Hybrid Learning for Mobile Ad-hoc Distancing/Positioning Using Bluetooth Low Energy

With the advent of Bluetooth Low Energy (BLE)-enabled smartphones, there has been considerable interest in investigating BLE-based distancing/positioning methods (e.g., for social distancing applications). In this paper, we present a novel hybrid learning method to support Mobile Ad-hoc Distancing (MAD) / Positioning (MAP) using BLE-enabled smartphones. Compared to traditional BLE-based distancing/positioning methods, the hybrid learning method provides the following unique features and contributions. First, it combines unsupervised learning, supervised learning and genetic algorithms for enhancing distance estimation accuracy. Second, unsupervised learning is employed to identify three pseudo channels/clusters for enhanced RSSI data processing. Third, its underlying mechanism is based on a new pattern-inspired approach to enhance the machine learning process. Fourth, it provides a flagging mechanism to alert users if a predicted distance is accurate or not. Fifth, it provides a model aggregation scheme with an innovative two-dimensional genetic algorithm to aggregate the distance estimation results of different machine learning models. As an application of hybrid learning for distance estimation, we also present a new MAP scenario with an iterative algorithm to estimate mobile positions in an ad-hoc environment. Experimental results show the effectiveness of the hybrid learning method. In particular, hybrid learning without flagging and with flagging outperform the baseline by 57 and 65 percent respectively in terms of mean absolute error. By means of model aggregation, a further 4 percent improvement can be realized. The hybrid learning approach can also be applied to previous work to enhance distance estimation accuracy and provide valuable insights for further research. IEEE

A 4C Model for Hyflex Classrooms

In last two years, universities around the world have been using hyflex teaching due to COVID-19. This allows students to attend physical/online lectures in a flexible manner. A hyflex class comprises classroom students as well as online students. In this paper, we present a model for hyflex classrooms that highlights 4Cs: Content, Collaboration, Community and Communication. Based on the 4C model, a hyflex classroom has been designed and implemented through various teaching/learning tools or elements. These include the effective use of presentation slides, annotations, chatbox, open education resources, multiple choice exercises, group exercises etc. The effectiveness of these tools/elements were evaluated by means of an initial student survey. These results provide valuable insights into hyflex teaching/learning. © 2022 IEEE.

Effect of SARS and COVID-19 outbreaks on urology practice and training.

INTRODUCTION: The objective was to investigate the changes in urology practice during coronavirus disease 2019 (COVID-19) pandemic with a perspective from our experience with severe acute respiratory syndrome (SARS) in 2003. METHODS: Institutional data from all urology centres in the Hong Kong public sector during the COVID-19 pandemic (1 Feb 2020-31 Mar 2020) and a non-COVID-19 control period (1 Feb 2019-31 Mar 2019) were acquired. An online anonymous questionnaire was used to gauge the impact of COVID-19 on resident training. The clinical output of tertiary centres was compared with data from the SARS period. RESULTS: The numbers of operating sessions, clinic attendance, cystoscopy sessions, prostate biopsy, and shockwave lithotripsy sessions were reduced by 40.5%, 28.5%, 49.6%, 44.8%, and 38.5%, respectively, across all the centres reviewed. The mean numbers of operating sessions before and during the COVID-19 pandemic were 85.1±30.3 and 50.6±25.7, respectively (P=0.005). All centres gave priority to cancer-related surgeries. Benign prostatic hyperplasia-related surgery (39.1%) and ureteric stone surgery (25.5%) were the most commonly delayed surgeries. The degree of reduction in urology services was less than that during SARS (47.2%, 55.3%, and 70.5% for operating sessions, cystoscopy, and biopsy, respectively). The mean numbers of operations performed by residents before and during the COVID-19 pandemic were 75.4±48.0 and 34.9±17.2, respectively (P=0.002). CONCLUSION: A comprehensive review of urology practice during the COVID-19 pandemic revealed changes in every aspect of practice.

Clinical HDAC Inhibitors Are Effective Drugs to Prevent the Entry of SARS-CoV2.

The outbreak of COVID-19 by the end of 2019 has posed serious health threats to humanity and jeopardized the global economy. However, no effective drugs are available to treat COVID-19 currently and there is a great demand to fight against it. Here, we combined computational screening and an efficient cellular pseudotyped virus system, confirming that clinical HDAC inhibitors can efficiently prevent SARS-CoV-2 and potentially be used to fight against COVID-19.