ABSTRACT
Our research deals with creating a suitable and sufficiently reliable methodology to use for evaluating the movement of passengers in public transport or pedestrians. The goal is to design crowds ensing-based methods that provide a quick alternative to large-scale evaluations. It is the settings, the number of installed elements, parameters, and possibly other attributes enabling an increase in quality and reliability in real city conditions. The methodology must comply with GDPR. We also deal with the possibility of evaluating the behavior of people in case of restrictions due to disease spreading (nowadays, for example, COVID19). Our goal is to find methods using wireless technology and their generally little-described features for evaluating the movement of people. The usability of these technologies extends to some branches of logistics or organizations of larger cultural or sporting events. © 2022 IEEE.
ABSTRACT
In IoT (Internet of Things), the concept of a Smart City integrates technologies and physical devices in various fields of deployment. One such instance is logistics. With the increasing popularity and need for online shopping, the e-commerce sector is growing-which goes hand in hand with the logistics industry. The logistics industry keeps growing and is gaining more and more importance-and so do the delivery solutions in the last-mile part of the logistics chain. The last-mile delivery offers a lot of possibilities for new and complexly integrated smart solutions. We propose a new solution for smart delivery services on the last mile. We call it a Smart Post Box. This concept combines various elements and creates a multi-purpose smart city solution that can be easily integrated into different systems. It introduces new ways to receive and send packages, integrates as a part of a smart household, sends notifications, and can be used to collect valuable data. During the current coronavirus outbreak, this solution would prove to be useful in reducing interpersonal contact and thus help eliminate the transfer of the disease. Our calculations show great potential for such innovation. © 2022 IEEE.
ABSTRACT
Progress in the fight against COVID-19 is jeopardized by the emergence of SARS-CoV-2 variants that diminish or abolish the efficacy of vaccines and antiviral monoclonal antibodies. Novel immune therapies are therefore needed, that are broadly effective against present and future coronavirus threats. In principle, this could be achieved by focusing on portions of the virus that are both functionally relevant and averse to change. The Subdomain 1 (SD1) of SARS-CoV-2 Spike protein is adjacent to the RBD and its sequence is conserved across SARS-CoV-2 variants, except for substitutions A570D in Alpha (B.1.1.7) and T547K in Omicron BA.1 (B.1.1.529). In order to specifically identify and study human antibodies targeting SD1, we designed a flow cytometry-based strategy that combines negative selection of B cells binding to the Receptor Binding Domain (RBD) with positive selection of those binding to SD1-RBD fusion protein. Among the 15 produced human monoclonal antibodies, 6 are SD1-specific. 3 of them cross-react with SD1-RBDs corresponding to all six variants of concern and 2 are neutralizing SARS-CoV-2 pseudovirus. Antibody sd1.040 also neutralizes Delta, Omicron BA.1 and Omicron BA.2 pseudovirus, synergizes with an antibody to the RBD for neutralization, and protects mice when present in a bispecific antibody. Thus, naturally occurring antibodies can neutralize SARS-CoV-2 variants by binding to SD1 and can act synergistically against SARS-CoV-2 in preclinical models.