The nudear changes of bovine oocytes during 24 hrs. of culture for mejotic maturation were examined. Bovine oocytes were collected from small(<2 mm), medium(2~6 mm) and large(>6mm) follicles and classified into three grades by their morphological characteristics. A total of 242 oocytes collected were obtained:from 184 small, 157 medium and 1 large follicles, respectively and were classified into 95 grade I, 155 grade H and 92 grade III oocytes. All the bovine oocytes collected and graded were washed with a basal medium and incubated in groups of 10 for 24 hrs in 5% and 39. The basal medium used was composed of TCM-199 supplemented with sodium bicarbonate, sodium pyruvate, streptomycin, penicillin G and 10% FCS. The oocytes were cultured in drops of 50,l basal medium supplemented with 35g /ml FSH, 10g /ml LH and 1g /ml estradiol-17. The oocytes were fixed and examined on their chromosomal status by 1% acetorcein staining in the interval of 3 hrs. Most of the grade I oocytes developed to germinal vesicule stage at 0 to 3 hrs., germinal vesicle breakdown at 6 hrs., metaphase I at 9 to 15 hrs., anaphase I and telophase I at 18 hrs., and metaphase II and the first polar body at 24 hrs. after culture for meiotic maturation. However, it was found that compared to grade I oocytes, grade H and W oocytes reached earlier to germinal vesicle breakdown and most of them developed earlier to M II stage at 21 hrs. after culture.

A Numerical modeling approach is usually applied to reproduce the physical phenomena of a fill dam-break. The accuracy of the dam-break model depends on the physical structure that defines input variables such as the storage volume, breach formation and progress, and the parameters of the model, which are subjective as they are prescribed by users. In this study, a sensitivity analysis was performed for the nonlinear breach progression curve that was already developed, which includes four parameters. The study focuses on the two of the parameters which control the breach forming time and peak discharge. The model is coupled with a two-dimensional flood simulation model (FLO-2D) to examine flood coverage and depth. It is generally observed that the parameter β controls only the breach forming time, the parameter γ is particularly sensitive to the peak flow.

The presence of the Fourth Industrial Revolution is omniscient, led by full force emergence of technologies that make biological, physical, and digital worlds borderless. All industries which jump on the bandwagon, can observe convergence and merging of bushiness happening within, between and across industries. As the shipping and port logistics industry is said to be in eye of this storm, the purpose of this study is to investigate the shipping and port logistics industry’s awareness regarding 4th IR, as well to identify necessary countermeasures in responding to progression of this trend. Analytic Hierarchy Process (AHP) methodology was then used to compare the importance of four phases of countermeasures, reviewed by experts in the field. Results showed that countermeasures should be first orchestrated to the ‘Merging and Integration of Inter-industry', then followed by ‘Preemptive Introduction of Advanced Technology', ‘Expansion of Intra-industry Businesses’, and eventually 'Automation, Unmanned Technology'. Last but not least, four phases of countermeasures which should be introduced and executed one phase after another, are outlined for the shipping and port logistics industry to boost its competitiveness in addressing this progressive trend.

The riprap zone of rock-fill dam is consists of shale, mudstone. This riprap is treated with engineered materials tends stable. The angle of bedding planes lead is split along the thin shale properties. Depending on weather conditions, such as exposure to soil physical and chemical properties have to be unstable. The subsidence and the slope-sliding due to weathering of the riprap occurs. The influence of weathering was analyzed by visual surveys and quantitative material properties

MFG-E8 (Milk fat globule-epidermal growth factor VIII), also called lactadherin or BA46, SED1 is a glycoprotein found in milk and mammary epithelial cells, it is a major protein component associated with milk fat globule membrane. Previously, our study showed that expression of MFG-E8 is gradually increased with hepatic differentiation of human embryonic stem cells (hESCs). Therefore, we hypothesized that MFG-E8 would be an early cancer stem cell marker, which may predict cancer progression. Our results showed that MFG-E8 was expressed in various human cancer cell lines such as HepG2, Hep3B, and Huh7. Production and secretion of the MFG-E8 were also confirmed in the conditioned media of those three cell lines using enzyme-linked immunosorbent assay. Next, we analyzed the MFG-E8 expression in 11 clinical cases of cholangiocellular carcinoma (CC) and 33 cases of hepatocellular carcinoma (HCC) by immunohistochemistry and examined the potential correlation with β-catenin and AFP, which are known cancer markers. According to hitological criteria, the progression of HCC and CC was evaluated and classified into high, low, metastatic, and well-, moderate-, poor-differentiated, respectively. Statistical analysis indicated that incidence of both HCC and CC is significantly associated with male compared to female (P<0.05). Tumor size also has positive correlation with age (r2=08948). Our immunohistochemistry data showed that MFG-E8 was expressed both HCC and CC tissue. Interestingly, the MFG-E8 expression was significantly increased with cancer progression (P<0.05) in both cases. Additionally, b-cateninexpression was increased and its localization was changed from membrane to cytoplasm and nucleus with the degree of HCC. Likely b-catenin, AFP was also increased with the degree of HCC but it was not correlated with severalty of CC. Importantly, both AFP and b-catenin were highly co-localized with MFG-E8 in HCC. These results suggest that MFG-E8 may have important physiological roles and its expression in HCC and CC would be considered as an important prognostic factor.