Confronting Shifting Identities: Reflections on Subjectivity in Transnational Research

As researchers’ identities impact the research process, researchers need to take a reflexive stance toward their positionality in the research. The issue of positionality is especially important for research focusing on multicultural issues, which necessarily involves dynamic power relations among different racial/ethnic groups. Drawing from reflections on my research focusing on South Korean adolescents’ understandings of migrants, this paper illustrates when and how I confronted my positionality. My positionality as a racial/ethnic minority in the United States affected the process of selecting the research topic and the theoretical framework as well as analyzing interview data while my positionality as an ethnic Korean was salient when making interview questions, interviewing ethnic Korean adolescents, and reporting the findings. There was also a moment in which my identity as an international student from the United States outweighed my ethnic/racial identity during interviews. By sharing my experiences in conducting transnational research in my home country, this paper attempts to contribute to underrepresented discourse on the use of reflexivity in non-Western societies, especially when neither the researcher nor the researched is White

Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph

As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort, and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a system call graph that consists of system calls found in the execution of the individual malware families. To explore distinguishing features of various malware species, we study social network properties as applied to the call graph, including the degree distribution, degree centrality, average distance, clustering coefficient, network density, and component ratio. We utilize features driven from those properties to build a classifier for malware families. Our experimental results show that influence-based graph metrics such as the degree centrality are effective for classifying malware, whereas the general structural metrics of malware are less effective for classifying malware. Our experiments demonstrate that the proposed system performs well in detecting and classifying malware families within each malware class with accuracy greater than 96%.Comment: Mathematical Problems in Engineering, Vol 201

Recent Progresses in <em>Ab Initio</em> Electronic Structure Calculation toward Understandings of Functional Mechanisms of Biological Macromolecular Systems

In this chapter, we present recent advances of theoretical analyses toward understandings of functional mechanisms of biological macromolecular systems, employing ab initio electronic structure calculations. Two distinct types of triggers to invoke dramatic rearrangements of electronic structures in the reaction centers are revealed by full ab initio quantum mechanics (QM) calculations (first example) and hybrid ab initio QM/molecular mechanics (MM) molecular dynamics (MD) calculations (second example). First, we demonstrate dramatic rearrangements of molecular orbitals (MOs) induced by binding of a hydroxyl ion (OH−) to the [4Fe-3S] cluster found in hydrogenases, which catalyzes both dissociation and production of dihydrogen (H2). This induces the significant delocalization of the LUMO, resulting in formation of electron transfer pathways required for the catalysis. Thus, in organisms, just a tiny species (e.g. OH− ligand) can play a key role for the biological functions. Second, we indicate dynamical rearrangements of MOs occurring in the enzymatic reactions of RNA-protein complexes. As the catalysis proceeds, the reactive MOs, which do not belong to the frontier orbitals in the initial stages of the reaction, are dramatically reconstituted in the hybrid ab initio QM/MM MD simulations, resulting in the frontier orbitals, which is a feature characteristic to biological macromolecular systems

Biological Applications of Hybrid Quantum Mechanics/Molecular Mechanics Calculation

Since in most cases biological macromolecular systems including solvent water molecules are remarkably large, the computational costs of performing ab initio calculations for the entire structures are prohibitive. Accordingly, QM calculations that are jointed with MM calculations are crucial to evaluate the long-range electrostatic interactions, which significantly affect the electronic structures of biological macromolecules. A UNIX-shell-based interface program connecting the quantum mechanics (QMs) and molecular mechanics (MMs) calculation engines, GAMESS and AMBER, was developed in our lab. The system was applied to a metalloenzyme, azurin, and PU.1-DNA complex; thereby, the significance of the environmental effects on the electronic structures of the site of interest was elucidated. Subsequently, hybrid QM/MM molecular dynamics (MD) simulation using the calculation system was employed for investigation of mechanisms of hydrolysis (editing reaction) in leucyl-tRNA synthetase complexed with the misaminoacylated tRNALeu, and a novel mechanism of the enzymatic reaction was revealed. Thus, our interface program can play a critical role as a powerful tool for state-of-the-art sophisticated hybrid ab initio QM/MM MD simulations of large systems, such as biological macromolecules

Effects of a multi-herbal extract on type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>An aqueous extract of multi-hypoglycemic herbs of <it>Panax ginseng </it>C.A.Meyer, <it>Pueraria lobata, Dioscorea batatas Decaisne, Rehmannia glutinosa, Amomum cadamomum Linné, Poncirus fructus </it>and <it>Evodia officinalis </it>was investigated for its anti-diabetic effects in cell and animal models.</p> <p>Methods</p> <p>Activities of PPARγ agonist, anti-inflammation, AMPK activator and anti-ER stress were measured in cell models and in <it>db/db </it>mice (a genetic animal model for type 2 diabetes).</p> <p>Results</p> <p>While the extract stimulated PPARγ-dependent luciferase activity and activated AMPK in C2C12 cells, it inhibited TNF-α-stimulated IKKβ/NFkB signaling and attenuated ER stress in HepG2 cells. The <it>db/db </it>mice treated with the extract showed reduced fasting blood glucose and HbA_1clevels, improved postprandial glucose levels, enhanced insulin sensitivity and significantly decreased plasma free fatty acid, triglyceride and total cholesterol.</p> <p>Conclusion</p> <p>The aqueous extract of these seven hypoglycemic herbs demonstrated many therapeutic effects for the treatment of type 2 diabetes in cell and animal models.</p