1,047 research outputs found
Applications of functional dyes in biomedicine and life sciences
Functional dyes are useful tool in Biomedical and Life Sciences. In chapter 2 and 3, we introduced a general and simple design concept using unnatural amino acids (UAAs) as flexible scaffold to link organic fluorophore covalently to a photostabilizer on an arbitrary biomolecular target using only NHS- or click chemistry. With this method, chemically distinct fluorophore species that could not be studied before can be improved through intramolecular photostabilization as âself-healingâ fluorophores. . In chapter 4, we developed novel photoswitchable aminoglycosides, that we can call âOpto-Drugsâ, which can resist aminoglycoside-modifying enzymes while simultaneously demonstrating selective antibiotic activities upon visible light light irradiation. In chapter 5, we generate an artificial photoresponsive system based on genetically encoded aptameric RNA that can respond to photoisomerizable, cell-permeable small molecules
Being and Becoming: the Implications of Different Conceptualizations of Children and Childhood in Education
How to conceptualize children and childhood are intrinsic to the ways of understanding education. The âbecomingâ child is seen as an opposite or negative form of adults while the âbeingâ child is recognized as a social actor with the ability as well as rights to actively participate in its own life and in those of others. However, in addition to the problems of each discourse, such a dyad also leads to a separation of fundamental education factors. With reference to the Interpretative Reproduction Model and the concept of time, this paper discusses an alternative perspective on children and childhood that views the child as the âhuman becoming and beingâ concurrently, coupled with its associated implication on education. By doing so, the author hopes to provide a platform facilitating adult professionals, pre-service or in-service teachers, to reflect upon their attitudes towards students and the ways of understanding education
Factors Influencing Behavioral Intention Towards MOOC Platform of Jingdezhen Vocational University of Art Students Majoring in Art and Design in Jiangxi Province, China
The objective of this investigation was to analyze the behavioral intention of students at the Jingdezhen Vocational University of Art who majoring in art and design majors to use the MOOC platform. It was carried out by the researchers using quantitative research techniques. Based on the Theory of Reason and Action (TRA), the Technology Acceptance Model (TAM), and the Unified Theory of Technology Acceptance and Use (UTAUT), this study develops a conceptual framework. Seven potential variables were chosen to assess the validity of the research tool using project-goal consistency and passed the internal consistency test: self-efficacy, perceived ease of use, perceived usefulness, attitude, performance expectancy, subjective norm, and behavioral intention. The reliability was evaluated by Cronbach α coefficient through the pilot test. In addition, the sampling strategy was multi-stage sampling. In the course of the study, a face-to-face questionnaire was distributed to 500 professional undergraduates majoring in art and design with MOOC platform experience at the School of Ceramic Art and Design and the School of Digital Art of Jingdezhen Art Vocational University. As statistical analysis tools, confirmatory factor analysis and structural equation modeling were applied in this research to advance the influence on data, matrix accuracy, basic variables, hypothetical support, and path coefficients. The results revealed that all the hypotheses are suggested, and the subjective norm was the most influential factor that affected art and design majors' behavioral intention to use the MOOC platform
Junior High School Teachersâ Feedback Giving and Perceptions of the CSE Writing Scale
Chinese EFL learnersâ deficiencies in writing have become increasingly apparent in their secondary education, especially in the originality of ideas and the logic of arguments. However, they may not be made aware of this as many teachers still use traditional feedback such as a single score to mark and report on studentsâ performance. The Writing Scale of Chinaâs Standards of English Language Ability (hereinafter referred to as the CSE Writing Scale) released in 2018 provides a framework of reference against which Chinese studentsâ English writing ability can be assessed. It consists of descriptors of writing ability in different contexts and genres. It makes detailed and analytical feedbacking possible and has far-reaching implications for the development of formative assessment in English teaching. Nevertheless, to date, there has been scarce empirical research as to whether teachers actually use the Writing Scale in teaching and whether they are able to utilize it in an effective way.   This study aims to investigate the current situation of feedback giving in junior high school and teachersâ views of and attitudes towards the application of the CSE Writing Scale. Through a questionnaire and interviews with the teachers, the study revealed three major findings. Firstly, although teachers were aware of the importance of giving feedback on studentsâ writing, they had problem providing individualized comments on student writing. Secondly, students had difficulty understanding teachersâ feedback. Lastly, teachers were generally not familiar with the CSE Writing Scale and concerned whether it could be effectively used in the process of feedback giving. Conclusions are drawn together with implications and recommendations for teachers to resolve the problems identified.
Spectral Unsupervised Domain Adaptation for Visual Recognition
Unsupervised domain adaptation (UDA) aims to learn a well-performed model in
an unlabeled target domain by leveraging labeled data from one or multiple
related source domains. It remains a great challenge due to 1) the lack of
annotations in the target domain and 2) the rich discrepancy between the
distributions of source and target data. We propose Spectral UDA (SUDA), an
efficient yet effective UDA technique that works in the spectral space and is
generic across different visual recognition tasks in detection, classification
and segmentation. SUDA addresses UDA challenges from two perspectives. First,
it mitigates inter-domain discrepancies by a spectrum transformer (ST) that
maps source and target images into spectral space and learns to enhance
domain-invariant spectra while suppressing domain-variant spectra
simultaneously. To this end, we design novel adversarial multi-head spectrum
attention that leverages contextual information to identify domain-variant and
domain-invariant spectra effectively. Second, it mitigates the lack of
annotations in target domain by introducing multi-view spectral learning which
aims to learn comprehensive yet confident target representations by maximizing
the mutual information among multiple ST augmentations capturing different
spectral views of each target sample. Extensive experiments over different
visual tasks (e.g., detection, classification and segmentation) show that SUDA
achieves superior accuracy and it is also complementary with state-of-the-art
UDA methods with consistent performance boosts but little extra computation
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