Education•Cheonan, South Korea•
About: Dankook University is a education organization based out in Cheonan, South Korea. It is known for research contribution in the topics: Population & OLED. The organization has 8133 authors who have published 15018 publications receiving 223270 citations. The organization is also known as: DKU.
Papers published on a yearly basis
TL;DR: A review of the recent progress and major trends in the field of thin-film transistor (TFT) research involving the use of amorphous oxide semiconductors (AOS) is provided in this paper.
Abstract: The present article is a review of the recent progress and major trends in the field of thin-film transistor (TFT) research involving the use of amorphous oxide semiconductors (AOS). First, an overview is provided on how electrical performance may be enhanced by the adoption of specific device structures and process schemes, the combination of various oxide semiconductor materials, and the appropriate selection of gate dielectrics and electrode metals in contact with the semiconductor. As metal oxide TFT devices are excellent candidates for switching or driving transistors in next generation active matrix liquid crystal displays (AMLCD) or active matrix organic light emitting diode (AMOLED) displays, the major parameters of interest in the electrical characteristics involve the field effect mobility (μFE), threshold voltage (Vth), and subthreshold swing (SS). A study of the stability of amorphous oxide TFT devices is presented next. Switching or driving transistors in AMLCD or AMOLED displays inevitably involves voltage bias or constant current stress upon prolonged operation, and in this regard many research groups have examined and proposed device degradation mechanisms under various stress conditions. The most recent studies involve stress experiments in the presence of visible light irradiating the semiconductor, and different degradation mechanisms have been proposed with respect to photon radiation. The last part of this review consists of a description of methods other than conventional vacuum deposition techniques regarding the formation of oxide semiconductor films, along with some potential application fields including flexible displays and information storage.
TL;DR: Data suggest that ADSC is constitutionally well suited for dermal wound healing and secretory factors derived from ADSCs promote wound healing via HDFs and ADSCs can be used for the treatment of photoaging and wound healing.
Abstract: Summary Background Adipose-derived stem cells (ADSCs) are a population of pluripotent cells, which have characteristics similar to bone marrow-derived mesenchymal stem cells. Whereas ADSCs have potential applications for the repair and regeneration of various damaged tissues, few studies have dealt with the effect of ADSCs on fibroblasts, which play a key role in skin biology. Objective In this study, we investigated the possible roles of ADSCs in skin wound healing process, especially in the aspect of fibroblast activation—proliferation, collagen synthesis and migratory properties. Methods and results ADSCs promoted human dermal fibroblast (HDF) proliferation, not only by cell-to-cell direct contact, which was confirmed by co-culture experiment, but also by paracrine activation through secretory factors, resolved by transwell co-culture and culturing with conditioned medium of ADSCs (ADSC-CM). ADSC-CM enhanced the secretion of type I collagen in HDFs by regulating the mRNA levels of extracellular matrix (ECM) proteins: up-regulation of collagen type I, III and fibronectin and down-regulation of MMP-1. Moreover, ADSC-CM showed stimulatory effect on migration of HDFs in in vitro wound healing models. Additional to those in vitro evidences, wound healing effect of ADSCs was also verified with in vivo animal study, resulted that ADSCs significantly reduced the wound size and accelerated the re-epithelialization from the edge. Conclusion Collectively, these data suggest that ADSC is constitutionally well suited for dermal wound healing and secretory factors derived from ADSCs promote wound healing via HDFs and ADSCs can be used for the treatment of photoaging and wound healing.
TL;DR: The transition metal phosphides (Ni2P) as mentioned in this paper have been proposed as a promising group of high-activity, stable catalysts for both HDS and HDN, with Ni2P outperforming the promoted sulfides on the basis of sites titrated by chemisorption.
Abstract: The diminishing quality of oil feedstocks coupled with increasingly more stringent environmental regulations limiting the content of sulfur in transportation fuels have given rise to a need for improved hydroprocessing technology. This review begins with a summary of the major improvements in hydrodesulfurization (HDS) and hydrodenitrogenation (HDN) catalysts and processes that have been reported in recent years. It then describes a new class of hydroprocessing catalysts, the transition metal phosphides, which have emerged as a promising group of high-activity, stable catalysts. The phosphides have physical properties resembling ceramics, so are strong and hard, yet retain electronic and magnetic properties similar to metals. Their crystal structures are based on trigonal prisms, yet they do not form layered structures like the sulfides. They display excellent performance in HDS and HDN, with the most active phosphide, Ni2P, having activity surpassing that of promoted sulfides on the basis of sites titrated by chemisorption (CO for the phosphides, O2 for the sulfides). In the HDS of difficult heteroaromatics like 4,6-dimethyldibenzothiophene Ni2P operates by the hydrogenation pathway, while in the HDN of substituted nitrogen compounds like 2-methylpiperidine it carries out nucleophilic substitution. The active sites for hydrogenation in Ni2P have a square pyramidal geometry, while those for direct hydrodesulfurization have a tetrahedral geometry. Overall, Ni2P is a promising catalyst for deep HDS in the presence of nitrogen and aromatic compounds.
Monash University1, Kaiser Permanente2, Pennington Biomedical Research Center3, Copenhagen University Hospital4, Ewha Womans University5, Norwegian Institute of Public Health6, Michigan State University7, Dankook University8, University of Antwerp9, Katholieke Universiteit Leuven10, University of California, Irvine11
TL;DR: More than 1 million pregnant women had gestational weight gain greater than or less than guideline recommendations, compared with weight gain within recommended levels, was associated with higher risk of adverse maternal and infant outcomes.
Abstract: Importance Body mass index (BMI) and gestational weight gain are increasing globally. In 2009, the Institute of Medicine (IOM) provided specific recommendations regarding the ideal gestational weight gain. However, the association between gestational weight gain consistent with theIOM guidelines and pregnancy outcomes is unclear. Objective To perform a systematic review, meta-analysis, and metaregression to evaluate associations between gestational weight gain above or below the IOM guidelines (gain of 12.5-18 kg for underweight women [BMI Data Sources and Study Selection Search of EMBASE, Evidence-Based Medicine Reviews, MEDLINE, and MEDLINE In-Process between January 1, 1999, and February 7, 2017, for observational studies stratified by prepregnancy BMI category and total gestational weight gain. Data Extraction and Synthesis Data were extracted by 2 independent reviewers. Odds ratios (ORs) and absolute risk differences (ARDs) per live birth were calculated using a random-effects model based on a subset of studies with available data. Main Outcomes and Measures Primary outcomes were small for gestational age (SGA), preterm birth, and large for gestational age (LGA). Secondary outcomes were macrosomia, cesarean delivery, and gestational diabetes mellitus. Results Of 5354 identified studies, 23 (n = 1 309 136 women) met inclusion criteria. Gestational weight gain was below or above guidelines in 23% and 47% of pregnancies, respectively. Gestational weight gain below the recommendations was associated with higher risk of SGA (OR, 1.53 [95% CI, 1.44-1.64]; ARD, 5% [95% CI, 4%-6%]) and preterm birth (OR, 1.70 [1.32-2.20]; ARD, 5% [3%-8%]) and lower risk of LGA (OR, 0.59 [0.55-0.64]; ARD, −2% [−10% to −6%]) and macrosomia (OR, 0.60 [0.52-0.68]; ARD, −2% [−3% to −1%]); cesarean delivery showed no significant difference (OR, 0.98 [0.96-1.02]; ARD, 0% [−2% to 1%]). Gestational weight gain above the recommendations was associated with lower risk of SGA (OR, 0.66 [0.63-0.69]; ARD, −3%; [−4% to −2%]) and preterm birth (OR, 0.77 [0.69-0.86]; ARD, −2% [−2% to −1%]) and higher risk of LGA (OR, 1.85 [1.76-1.95]; ARD, 4% [2%-5%]), macrosomia (OR, 1.95 [1.79-2.11]; ARD, 6% [4%-9%]), and cesarean delivery (OR, 1.30 [1.25-1.35]; ARD, 4% [3%-6%]). Gestational diabetes mellitus could not be evaluated because of the nature of available data. Conclusions and Relevance In this systematic review and meta-analysis of more than 1 million pregnant women, 47% had gestational weight gain greater than IOM recommendations and 23% had gestational weight gain less than IOM recommendations. Gestational weight gain greater than or less than guideline recommendations, compared with weight gain within recommended levels, was associated with higher risk of adverse maternal and infant outcomes.
TL;DR: A computer‐assisted classification method combining conventional MRI and perfusion MRI is developed and used for differential diagnosis and consists of several steps including region‐of‐interest definition, feature extraction, feature selection, and classification.
Abstract: The objective of this study is to investigate the use of pattern classification methods for distinguishing different types of brain tumors, such as primary gliomas from metastases, and also for grading of gliomas. The availability of an automated computer analysis tool that is more objective than human readers can potentially lead to more reliable and reproducible brain tumor diagnostic procedures. A computer-assisted classification method combining conventional MRI and perfusion MRI is developed and used for differential diagnosis. The proposed scheme consists of several steps including ROI definition, feature extraction, feature selection and classification. The extracted features include tumor shape and intensity characteristics as well as rotation invariant texture features. Feature subset selection is performed using Support Vector Machines (SVMs) with recursive feature elimination. The method was applied on a population of 102 brain tumors histologically diagnosed as metastasis (24), meningiomas (4), gliomas WHO grade 2 (22), gliomas WHO grade 3 (18), and glioblastomas (34). The binary SVM classification accuracy, sensitivity, and specificity, assessed by leave-one-out cross-validation, were respectively 85%, 87%, and 79% for discrimination of metastases from gliomas, and 88%, 85%, and 96% for discrimination of high grade (grade III and IV) from low grade (grade II) neoplasms. Multi-class classification was also performed via a one-versus-all voting scheme.
Showing all 8133 results
|Sang Yup Lee||117||1005||53257|
|Kam W. Leong||109||601||45031|
|Jin Yong Lee||107||757||55220|
|Albert J. Fornace||106||403||40889|
|Surendra P. Shah||99||710||32832|
|Jong Seung Kim||97||502||36410|
|Jonathan C. Knowles||78||462||21683|
|Jon A. Jacobson||64||267||11007|
|Tae Il Kim||60||553||16591|
|Subhas C. Kundu||60||241||15487|
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