Master of Science

thesisAs the identification of new targets for therapeutic intervention that might attenuate cardiovascular complications associated with type 2 diabetes are needed, our lab conducted a prior study to address that need. We reported at that time that mice treated with a potent and selective small molecule inhibitor (LB1; Lixte Biotechnology Holdings, Inc., East Setauket, NY; 1 mg/kg IP; intraperitoneal) of protein phosphatase 2A (PP2A) for the last 14 days of an obesogenic diet (12 weeks of fat-feeding) did not display vascular PP2A hyperactivation, endothelial dysfunction, or hypertension that otherwise developed in fat-fed mice treated with vehicle. We concluded that PP2A hyperactivation should be considered further as a therapeutic target for intervention. While our investigation was in progress, results from another study indicated that 2 -mg/kg LB1 IP (3 hr) evoked hyperglycemia, glucose intolerance, and hepatic glycogen depletion in chow-fed and fat-fed (3 days) rats. The authors concluded that targeting PP2A hyperactivation should not be considered as a therapeutic intervention. Based on the incongruent conclusions from these two studies, we conducted a new research study, testing the following hypotheses-that LB1 treatment for 14-days impairs: (i) peripheral; glucose homeostasis; (ii) hepatic glycogen content; and (iii) insulin-mediated signal; transduction in the liver. The first two hypotheses were tested using 7-week old male C57BL/6J mice who consumed standard (Con) or high fat (HF) chow for 12 weeks. Subgroups of Con and HF mice received 1 mg/kg LB1 or saline (Veh) IP for the last 14 days of testing. Glucose and insulin tolerance testing indicated that LB1 treatment does not impair peripheral glucose homeostasis in Con mice or HF mice, denying the first hypothesis. Regarding second hypothesis, LB1 treatment did not lower hepatic glycogen content, p-Akt2S474 / Akt2, p-Gsk3ɑS21 / Gsk3ɑβ, or p-GSS641 / GS, in lean or obese mice under basal, random-fed conditions. To test the third hypothesis, age-matched male mice that consumed standard chow were treated with LB1 or Veh for 14 days. On day 15, after a 6-hr fast, insulin or saline was administered (i.v. intravenous) to anesthetized mice, and segments of liver were collected to assess p-Akt2S474 / Akt2, p-GSK3ɑS21 / GSK3ɑ, and p-GSS641 / GS. Insulin-mediated signal transduction in the liver was similar regardless of LB1 treatment. We conclude that LB1 treatment in mice for 14-days does not impair: (i) peripheral glucose homeostasis; (ii) hepatic glycogen content; or (iii) insulin-mediated; signal transduction in the liver

English Language Learning Strategies Reported By Advanced Language Learners

The purpose of the present study is to investigate effective English language learning strategies (LLSs) employed by successful language learners. The participants in this study were 20 student interpreters enrolled in the graduate school of interpretation and translation in Korea. Data on LLSs were collected through unstructured essay writing, a method employed to encourage participants to freely reflect on their language learning experiences and report what strategies and study methods helped them develop a high level of English proficiency. Qualitative data analysis produced several findings related to the use of learning strategies. Specifically, metacognitive strategies, such as disciplined approach to language learning and monitoring of progress, and cognitive strategies, such as reading-aloud and text analysis, were frequently mentioned as effective strategies. In addition, a number of participants emphasized the importance of conscious attention to language input during language learning activities. Testimonies of advanced English language learners in an English as a Foreign Language (EFL) context suggest that learner autonomy manifested in self-regulated learning activities may be crucial for successful foreign language learning. These and other findings are discussed with respect to their pedagogical implications for strategy-based instruction in English education

Synergistic effect of lithium difluoro(bisoxalato) phosphate and propionitrile for Li-ion batteries with high discharge rate capability

Department of Energy Engineering (Battery Science and Technology)Lithium-ion batteries (LIBs) have been widely used for various electronic devices from small electronics to power tools, electronic vehicles (EVs) and energy storage systems (ESS), taking advantages of their high capacity and efficiency featuring its lighter weight and higher energy density than the other batteries. Furthermore, the studies on LIB are working to broaden its application field as one of the leading candidates to resolve the environmental issues on greenhouse gas, typically CO2 gas as well as due to its convenience. To expand the usage of LIBs, however, there are several issues to be overcome such as poor rate capability according to the effort to increase the energy density by using high-loading electrodes and so on. In this study, propionitrile (PN, H5C2-CN) and lithium difluoro(bisoxalato) phosphate (LiDFBP) are introduced to enhance high discharge rate capability for LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode and Si-containing graphite (Si-C) anode in lithium-ion batteries. The research reveals that the use of propionitrile as a cosolvent improved the mobility of lithium ions in the electrolyte. However, the irreversible capacity loss after the discharge rate test and the drastic decrease in the cycling test at high temperatures occur. To overcome this deterioration, LiDFBP as a lithium salt type electrolyte additive is adopted to form stable cathode-electrolyte interphase. Electrochemical tests proved that the LiDFBP effectively decreases the amounts of the byproduct of PN on the NCM811 cathode, improving the capacity recovery after discharge rate test and enabling the reversible cycling with capacity retention from 26.6% (LiDFBP-free PN) to 78.5% after 50 cycles at 0.5C rate at 45oC. The synergistic effect of PN cosolvent and LiDFBP additive is contact angle, XPS, SEM, and XRD analyses.clos

Assessing the Impact of Open and Closed Knowledge Sourcing Approach on Innovation in Small and Medium Enterprises

AbstractThere is very limited research on open innovation in small and medium enterprises (SMEs). By drawing on complementarity theory and knowledge based theory, this study develops three hypotheses in order to identify the impact of knowledge sourcing approaches for innovation on SMEs’ innovation performance. Surveys collected from 196 SMEs in Korea were analyzed to test the hypotheses by using supermodularity function. The results indicate no significant impact of external knowledge-oriented approach while positive impact of internal knowledge-oriented (i.e., closed approach) on innovation performance. Interestingly, this study finds that open innovation has significant negative impact on SMEs’ innovation performance (i.e., both internal knowledge- and external knowledge-oriented approaches have a substitutive relationship). This study sheds new light on open innovation and knowledge management research by identifying the relationships between knowledge sourcing approaches for innovation and innovation performance in SMEs

The GitHub Recent Bugs Dataset for Evaluating LLM-based Debugging Applications

Large Language Models (LLMs) have demonstrated strong natural language processing and code synthesis capabilities, which has led to their rapid adoption in software engineering applications. However, details about LLM training data are often not made public, which has caused concern as to whether existing bug benchmarks are included. In lieu of the training data for the popular GPT models, we examine the training data of the open-source LLM StarCoder, and find it likely that data from the widely used Defects4J benchmark was included, raising the possibility of its inclusion in GPT training data as well. This makes it difficult to tell how well LLM-based results on Defects4J would generalize, as for any results it would be unclear whether a technique's performance is due to LLM generalization or memorization. To remedy this issue and facilitate continued research on LLM-based SE, we present the GitHub Recent Bugs (GHRB) dataset, which includes 76 real-world Java bugs that were gathered after the OpenAI data cut-off point

Open Innovation Maturity Model for the Government: An Open System Perspective

To meet the increasing expectations of citizens, governments have become increasingly open, transparent, accessible and consultative to deliver efficient public services. These trends can be fulfilled through open government data provision and usage. Governments can generate social and economic values by using data-driven open innovation processes, such as by adopting citizens’ ideas or knowledge related to open data and by providing government data to the public. Despite the trends of open innovation in the context of government, research on open innovation is lacking. Furthermore, most studies disregard the differences of countries in the level of open innovation maturity of open data provision and usage. Therefore, this study aims to understand data-driven open innovation practices in government by developing a government-level open innovation maturity model, evaluating the current status of open innovation of the government, and suggesting appropriate future directions and guidelines for the government

Advancing Bayesian Optimization via Learning Correlated Latent Space

Bayesian optimization is a powerful method for optimizing black-box functions with limited function evaluations. Recent works have shown that optimization in a latent space through deep generative models such as variational autoencoders leads to effective and efficient Bayesian optimization for structured or discrete data. However, as the optimization does not take place in the input space, it leads to an inherent gap that results in potentially suboptimal solutions. To alleviate the discrepancy, we propose Correlated latent space Bayesian Optimization (CoBO), which focuses on learning correlated latent spaces characterized by a strong correlation between the distances in the latent space and the distances within the objective function. Specifically, our method introduces Lipschitz regularization, loss weighting, and trust region recoordination to minimize the inherent gap around the promising areas. We demonstrate the effectiveness of our approach on several optimization tasks in discrete data, such as molecule design and arithmetic expression fitting, and achieve high performance within a small budget

Evaluation Indicators for Priorities of Standardization in Traditional Medicine: using Analytic Hierarchy Process(AHP)

The entire manuscript is available for download as a single PDF file. Higher-resolution images are unavailable. For assistance, please contact [email protected]. Fieldwork Team: Philippe Beaujard (Director of Research, French National Centre for Scientific Research). Technical Team: Dr. Vika Zafrin (Digital Scholarship Librarian, BU Libraries), Eleni Castro (OpenBU and Electronic Theses & Dissertations Librarian, BU Libraries), Dr. Fallou Ngom (Director of the African Studies Center), Dr. Peter Quella (Assistant Director, African Studies Center), Mustapha Hashim Kurfi (PhD Candidate, Department of Political Science), and Zachary Gersten (Research Assistant, African Studies Center). This collection of Malagasy Ajami materials is copied as part of the African Studies Center’s African Ajami Library. This project is partly funded by the BU African Studies Center. We thank Dr. Tim Longman, past Director of the African Studies Center, and the entire African Studies team for their support. For Inquiries: Please contact Professor Fallou Ngom ([email protected]).The material is the fourth part of the second of two texts copied and owned by Jean, a diviner-healer (called ombiasy in Malagasy). Jean belonged to the Anakara Clan and lived in a village called Vatomasina in the Antemoro region (in the valley of the Matatàña River). The original author of the material is unknown. The material was photographed between 1983 and 1990. The material was written on paper school notebooks. While the exact content of material is unknown, it is believed to contain guidance for charms, divination, and healing through prayers, geomancy, and astrology

A multidimensional approach to wearability assessment of an electronic wrist bracelet for the criminal justice system

Electronic monitoring systems have been globally adopted to track criminals to ensure public safety efficiently. In this study, we aimed to assess the wearability of an electronic bracelet using multiple evaluation methods, including the evaluation of range of motion (ROM), air gap (AG), and clothing pressure (CP) at the wearer’s wrist, as well as self-scoring of subjective comfort (SC). We recruited eight Korean male participants (N = 8) who were in their 30 s and did not have any musculoskeletal problems at data collection. We compared the test results collected on the first day with those obtained after wearing the electronic wrist bracelet for 5 consecutive days. We also examined the differences between the normal-weight and overweight groups. Overall, the data evinced a decrease in the wrist ROM, AG, and SC, but an increase in the CP after it was worn for 5 days. And, the results were more observable in the overweight group, as compared to the normal-weight group. Furthermore, this study proposed a novel and effective assessment tool that could be used to measure the wearability of devices or systems intended to be worn on the human body—not only the electronic wrist bracelet for criminal monitoring but also popular commercial electronic bracelets for sportswear or health-related monitoring system.This work was supported by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0012770, Professional Human Resources Training Project), and the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (2016R1A5A1938472