Microencapsulation of imidazole curing agent by solvent evaporation method using W/O/W emulsion

The epoxy–imidazole resin system is used to form the anisotropic conducting film. The latent character of the system is very significant. In this study, imidazole (Im) or 2‐methylimidazole (2MI) was encapsulated for the latent curing system to use in the reaction of epoxy resin. Polycaprolactone was used as a wall material, and the solvent evaporation method was used to form the microcapsule using W/O/W emulsion. The shelf life of the microcapsules was studied for the epoxy resin, and the curing behavior of the microcapsules for epoxy resin was examined using a differential scanning calorimeter. The curing times at 150 and 180°C were estimated using an indentation method. The microcapsules of Im or 2MI exhibited a long shelf life for epoxy resin. When comparing the results of the previous methods with the results of this study using the W/O/W emulsion, finer microcapsules were formed and the microcapsule has longer shelf life. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98341/1/38767_ftp.pd

A Two-Dimensional Framework for RFID Adoption and Diffusion: Strategic Implications for Developing Countries

Although there has been a growing interest in studying RFID in various application areas, little research has been undertaken to address applications in developing countries. Among the research that has been undertaken in developing countries, organizational perspectives have received considerable attention but less has been undertaken from other perspectives such as industry and country level. In this paper, a literature study of RFID adoption from different perspectives is presented and focuses on the stages of adoption, level of analysis, and issues of developing countries. A stage-scale (2S) framework is proposed to help identify relevant success factors in RFID adoption and diffusion, as well as its relation to other factors. It is concluded that the proposed framework is useful in providing a broad view of RFID adoption and in observing the dynamic changes in RFID issues from different stages, which is useful for policy and decision makers. Based on this framework, most factors of RFID adoption in developing countries fall within the preliminary stage, while the factors that are shared with developed countries are mostly situated in intermediate stages

A multi-criteria performance study of an integrated demand/supply energy system for low and zero carbon technologies within domestic building design

When low carbon and renewable energy (RE) systems are adopted in a building, matching the outputs from RE systems (e.g. photovoltaic, solar collectors, small scale wind turbines and heat pumps) to demand has to be taken into account to fully realise the potential of the hybrid energy system. Considering the varying demand profiles due to different building design options (e.g. orientation, construction types etc), it is necessary to evaluate key technology elements in an integrated context and establish appropriate strategies for simultaneously meeting heating and electricity loads as well as matching demand and supply. This paper presents a new approach to evaluate the interactive effects of low carbon technologies and demand reduction measures in the early design stage of a new building. A case study of a sustainable domestic building project (PLUS 50), was implemented on the basis of the proposed design approach

Deep Learning-based Synthetic High-Resolution In-Depth Imaging Using an Attachable Dual-element Endoscopic Ultrasound Probe

Endoscopic ultrasound (EUS) imaging has a trade-off between resolution and penetration depth. By considering the in-vivo characteristics of human organs, it is necessary to provide clinicians with appropriate hardware specifications for precise diagnosis. Recently, super-resolution (SR) ultrasound imaging studies, including the SR task in deep learning fields, have been reported for enhancing ultrasound images. However, most of those studies did not consider ultrasound imaging natures, but rather they were conventional SR techniques based on downsampling of ultrasound images. In this study, we propose a novel deep learning-based high-resolution in-depth imaging probe capable of offering low- and high-frequency ultrasound image pairs. We developed an attachable dual-element EUS probe with customized low- and high-frequency ultrasound transducers under small hardware constraints. We also designed a special geared structure to enable the same image plane. The proposed system was evaluated with a wire phantom and a tissue-mimicking phantom. After the evaluation, 442 ultrasound image pairs from the tissue-mimicking phantom were acquired. We then applied several deep learning models to obtain synthetic high-resolution in-depth images, thus demonstrating the feasibility of our approach for clinical unmet needs. Furthermore, we quantitatively and qualitatively analyzed the results to find a suitable deep-learning model for our task. The obtained results demonstrate that our proposed dual-element EUS probe with an image-to-image translation network has the potential to provide synthetic high-frequency ultrasound images deep inside tissues.Comment: 10 pages, 9 figure