silo temperatures under various conditions.

Artificial insemination (AI) has been performed widely in swine industry using fresh liquid sperm instead of frozen type of sperm. However fresh sperm are not able to preserve more than three days with optimal motility and other sperm parameters for the successful fertilization, since in vitro stored sperm has an oxidative stress that resulted increase of abnormality and acrosome reation. To overcome these major problems, novel preservative formulation is needed to neutralize the oxidative stress and to provide suitable physiological environment for sperm in in vitro. In this study, naturally derived substances such as Poncirus trifoliate (Trifoliate orange), Garcinia mangostana (Mangosteen), pig placenta and testis extracts were tested as sperm preservative agents. Placenta extracts (PE), trifoliate orange extracts (TOE), testes extracts (TE) and mangosteen extracts (ME) were applied to analyze specific parameters for sperm motion characteristics individually and combinatorial. Each individual extract treatment can accelerate the sperm motility but noticeably TOE, TE and ME treatments exhibited the considerable and significant preservation of sperm motility. PE, TE and ME showed a significant (p<0.05) increase in ALH after one week. Further we evaluated the five different combinations of these extracts on sperm motility and its motion characteristics. Surprisingly even after one week ME, TOE and TE combination significantly preserved the sperm motility about 75%. It is noteworthy that unlike individual extract treatment, combination of ME, TOE and TE simultaneously protect the sperm motility and its motion characteristics. Taken together these data conclude that addition of ME, TOE and TE can be effective for preservation of pig sperm.

MAC-T cells, bovine mammary epithelial cell line, have been utilized to investigate bovine lactation system. A lactogenic phenotype of the cell is generally induced by combination of dexamethasone, insulin and prolactin (PRL). Effect of vitamin A derivative retinoic acid (RA), well reported as an inducer for differentiation in many cells, to MAC-T cell has not been studied. The objective of this study was to confirm effect of differentiation potential by RA treatment in MAC-T cells and to test effect of combination of RA and PRL treatment. In RA or PRL treatment groups, both has induced morphological change to secrete milk of MAC-T cells. Combination of RA and PRL treatment group has presented noticeable lactogenic phenotype among the all group. This phenotype observed at four days after treatment and showed critical morphological change that was rouphly spherical structure at eight days. RA alone treatment showed slightly inhibition of proliferation in the MAC-T cells, but co-treatment with PRL was improved the cell growth more than control group. MTT assay result and Bcl-xL/Bax ratio of mRNA abundance also was entirely consistent with earlier one. RA-induced differentiation of MAC-T cells has increased αs1-casein, αs2-casein and β-casein mRNA expression compared to PRL treatment group. Expression of αs1-casein, αs2-casein and β-casein genes represented the maximum value in the combination of RA and PRL treatment group at four days. The value of each casein gene expression was 4-, 5.5- and 5.9-fold, respectively, as compared with PRL alone treatment in the MAC-T cells. Protein level of β-casein releasing to the medium also induced the highest level at four days. These results provide evidence that RA can induce the differentiation of MAC-T cells and have synergetic effect with PRL.