The COVID-19 pandemic has forced many organizations around the world to make full use of a variety of emerging online communication platform technologies. Universities are among the organizations that have asked students, tutors, and lecturers to use a number of different online communication platforms to ensure the education process remains uninterrupted. However, the COVID-19 pandemic has generated considerable challenges for the global higher education community while using such emerging technologies. This research has two main goals. First, this paper will begin by investigating whether the online learning platforms used by university students during the COVID-19 period have presented any challenges to their learning. Second, the paper will then go on to address proposed solutions by developing a conceptual model to reduce the impact of such challenges. This research uses an exploratory qualitative research approach, supported by literature content analysis techniques. The data set for this study was collected during the first peak of the pandemic period in Malaysia, between the 16th of May 2020 and the 5th of June 2020. We used SPSS to conduct a descriptive analysis and NVivo12 to analyse data collected from 486 students from different universities in Malaysia. These students disclosed various obstacles they encountered when they used IT platform applications for online learning. These obstacles include (a) work and information overload received from instructors, (b) inadaptability and unfamiliarity of the new online learning environment, and (c) personal health challenges related to stress and anxiety. Based on previous relevant research, this study introduced a set of motivational factors and developed a conceptual motivational model for sustainable and healthy online learning.

This paper presents a new capsule-shaped sensor to detect the glucose concentration in the human body. The model under study was formulated by relying on the index change in the refractive index (RI) because of the change in the sample that infiltrated the cavity. The index of refraction change is accompanied by modifying the resonant wavelength. The recommended model has considered the simple shape and ease of manufacture, along with other characteristics such as sensitivity and a low detection limit. The results report a high sensitivity of S = 546.72 nm/RI unit (RIU), a high quality factor of Q = 2066.24, a low detection limit of DL = 1.44 × 10⁻⁴ RIU, and a high value of transmission of 97%, which are considered to be sufficient and efficient in detecting measured material. This proposed model provides many opportunities and is promising for the manufacture of different types of sensing detection devices.

The use of social media has increased during the COVID-19 pandemic because people are isolated and working from home. The use of social media enhances information exchange in society and may influence public protective behavior against the COVID-19 pandemic. The purpose of this study is to identify the factors affecting public protective behavior when relying on COVID-19 pandemic-related content shared on social media. A model based on Protection Motivation Theory (PMT) was proposed and validated using a quantitative survey approach. A questionnaire was distributed to random respondents, and 488 responses were received and analyzed using Smart-PLS software. The findings showed that perceived risk, e-health literacy, public awareness, and health experts’ participation influence public protective behavior when using social media to share COVID-19-relevant content. The outcomes of this study can enhance government agencies’ and public health care authorities’ understanding of how to use social media to raise awareness and reduce panic among the public.