ABSTRACT
Due to COVID-19 pandemic. Education systems all around the world had been forced to migrate from face-to-face education to online format by using digital platforms. In Japan, the shift to distance education was particularly challenging across the higher education sector due to lack of experience in conducting classes online, as well as the slow pace of the country education system to take up digital technology. The scope of the field of industrial design has been increasingly widening, including non-tangible products such as services, interfaces and experiences, among others. Additionally, CAD technology facilitates design distance learning. However, the core of industrial design remains in the development of proposals of physical products, especially in Japan where there is a very strong culture of monozukuri or “making of things”. Since the practice of industrial design cannot be taught solely by remote classes, this paper documents the attempt to carry out two hybrid courses with face-to-face lessons for physically building design proposals. In order to adapt to the academic conditions in the pandemic context, digital fabrication technology was utilized, specifically laser cutting machines. By using online communication platform students attended lectures, submitted design ideas, received professor feedback and built necessary data. During face-to-face lessons, students used laser cutting machine to make parts, built prototypes and received feedback. Surveys were applied at the end of each course, showing high level of satisfaction among students. This research aims to contribute to finding the most optimum balance point between online and face-to-face lessons for industrial design courses towards the “new normal” reality. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The outbreak of the coronavirus disease emphasized the need for fast and sensitive inhibitor screening tools for the identification of new drug candidates. In SARS-CoV-2, one of the initial steps in the infection cycle is the adherence of the receptor-binding domain (RBD) of the spike protein 1 (S1) to the host cell by binding to the angiotensin-converting enzyme 2 (ACE2) receptor. Therefore, inhibition of S1-ACE2 interaction may block the entry of the virus to the host cell, and thus may limit the spread of the virus in the body. We demonstrate a rapid and quantitative method for the detection and classification of different types of molecules as inhibitors or non-inhibitors of the S1-ACE2 interaction using magnetically modulated biosensors (MMB). In the MMB-based assay, magnetic beads are attached to the S1 protein and the ACE2 receptor is fluorescently labeled. Thus, only when the proteins interact, the fluorescent molecule is connected to the magnetic bead. To increase the sensitivity of fluorescence detection, the complex of magnetic beads and attached fluorescent molecules are aggregated by two opposing electromagnets and are moved from side to side in a periodic motion in and out of a laser beam, emitting a flashing signal that is collected by a digital camera. When an inhibitor interferes with the interaction, the signal is reduced. The MMB-based assay is much faster and has minimal non-specific binding than the commonly used ELISA. It can be adjusted to other interactions, and therefore can be utilized as a global tool for inhibitor screening. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.
ABSTRACT
As COVID-19 has increased the need for connectivity around the world, researchers are targeting new technologies that could improve coverage and connect the unconnected in order to make progress toward the United Nations Sustainable Development Goals. In this context, drones are seen as one of the key features of 6G wireless networks that could extend the coverage of previous wireless network generations. That said, limited onboard energy seems to be the main drawback that hinders the use of drones for wireless coverage. Therefore, different wireless and wired charging techniques, such as laser beaming, charging stations, and tether stations, are proposed. In this article, we analyze and compare these different charging techniques by performing extensive simulations for the scenario of drone-assisted data collection from ground-based Internet of Things devices. We analyze the strengths and weaknesses of each charging technique, and finally show that laser-powered drones strongly compete with, and outperform in some scenarios, other charging techniques.