The emerging business of science in Vietnam

Manh-Tung Ho, Khanh-Linh Hoang, Minh-Hoang Nguyen, Manh-Toan Ho (2019). Chapter 8. The emerging business of science in Vietnam. In Quan-Hoang Vuong, Trung Tran (Eds.), The Vietnamese Social Sciences at a Fork in the Road (pp. 163–177). Warsaw, Poland: De Gruyter. DOI:10.2478/9783110686081-013. Online ISBN: 9783110686081 © 2019 Sciendo / De Gruyte

Packaging for a drug delivery microelectromechanical system

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2005.Includes bibliographical references (p. 52-55).Local drug delivery is a fast expanding field, and has been a center of attention for researchers in medicine in the last decade. Its advantages over systemic drug delivery are clear in cancer therapy, with localized tumors. A silicon microelectromechanical drug delivery device was fabricated for the purpose of delivering chemotherapeutic agents such-as carmustine, a potent brain cancer drug, directly to the site of the tumor. Limitations in the delivery capacity of the device led to the design of a new package. This package is made from thermally bonded Pyrex® 7740 frames that are anodically bonded to the drug delivery chip. It increases the capacity of the chip, is smaller than the previous package and possesses true hermeticity, because of the bonding processes involved. This work describes the fabrication steps of the new package and a problem with the thermal bonding of Pyrex® frames preventing the achievement of a package true to the original design. A temporary solution was devised and the completed package was tested with regards to its intended goals. It managed to increase the load capacity of the chip by a, factor of 10, with potential for more, while decreasing the overall size of the package. Short-term hermeticity was achieved for this package by using a UV-cured epoxy to bond some pieces, which was not in the original design. Future work will focus on finding a permanent solution to the aforementioned problem, and directions for it were suggested.by Hong Linh Ho Duc.S.M

Reconstruction of Multidecadal Country-Aggregated Hydro Power Generation in Europe Based on a Random Forest Model

Hydro power can provide a source of dispatchable low-carbon electricity and a storage solution in a climate-dependent energy mix with high shares of wind and solar production. Therefore, understanding the effect climate has on hydro power generation is critical to ensure a stable energy supply, particularly at a continental scale. Here, we introduce a framework using climate data to model hydro power generation at the country level based on a machine learning method, the random forest model, to produce a publicly accessible hydro power dataset from 1979 to present for twelve European countries. In addition to producing a consistent European hydro power generation dataset covering the past 40 years, the specific novelty of this approach is to focus on the lagged effect of climate variability on hydro power. Specifically, multiple lagged values of temperature and precipitation are used. Overall, the model shows promising results, with the correlation values ranging between 0.85 and 0.98 for run-of-river and between 0.73 and 0.90 for reservoir-based generation. Compared to the more standard optimal lag approach the normalised mean absolute error reduces by an average of 10.23% and 5.99%, respectively. The model was also implemented over six Italian bidding zones to also test its skill at the sub-country scale. The model performance is only slightly degraded at the bidding zone level, but this also depends on the actual installed capacity, with higher capacities displaying higher performance. The framework and results presented could provide a useful reference for applications such as pan-European (continental) hydro power planning and for system adequacy and extreme events assessments

The scinderin gene (SCIN) is the direct target of miR3085-3p in chondrocytes

MiR-3085-3p was shown to play a crucial role in cartilage biology, with potential impacts in osteoarthritis (OA). Insight into this miRNA function could be of practical importance for future miRNA-based therapy, however, little is known regarding the biological roles of this miRNA. The physiologic function of an individual miRNA is dictated through its mRNA targets, and as SCIN (scinderin, also known as adseverin) was reported to be involved in chondrocyte differentiation, maturation, and phenotype maintenance, this study aimed to prove SCIN is a direct target of miRNA- 3085-3p. Bioinformatics algorithms were utilized for predicting their interacting sites. Gain- and loss of- function experiments with miRNA-3085-3p were performed and SCIN expression was measured by real-time RT-PCR. SCIN 3'UTR regions harboring either the miR-3085-3p seed site or its mutant version were cloned into pmirGLO downstream of a reporter firefly luciferase encoding gene. The effect of miR-3085-3p on this region was determined by the luciferase assay. Four binding sites of miR-3085- 3p in SCIN 3'UTR were identified. SCIN expression level was found to be inversely correlated with the level of miRNA-3085-3p. MiR3085-3p directly binds to its binding sites in SCIN 3' UTR. These data suggest that SCIN is the direct target of miR-3085-3p in chondrocyte cells

Scrambling for higher metrics in the Journal Impact Factor bubble period: a real-world problem in science management and its implications

Universities and funders in many countries have been using Journal Impact Factor (JIF) as an indicator for research and grant assessment despite its controversial nature as a statistical representation of scientific quality. This study investigates how the changes of JIF over the years can affect its role in research evaluation and science management by using JIF data from annual Journal Citation Reports (JCR) to illustrate the changes. The descriptive statistics find out an increase in the median JIF for the top 50 journals in the JCR, from 29.300 in 2017 to 33.162 in 2019. Moreover, on average, elite journal families have up to 27 journals in the top 50. In the group of journals with a JIF of lower than 1, the proportion has shrunk by 14.53% in the 2015–2019 period. The findings suggest a potential ‘JIF bubble period’ that science policymaker, university, public fund managers, and other stakeholders should pay more attention to JIF as a criterion for quality assessment to ensure more efficient science management

Implementing education reforms: a multiple case study of Vietnamese primary schools

This study investigates the implementation of Vietnam's Fundamental and Comprehensive Education Reform (FCER) through the theoretical lens of Complex Adaptive System Theory (CAST). While focusing on the Vietnamese context, it touches on a significant global issue in education: the challenge of implementing change. The study examines how the FCER's centralised-decentralisation approach in whole-system reforms which attempts to balance national educational goals with local autonomy might offer useful insights for reform implementation efforts worldwide. Using a qualitative, multiple-case study approach, the study investigates three primary public schools in Central and Southern Vietnam. The schools are selected to represent diverse contexts in geography, socioeconomic background, and school size. This variety allows for an understanding of how different educational contexts respond to system-level reform policies. Research methods include interviews with school leaders and teachers, observations, and analysis of documents, including national policies, textbooks, and school-level documents. The findings in selected schools indicate widespread compliance among educators with higher authorities' decisions to enact innovative practices. This system-level adoption brought some benefits, such as creating an initial momentum for change and reducing costs associated with change. However, as the FCER policies were gradually implemented, educators displayed more complex nuances in their interpretations and responses. While there were attempts to implement innovative practices, such as learner-centred pedagogy, formative assessments, the lesson-study model, and school councils, there was a tendency for these practices to be oversimplified and not fully integrated into schools' routines. The gaps between reality and the ideal were more significant in disadvantaged settings where aspects of schooling such as class size, facilities, teaching materials, students’ backgrounds, and parents’ collaboration were more challenging to address. Empirical evidence from this study supports the usefulness of CAST as an analytical framework for studying reform efforts. Additionally, the study proposes original concepts, namely, Zone of Feasible Practices (ZFP), Zone of Expected Practices (ZEP) and Buffering Zone (BZ). These concepts contribute to the development of CAST, enabling more accessible and actionable implications of the theory in the field of educational change and reform. In conclusion, the study highlights that the centralised-decentralisation approach in whole-system reforms could be an effective way to achieve consistency while allowing schools to develop ownership of the reforms and adapt to their local contexts. However, the effectiveness of this approach diminishes if schools are not adequately supported to develop their capacity for local adaptations. Without timely, concrete and context-sensitive guidance and support, schools and educators could be overwhelmed with additional responsibilities, causing frustration and limited transformations. The study advocates for an Adaptive Implementation Approach to complement the centralised-decentralisation strategy in whole-system reforms. This approach encourages collaboration between schools, higher authorities and other stakeholders in the community in tailoring reform objectives and pathways, taking account of the diverse and evolving contexts of schools

Optimization of a dual ring antenna by means of artifcial neural network

In literature, heuristic algorithms have been successfully applied to a number of electromagnetic problems. The associated cost functions are commonly linked to full-wave analysis, leading to complexity and high computational expense. Arti-cial Neural Network is one of the most e®ective biological inspired techniques. In this article, an e±cient surrogate model is trained to replace the full-wave analysis in optimizing the bandwidth of microstrip antenna. The numerical comparison between ANN substitution model and full-wave characterization shows signi-cant improvements in time convergence and computational cost. To verify the robustness of this approach, all these concepts are integrated into a case study represented by a rectangular ring antenna with proximity-coupled feed antenna

Design and analysis of a displacement sensor-integrated compliant microgripper based on parallel structure

This study evaluates the displacement sensitivity of a new compliant microgripper. The microgripper is designed based on a four-bar mechanism and the concept of a compliant mechanism. The effects of the width of the right circular hinge, the thickness of microgripper, and the material properties on the dis-placement sensitivity are considered via using the finite element method. In the beginning, the stress and deformation of the compliant microgripper are evaluated. Subsequently, the displacement of the microgripper is then analyzed. The results showed that the design parameter and the displacement sensitivity have a close relationship. To increase the grasping reliability and measure the displacement or force, a micro-displacement sensor is integrated with the proposed microgripper. Finally, the modeling and analysis of the proposed sensor are conducted

Hybridization strategy for microstrip antenna optimization

In the exploding growth of radio mobile and wireless communication applications, microstrip antennas with its advantages of low cost and flexible fabrications, emerge as the most suitable candidate. The direct antenna synthesis could, however do not result in the optimal antenna configuration, and therefore a possible alternative is considering the problem of optimizing the antenna as a system of uncertainty, in which each set of geometrical parameters returns a totally different response; the best set, i.e. the one that gives the best antenna performances, can be obtained using global optimizers, as evolutionary algorithms. The main drawback of this approach is that it is really time and memory consuming. In this article, a technique based on the hybridization between Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)is introduced with the aim of reducing this nimerical cost and implemented to optimize a dual-annular ring proximity coupled feed antenna