A Prediction Model for Remote Lab Courses Designed upon the Principles of Education for Sustainable Development

The COVID-19 pandemic brought about a cease to the physical-presence operation of many laboratory-based university courses. As a response, higher education courses turned into distance learning. Distance education can foster sustainability through resource savings offered by the benefits of technology use. Therefore, there is a necessity to establish a pathway for sustainability practices concerning the increasing distance education enrollment and technological progress. Under the previous concept, this research paper presents a remote lab for the "Data Acquisition Systems” course, delivered during the pandemic as the digital twin of its respective conventional lab. This remote lab was designed on the Education for Sustainable Development (ESD) principles to help students develop critical thinking, problem-solving, and collaboration competencies. This paper aims to develop a concrete framework for identifying factors that critically affect students' performance during remote lab courses. The analysis is based on students' engagement data collected by the NI-ELVIS remote lab measurement system during the spring academic semester of 2020 at the University of West Attica, Greece. Furthermore, the paper develops a competent prediction model for students at risk of failing the lab. The findings indicate that content comprehension and theory-exercise familiarization were the main risk factors in the case of the specific remote lab. In detail, a unit increase in content comprehension led to a 2.7 unit decrease in the probability of the risk occurrence. In parallel, a unit increase in theory familiarization through exercises led to a 3.2 unit decrease in the probability of the risk occurrence. The findings also underlined that risk factors such as critical thinking were associated with ESD competencies. Besides this, the benefits of delivering distance-learning labs according to the proposed methodology include environmental benefits by contributing to resource and energy savings since students who are about to fail can be located early and assisted. © 2023 by the authors.

3D Printing of an Advanced Design Emergency Mechanical Ventilator, in Response to the COVID 19 Pandemic

Additive manufacturing is a rapidly evolving technological field, beyond he simple application of 3D printers, leading to an entirely new means of designing and manufacturing objects, paving the way for novel and unexplored possibilities. It is currently used in the production of mechanical components and tooling, medical and surgical implants and, also, to facilitate surgical design. The advantages stemming from this technology should be facilitated to combat the COVID-19 pandemic. With cases of respiratory failure and respiratory distress globally soaring and unavailability of standard automated ventilators in certain regions, the need to meet this demand is crucial. In this context, the research team considered it appropriate to move towards finding a solution to the problem of shortage in respirators in health systems worldwide. Having originally received plans for 3D printing from the University of Illinois, which produced disposable mechanical respirators with this technology, the possibility of optimizing and producing them at UNIWA was explored. The CAD files were analyzed in order to evaluate their printability resulting in partial redesign in order to limit dimensional variability, acceptable surface finish and make the printing process generally easier, faster, and less expensive. In addition, these modifications make the parts more suitable for casting, if high output is required. Metallic and thermoplastic composite respirators were produced and then tested in real operating conditions, i.e. with oxygen supply resembling a hospital environment. The initial results are considered positive, both in the quality of construction and in their performance. Furthermore, combination ofmanufacturing technologies is assessed, aiming at high output production. © 2022 American Institute of Physics Inc.. All rights reserved.

Bio-Virus Spread Simulation in Real 3D Space using Augmented Reality

Due to the emergence of the novel human coronavirus disease (COVID-19), human life is jeopardized. Normal livelihood and economy have been disrupted due to safety concerns associated with the viral dissemination. The pandemic has instilled fear in people due to the lack of understanding and the impact an infection could have. In addition, laboratory experiments focused on coronavirus infection dynamics are labor intensive, costly and time consuming. A viable alternative to wet-lab experimentation is the in silico simulations, which enable difficult tasks to be efficiently and accurately performed by both professionals and citizens alike. This would enable people to gain a simpler understanding of the coronavirus dissemination and be informed timely, to take the preventive measures required. The application described herein was designed to simulate the spread of Covid-19 on different surfaces and showcase its longevity. A case study was also conducted by using this application. © Engineered Science Publisher LLC 2021.