• 헬스앤미션
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• 통권12호
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• pp.28-31
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• 2008

• Asian Pacific Journal of Cancer Prevention
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• 제15권6호
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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.

• 한국콘텐츠학회논문지
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• 제20권7호
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• pp.368-378
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• 2020

본 논문은 전쟁 다큐멘터리 사진이 가진 푼크툼(punctum)과 스투디움(studium)의 특성이 수용자에게 어떻게 작용되는지 로버트 카파와 미군 사진병이 촬영한 'D-DAY' 사진을 통해 분석하였다. 연구 방법으로는 수용자들과의 인터뷰를 수행하여 푼크툼과 스투디움 경험의 표출 과정을 살펴보았다. 연구 결과 수용자들은 미군 사진병의 사진 보다 로버트 카파의 전쟁 다큐멘터리 사진에서 푼크툼적 경험을 더 크게 느끼는 것으로 나타났다. 동일한 장소에서 같은 상황을 촬영해도 촬영한 사진가에 따라 푼크툼과 스투디움을 다양한 방식으로 경험하며 사진이 현실을 그대로 보여 주지 못해 왜곡의 수단이 될 수 있다는 것을 수용자 측면에서 확인할 수 있었다. 본 연구는 전쟁 다큐멘터리 사진에 대한 수용자의 경험을 질적연구를 통해 살펴봄으로써 전쟁 다큐멘터리 사진이 가진 왜곡성과 수용자의 푼크툼적 경험을 밝혔다는 점에서 의의가 있다.

• Advances in Traditional Medicine
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• 제7권4호
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• pp.336-340
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• 2007

Plants from the genus Centaurea (C.) (Family: Asteraceae alt. Compositae), widely distributed in Asia, Europe and North America, have traditionally been used in the treatment of various ailments. As a part of our on-going studies on the plants from the genus C. for their phytochemistry and biological activities, extracts of the seeds of Turkish endemic C. species, C. bornmuelleri and C. huber-morathii, were tested for their cytotoxicity towards the CaCo2 colon cancer cell line as well as for the toxicity towards the brine shrimps, using the MTT and the brine shrimp lethality assays, respectively. Among the extracts, the MeOH extract of these plants showed significant toxicity towards the brine shrimps ($LD_{50}=55.2{\times}10^{-2}\;and\;42.4{\times}10^{-2}mg/ml$, respectively). The MeOH extract of both C. species also inhibited the growth of CaCo2 colon cancer cells in the MTT assay ($IC_{50}$=29.9 and 33.0 g/ml, respectively). As the most prominent activities in both assays were observed with the MeOH extracts, it can be assumed that the compound(s) responsible for these activities are polar in nature.

• Asian Pacific Journal of Cancer Prevention
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• 제15권14호
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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.

• Advances in Traditional Medicine
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• 제5권3호
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• pp.246-250
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• 2005

A number of species of the genus Centaurea (Family: Asteraceae), distributed in various parts of Asia, Europe and North America, have been used in traditional plant-based medicine and reported to possess various medicinal properties. As part of our continuing evaluation of plants from the genus Centaurea for their phytochemistry and biological activities, the dichloromethane (DCM) and methanol (MeOH) extracts of the seeds of Turkish Centaurea species, C. bornmuelleri, C. huber-morathii and C. schiskinii, were screened for antioxidant and antibacterial activities. Among the three species, C. huber-morathii displayed the most prominent antibacterial activity. Both the MeOH and DCM extracts of this plant showed activity against Citrobacter freundii, Enterococcus faecalis and Salmonella goldcoast with the MIC values within the range of $1\;{\times}\;10^{-2}\;to\;1\;{\times}\;10^{-3}\;mg/ml$. The MeOH extract of C schiskinii showed activity $(MIC\;=\;1\;{\times}\;10^{-1}\;mg/ml)$ against Citrobacter freundii and Staphylococcus aureus. While the DCM extract of C. bornmuelleri was only active against Staphylococcus aureus $(MIC\;=1\;{\times}\;10^{-2}\;mg/ml)$, the MeOH extract did not show any inhibitory activity at test concentrations. The DCM and MeOH extracts of all three species demonstrated good degree of antioxidant property in the DPPH assay with the $RC_{50}$ values ranging from $72\;{\times}\;10^{-2}\;to\;31{\times}\;10^{-3}\;mg/ml$. Among these extracts, the MeOH extract of C. hubermorathii was the most active antioxidant extract $(MlC\;=\;31\;{\times}\;10^{-3}\;mg/ml)$.

• 비교문화연구
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• 제31권
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• pp.95-118
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• 2013

Robert Frost's poetry has generally been considered fairly readable partly because of the simplicity or down-to-earth-ness of the messages that go along with the poet's projected public image and the 'traditional' forms he used. Against the grain of such general perception, this study reads some of the early poems of Robert Frost to re-characterize the beginning of the poet's career as a modernist attempt to challenge the dominant poetic conventions of the time: the genteel conventions. In reading the poems, this study focuses on frost's strategic method of using the speaker or persona regarding the delivery of meanings. Those readers who would like to find the immediate presence of Frost's voice in the poems, fail to distinguish the speaker and the poet, readily accepting the face value of what the speaker tries to convey: those messages which are in line with liberal individualism, like self-reliance, autonomous self, work ethics, etc. Frost's speakers, however, are rarely the mouthpiece of the poet himself. Rather, they are fictional characters who, while on the surface of the text appear to be hammering out a stable theme out of their everyday experience, under a heuristic scrutiny of the textual structure, turn out to be undermining the logic or the rationality of the theme, which can be identified as a modernist textual strategy that challenges the traditional conventions regarding the stability of meaning in a poetic text.

• 국제지역연구
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• 제15권2호
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• pp.25-47
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• 2011

본 논문은 로버트 하조의 1993년 논문을 바탕으로 중동지역에서의 평화와 갈등의 과정을 분석 하였다. 중동지역에서는 이스라엘과 연관된 수많은 무력적 충돌 가능성이 상존하고 있는 지역이다. 특히 로버트 하조의 분석처럼 팔레스타인과 시리아, 그리고 이스라엘 간의 관계는 중동 문제의 핵심이라고 볼 수 있다. 그가 지적한 이 두가지 문제는 우리가 그간 간과해왔던, 혹은 전체적으로 중동문제를 일괄적으로 다루어왔던 결과이다. 아랍 이스라엘 분쟁은 역사상 가장 다루기 힘든 분쟁 중 하나이다. 이에 관련하여 로버트 하조의 분석은 여러면에서 시사하는 바가 크다고 볼 수 있다. 먼저 1993년 로버트 하조는 '이 분쟁은 끝나지 않는 투쟁이다.' 라고 결론 내렸다. 본 논문에서는 진전, 혹은 개입 기간 부족이라는 관점에서, 그리고 현 시대의 전략적 환경에 대항하는 방식으로서 그의 분석을 살펴보고자 한다. 이를 위해 여러 가지 실증적 문헌연구를 통해 하조의 평가가 유효하다는 것을 증빙해 보려고 한다. 1993년부터 미국, 이스라엘, 그리고 시리아가 희망적인 합의를 이끌어 낼 수 있다는 잠재적인 시각이 다양한 논의들과 결합되어 진행된 가운데, 난민들에 대한 귀환의 권리, 국경문제, 그리고 예루살렘에 대한 논쟁은 가까운 미래에는 제기되지 않을 것으로 보인다.

• Journal of Interdisciplinary Genomics
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• 제6권2호
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• pp.21-24
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• 2024

The disease gene for delayed puberty is hypothesized to reside within a 3.7 Mb genomic region on chromosome 9, spanning 9q31.2 to 9q31.3, which contains 20 genes. This region aligns with 9q31.3, where the Kallmann syndrome gene is suspected to be located in a patient with a de novo balanced translocation, t(7;9)(p14.1;q31.3). After analyzing the expression patterns and reported genetic variants of the 20 candidate genes, we propose ACTL7A and ACTL7B as strong candidate genes for Kallmann syndrome. Mutation screening of these genes in Kallmann syndrome patients will be essential to confirm their pathological roles in delayed puberty.

• Asian Pacific Journal of Cancer Prevention
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• 제15권9호
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• pp.4049-4054
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• 2014

Background: Race and ethnicity are significant factors in predicting survival time of breast cancer patients. In this study, we applied advanced statistical methods to predict the survival of White non-Hispanic female breast cancer patients, who were diagnosed between the years 1973 and 2009 in the United States (U.S.). Materials and Methods: Demographic data from the Surveillance Epidemiology and End Results (SEER) database were used for the purpose of this study. Nine states were randomly selected from 12 U.S. cancer registries. A stratified random sampling method was used to select 2,000 female breast cancer patients from these nine states. We compared four types of advanced statistical probability models to identify the best-fit model for the White non-Hispanic female breast cancer survival data. Three model building criterion were used to measure and compare goodness of fit of the models. These include Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC). In addition, we used a novel Bayesian method and the Markov Chain Monte Carlo technique to determine the posterior density function of the parameters. After evaluating the model parameters, we selected the model having the lowest DIC value. Using this Bayesian method, we derived the predictive survival density for future survival time and its related inferences. Results: The analytical sample of White non-Hispanic women included 2,000 breast cancer cases from the SEER database (1973-2009). The majority of cases were married (55.2%), the mean age of diagnosis was 63.61 years (SD = 14.24) and the mean survival time was 84 months (SD = 35.01). After comparing the four statistical models, results suggested that the exponentiated Weibull model (DIC= 19818.220) was a better fit for White non-Hispanic females' breast cancer survival data. This model predicted the survival times (in months) for White non-Hispanic women after implementation of precise estimates of the model parameters. Conclusions: By using modern model building criteria, we determined that the data best fit the exponentiated Weibull model. We incorporated precise estimates of the parameter into the predictive model and evaluated the survival inference for the White non-Hispanic female population. This method of analysis will assist researchers in making scientific and clinical conclusions when assessing survival time of breast cancer patients.