It is believed that studies on the early hydroxyapatite (HAp) deposition on nano-sized substrates may possibly allow us to understand the formation mechanisms of biominerals at the molecular level. In this study, bacterial cellulose (BC) nanofibers were phosphorylated and used as nano-sized templates for early mineralization of calcium phosphate (Ca-P). To initiate mineralization the BC nanofibers were immersed in 1.5 times simulated body fluids (1.5 SBF) at 37 degreees C for varying periods of time. The deposited minerals on the nanofiber surfaces were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transformed infrared spectroscopy (FTIR). SEM observations confirmed that early growth (at 4 h) of the Ca-P minerals was heterogeneous, which was followed by extensive spread of the minerals on the entire surfaces of the nanofibers. XRD and FTIR analyses indicated that octacalcium phosphate (OCP) was the precursor of HAp formed on BC nanofibers. Furthermore, HAp deposited on BC nanofibers elongated along the c axis. Nucleation and growth of the Ca-P minerals were analyzed in this paper.
The onset of technological innovations (mobile and handhelds, virtual reality, multi-touch screens, and interactive 3D) have provided creative ideas and perspectives for online communication, dissemination, and protection of cultural heritage for costume museums. Digital costume museums (DCM) digitized clothing collections for the Internet, conducive to enhancing visitors’ understanding, enjoyment, and positive attitudes and stimulating further learning, experience, and exploration. However, little attention has been paid to the influence and effects of these technologies on visitors’ experience toward digital costume museums. Improving users’ behavior intention and expanding the influence of digital costume museums are issues that need further discussion. In this study, we expand the technology acceptance model (TAM) by adding information quality and information richness as the system characteristics, constructing the research model, and 11 hypotheses of users’ behavior intention toward digital costume museums. Analysis of data collected from 265 costume-related respondents reveal that information quality (IQ) positively influences perceived convenience (PC) and perceived ease of use (PEOU), while information richness (IR) has a positive impact on perceived usefulness (PU) and perceived playfulness (PP). The finding also reveals that perceived usefulness (PU) and perceived playfulness (PP) are significant predictors of users’ behavior intention (BI) toward using digital costume museums. The research conclusion enriches academic theories and brings practical inspiration for managers, curators, and practitioners to construct and innovate digital costume museums.
Purpose Today clothing has become the largest category in online shopping in China, and even in Asia-Pacific. The satisfaction degree of apparel online shopping can be improved by effective personalized recommendation. The purpose of this paper is to propose a personalized recommendation model and algorithm based on Kansei engineering, traditional filtering algorithm and the knowledge relating to apparel. Design/methodology/approach Users’ perceptual image and the design elements of apparel based on Kansei engineering are discussed to build the mapping relation between the design elements and user ratings employing verbal protocol, semantic differential and partial least squares. The implicit knowledge and emotional needs pertaining to users are accessed using analytic hierarchy process. A personalized recommendation model for apparel online shopping is established and the algorithm for the personalized recommendation process is proposed. To present the personalized recommendation model, men’s plaid shirts are taken as the example, and the recommendations of apparel for online shopping were implemented and ranked in the context of differing users’ emotional needs. A comparison between the traditional model and this model is made to verify the effectiveness. Findings The recommendation model is capable of analyzing data and information effectively, and providing fast, personalized apparel recommendation services in accordance with users’ emotional needs. The experimental results suggest that the model is effective. Originality/value Similar researches of recommendation mainly focus on the field of computer science, the basic idea of which is using users’ history accessing records or the preferences of other similar users for determination of users’ preferences. Since the attributes of apparel products are not factored in the approach referred above, the issue of personalized recommendation cannot be solved in a really effective way. Combining Kansei engineering and recommendation algorithm, a framework for apparel product recommendation is presented and it is a new way for improvement of recommendations for apparel products on shopping sites.
Digital museums that use modern technology are gradually replacing traditional museums to stimulate personal growth and promote cultural exchange and social enrichment. With the development and popularization of the mobile Internet, user experience has become a concern in this field. From the perspective of the dynamic stage of user experience, in this study, we expand ECM and TAM by combining the characteristics of users and systems, thereby, constructing the theoretical model and 12 hypotheses about the influencing factors of users’ continuance intentions toward digital museums. A total of 262 valid questionnaires were collected, and the structural equation model tested the model. This study identifies variables that play a role and influence online behavior in a specific experiential environment: (1) Perceived playfulness, perceived usefulness, and satisfaction are the critical variables that affect users’ continuance intentions. (2) Expectation confirmation has a significant influence on perceived playfulness, perceived ease of use, and satisfaction. (3) Media richness is an essential driver of confirmation, perceived ease of use, and perceived usefulness. The conclusions can be used as a reference for managers to promote the construction and innovation of digital museums and provide a better experience to meet users’ needs.
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