• ALGAE
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• v.31 no.4
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• pp.341-349
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• 2016

The red algal genus Amalthea was first described from New Zealand with one species, A. freemaniae. We discovered a new species of Amalthea from Korea, Amalthea rubida sp. nov., and described it based on morphology and rbcL sequences. A. rubida is characterized by a foliose, membranous and soft thallus having loosely arranged anticlinal medullary filaments, much like A. freemaniae, except for a difference of the cortex thickness in the basal part of vegetative structure. In the rbcL phylogenetic analyses, A. rubida formed a clade with A. freemaniae from New Zealand and Halymenia abyssicola from Mexico. A. rubida showed 5.7% interspecific divergence to A. freemaniae and 4.7% to H. abyssicola. Our discovery of A. rubida expands the distribution of Amalthea from the oceanic southwestern Pacific into the continental northwestern. A targeted global study is needed to fully reveal the species diversity and phylogenetic relationships of the genus Amalthea and members of the order Halymeniales.

• Child Studies in Asia-Pacific Contexts
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• v.3 no.2
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• pp.159-173
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• 2013

We examined the associations between Latino cultural variables and four sexual behaviors among female adolescents of Mexican origin. Participants ages 14 to 19 (N = 153; 70% born in the U.S) completed surveys about four sexual behaviors (making out, receiving and performing oral sex, and vaginal sex) and cultural variables (nativity, language use, familism, and importance of female virginity). Findings indicated that participants who were born in the U.S. were less likely to have engaged in making out and vaginal sex than participants born in Mexico. Participants reporting stronger familism were less likely to have engaged in making out and oral sex than participants reporting less familism. For all behaviors, placing a greater value on female virginity was associated with lesser odds of engaging in that behavior. This study expands our understanding of the role of nativity and Latino values in the sexual behaviors of Mexican-origin female adolescents.

• Asia pacific journal of information systems
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• v.33 no.3
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• pp.573-602
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• 2023

The smartphone is a necessary communication and productivity tool. Unlike other neutral, utilitarian technologies, smartphones are also a social display of wealth, i.e., of conspicuous consumption. Behavior around necessity and conspicuous goods are normally separate research tracks, and we can find no studies for technology products that exhibit both traits. We therefore propose a four-factor model that explains conspicuous consumption of "necessary" smartphones: dependency, social influence, the need for social connection, and convenience, in the United States, Mexico, and the Philippines. This paper provides confirmatory support for extant literature of the four constructs; it demonstrates the viability of the survey instrument across countries; and it shows similar effects among country models. Our structural model results imply the borderless nature of smartphone conspicuous consumption.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1271-1276
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• 2018

The CPTPP(Comprehensive and Progressive Agreement for Trans-Pacific Partnership) is a large-scale free trade agreement(FTA) in the Asia-Pacific region involving 11 remaining countries(Japan, Australia, New Zealand, Canada, Mexico, Chile, Peru, Singapore, Vietnam, Malaysia and Brunei) since the withdrawal of the US TPP in January 2017, Although the economic size is smaller than the TPP, the CPTPP has 12.9% of the world GDP and 14.9% of the trade volume, meaning that another mega FTA is born. Local economic experts believe that Vietnam's stable economic growth rate and the CPTPP agreement will have a positive impact on Vietnam's stock market and M&A market in 2018. The experts usually expect it will be come into force in 2018 and not later than 2019. The CPTPP is also very likely to enter into force in 2019 with the aggressive attitude of the member countries, simplifying the entry into force of the agreement.

• ALGAE
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• v.34 no.2
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• pp.141-151
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• 2019

The 1982-83, 1986-87, 1991-92, and 1997-98 El $Ni{\tilde{n}}o$-Southern Oscillations (ENSOs) were compared with regards to their strength and timing in the tropical Pacific Ocean, changes in ocean temperature and wave intensity, and their impacts to giant kelp populations in the Northeast Pacific. The Multivariate ENSO Index, oceanographic data, and kelp abundance data all show that the 1982-83 and 1997-98 ENSOs were stronger and resulted in greater losses of giant kelp than the 1986-87 and 1991-92 ENSOs, but that the 1982-83 and 1997-98 ENSOs differed with regard to the arrival of destructive waves relative to when the ocean waters warmed and cooled. The 1982-83 ENSO was more destructive to the giant kelp populations in central California, USA than the 1997-98 ENSO, but the 1997-98 ENSO was more destructive to the giant kelp in southern California. These events appeared similarly destructive to the populations in Baja California, Mexico. Recovery of the kelp populations also varied among the two strong ENSOs due to the ocean conditions following each ENSO. In southern and Baja California, recovery was slow following the 1982-83 ENSO, while recovery was more rapid following the 1997-98 ENSO. Unfortunately, the monitoring programs used to evaluate the kelp populations stopped shortly after the 1997-98 ENSO, resulting in a lack of data for comparisons with the more recent weak ENSOs that occurred between 2002 and 2010, or with the strong ENSO that occurred in 2014-2016. This supports the need for continued long-term monitoring programs to better understand how climate anomalies impact coastal ecosystems.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5287-5294
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• 2016

Background: Breast cancer is a worldwide public health concern and is the most prevalent type of cancer in women in the United States. This study concerned the best fit of statistical probability models on the basis of survival times for nine state cancer registries: California, Connecticut, Georgia, Hawaii, Iowa, Michigan, New Mexico, Utah, and Washington. Materials and Methods: A probability random sampling method was applied to select and extract records of 2,000 breast cancer patients from the Surveillance Epidemiology and End Results (SEER) database for each of the nine state cancer registries used in this study. EasyFit software was utilized to identify the best probability models by using goodness of fit tests, and to estimate parameters for various statistical probability distributions that fit survival data. Results: Statistical analysis for the summary of statistics is reported for each of the states for the years 1973 to 2012. Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared goodness of fit test values were used for survival data, the highest values of goodness of fit statistics being considered indicative of the best fit survival model for each state. Conclusions: It was found that California, Connecticut, Georgia, Iowa, New Mexico, and Washington followed the Burr probability distribution, while the Dagum probability distribution gave the best fit for Michigan and Utah, and Hawaii followed the Gamma probability distribution. These findings highlight differences between states through selected sociodemographic variables and also demonstrate probability modeling differences in breast cancer survival times. The results of this study can be used to guide healthcare providers and researchers for further investigations into social and environmental factors in order to reduce the occurrence of and mortality due to breast cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2519-2525
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• 2016

There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2923-2930
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• 2012

Background: Little is known about interest in faith-based health promotion programs among Asian American populations. Among the Christian denominations, the Seventh-day Adventist (SDA) church is known to place a strong doctrinal emphasis on health. Objectives: To understand appropriate ways to develop and implement health promotion programs and to conduct research among Korean American SDAs. Methods: We collaborated with the North American Division of Korean SDA Churches which sponsors annual week-long religious retreats for their church members. We developed and administered a 10-page questionnaire at their 2009 retreat in order to assess socio-demographic and church characteristics, religiosity, perceived relationship between health and religion, and interest and preferences for church-based health promotion programs. Results: Overall, 223 participants completed our survey (123 in Korean and 100 in English). The sample consisted of regular churchgoers who were involved in a variety of helping activities, and many holding leadership positions in their home churches. The vast majority was interested in receiving health information at church (80%) in the form of seminars, cooking classes and workshops (50-60%). Fewer respondents were interested in support groups (27%). Some interests and preferences differed between English and Korean language groups. Conclusion: Korean American SDA church retreat participants from a large geographic area are very interested in receiving health information and promoting health at their churches and can potentially serve as "agents of influence" in their respective communities.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2893-2900
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• 2014

Background: Statistical methods are very important to precisely measure breast cancer patient survival times for healthcare management. Previous studies considered basic statistics to measure survival times without incorporating statistical modeling strategies. The objective of this study was to develop a data-based statistical probability model from the female breast cancer patients' survival times by using the Bayesian approach to predict future inferences of survival times. Materials and Methods: A random sample of 500 female patients was selected from the Surveillance Epidemiology and End Results cancer registry database. For goodness of fit, the standard model building criteria were used. The Bayesian approach is used to obtain the predictive survival times from the data-based Exponentiated Exponential Model. Markov Chain Monte Carlo method was used to obtain the summary results for predictive inference. Results: The highest number of female breast cancer patients was found in California and the lowest in New Mexico. The majority of them were married. The mean (SD) age at diagnosis (in years) was 60.92 (14.92). The mean (SD) survival time (in months) for female patients was 90.33 (83.10). The Exponentiated Exponential Model found better fits for the female survival times compared to the Exponentiated Weibull Model. The Bayesian method is used to obtain predictive inference for future survival times. Conclusions: The findings with the proposed modeling strategy will assist healthcare researchers and providers to precisely predict future survival estimates as the recent growing challenges of analyzing healthcare data have created new demand for model-based survival estimates. The application of Bayesian will produce precise estimates of future survival times.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5571-5575
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• 2014

Background: The ability to predict the survival time of breast cancer patients is important because of the potential high morbidity and mortality associated with the disease. To develop a predictive inference for determining the survival of breast cancer patients, we applied a novel Bayesian method. In this paper, we propose the development of a databased statistical probability model and application of the Bayesian method to predict future survival times for White Hispanic female breast cancer patients, diagnosed in the US during 1973-2009. Materials and Methods: A stratified random sample of White Hispanic female patient survival data was selected from the Surveillance Epidemiology and End Results (SEER) database to derive statistical probability models. Four were considered to identify the best-fit model. We used three standard model-building criteria, which included Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) to measure the goodness of fit. Furthermore, the Bayesian method was used to derive future survival inferences for survival times. Results: The highest number of White Hispanic female breast cancer patients in this sample was from New Mexico and the lowest from Hawaii. The mean (SD) age at diagnosis (years) was 58.2 (14.2). The mean (SD) of survival time (months) for White Hispanic females was 72.7 (32.2). We found that the exponentiated Weibull model best fit the survival times compared to other widely known statistical probability models. The predictive inference for future survival times is presented using the Bayesian method. Conclusions: The findings are significant for treatment planning and health-care cost allocation. They should also contribute to further research on breast cancer survival issues.