Institution
Chung-Ang University
Education•Seoul, South Korea•
About: Chung-Ang University is a education organization based out in Seoul, South Korea. It is known for research contribution in the topics: Population & Thin film. The organization has 13381 authors who have published 26978 publications receiving 416735 citations. The organization is also known as: CAU & Chung.
Topics: Population, Thin film, Medicine, Cancer, Apoptosis
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors identify and analyze major factors for knowledge sharing among faculty members in a higher educational institution in order to examine how those factors influence campus wide knowledge sharing and investigate the way in which those factors are interrelated.
239 citations
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TL;DR: G*Power as mentioned in this paper is a free software that supports sample size and power calculation for various statistical methods (F, t, χ2, Z, and exact tests) and is easy to use and free.
Abstract: Appropriate sample size calculation and power analysis have become major issues in research and publication processes. However, the complexity and difficulty of calculating sample size and power require broad statistical knowledge, there is a shortage of personnel with programming skills, and commercial programs are often too expensive to use in practice. The review article aimed to explain the basic concepts of sample size calculation and power analysis; the process of sample estimation; and how to calculate sample size using G*Power software (latest ver. 3.1.9.7; Heinrich-Heine-Universitat Dusseldorf, Dusseldorf, Germany) with 5 statistical examples. The null and alternative hypothesis, effect size, power, alpha, type I error, and type II error should be described when calculating the sample size or power. G*Power is recommended for sample size and power calculations for various statistical methods (F, t, χ2, Z, and exact tests), because it is easy to use and free. The process of sample estimation consists of establishing research goals and hypotheses, choosing appropriate statistical tests, choosing one of 5 possible power analysis methods, inputting the required variables for analysis, and selecting the “calculate” button. The G*Power software supports sample size and power calculation for various statistical methods (F, t, χ2, z, and exact tests). This software is helpful for researchers to estimate the sample size and to conduct power analysis.
238 citations
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TL;DR: This article provides an easy introduction to clinicians on performing and understanding meta-analyses and can be dangerous in accepting the conclusions of many studies without understanding the meta-analysis.
Abstract: Systematic reviews and meta-analyses present results by combining and analyzing data from different studies conducted on similar research topics. In recent years, systematic reviews and meta-analyses have been actively performed in various fields including anesthesiology. These research methods are powerful tools that can overcome the difficulties in performing large-scale randomized controlled trials. However, the inclusion of studies with any biases or improperly assessed quality of evidence in systematic reviews and meta-analyses could yield misleading results. Therefore, various guidelines have been suggested for conducting systematic reviews and meta-analyses to help standardize them and improve their quality. Nonetheless, accepting the conclusions of many studies without understanding the meta-analysis can be dangerous. Therefore, this article provides an easy introduction to clinicians on performing and understanding meta-analyses.
237 citations
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TL;DR: This review provides an overview of various methods of chemical and physical crosslinking using different linkers that have been investigated to develop the mechanical properties, biodegradation, and biocompatibility of hyaluronic acid as an injectable hydrogel in cell scaffolds, drug delivery systems, and wound healing applications.
Abstract: In the field of tissue engineering, there is a need for advancement beyond conventional scaffolds and preformed hydrogels. Injectable hydrogels have gained wider admiration among researchers as they can be used in minimally invasive surgical procedures. Injectable gels completely fill the defect area and have good permeability and hence are promising biomaterials. The technique can be effectively applied to deliver a wide range of bioactive agents, such as drugs, proteins, growth factors, and even living cells. Hyaluronic acid is a promising candidate for the tissue engineering field because of its unique physicochemical and biological properties. Thus, this review provides an overview of various methods of chemical and physical crosslinking using different linkers that have been investigated to develop the mechanical properties, biodegradation, and biocompatibility of hyaluronic acid as an injectable hydrogel in cell scaffolds, drug delivery systems, and wound healing applications.
236 citations
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TL;DR: A new 8-hydroxyquinoline derivative having an appended boron-dipyrromethene function has been prepared, and its metal ion sensing properties were investigated, and it exhibited pronounced Hg(2+)-selective on-off-type fluoroionophoric properties among the representative transition- and heavy-metal ions in aqueous dioxane solution.
Abstract: A new 8-hydroxyquinoline derivative having an appended boron−dipyrromethene function has been prepared, and its metal ion sensing properties were investigated. The designed compound exhibited pronounced Hg2+-selective on−off-type fluoroionophoric properties among the representative transition- and heavy-metal ions in aqueous dioxane solution. The fluorescence was efficiently quenched more than 98% with 5 equiv of Hg2+ ions, and the detection limit was found to be 5 × 10-6 M in a dioxane−water (1:3, v/v) solvent system. The ionophore also showed a selective chromogenic behavior toward Hg2+ ions by changing the color of the solution from light amber to red, which can be detected with the naked eye.
236 citations
Authors
Showing all 13500 results
Name | H-index | Papers | Citations |
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Carl Nathan | 135 | 430 | 91535 |
Scheffer C.G. Tseng | 93 | 333 | 29213 |
Richard L. Sidman | 93 | 297 | 32009 |
H. Yamaguchi | 90 | 375 | 33135 |
Ajith Abraham | 86 | 1113 | 31834 |
Byung Ihn Choi | 78 | 609 | 24925 |
Stefano Soatto | 78 | 499 | 23597 |
J. H. Kim | 73 | 566 | 23052 |
Daehee Kang | 72 | 422 | 23959 |
Lance M. McCracken | 72 | 281 | 18897 |
Masanobu Shinozuka | 69 | 456 | 21961 |
Seung U. Kim | 64 | 355 | 14269 |
Sug Hyung Lee | 64 | 454 | 21552 |
Seung U. Kim | 63 | 129 | 11983 |
Nam Jin Yoo | 63 | 403 | 12692 |