ABSTRACT
The COVID-19 pandemic has caused significant changes around the world. The circumstances resulted in a radical shift in people's lives, including the way they move around the cities and/or carry out their activities. This study carries out a travel behavior analysis using commuting panel data collected over 7 days using smartphones. The study focuses on the Maceió Metropolitan Area (MMA), which is in the state of Alagoas in the northeast region of Brazil. Cluster analysis, using the k-means algorithm, divided the sample into three groups of travel behavior: Group A ("Infrequent travelers, for work or shopping trip purposes and very prone to do remote work"), Group B ("Intermediate travelers, for work or shopping trip purposes and prone to do remote work"), and Group C ("Frequent travelers, for work or meal purchases and not likely to do remote work"). Groups B and C are predominantly formed by individuals who carry out activities that are less likely to do remote work. By analyzing the groups, it is possible to understand the changes that occurred during the period studied (September/October 2020) and what are the expectations for a post-pandemic scenario, associated with each behavioral group. It was observed that "Working" was the main trip purpose during the pandemic and that the possibility of teleworking depends on the type of activity carried out. Making a scale of the resilience of activities considering the replacement of out-of-home activities by in-home remote activities, it can be observed that Group A was the most resilient, followed by Group B and C, respectively. For the post-pandemic scenario, Groups A and B are also the most likely to use Information and Communication Technologies (ICTs) and continue carrying out other remote activities, such as grocery shopping and meals, replacing, in the future, predominantly trips using ICTs.
ABSTRACT
Hybrid quantum chemical/molecular mechanical (QCMM) potentials are very powerful tools for molecular simulation. They are especially useful for studying processes in condensed phase systems, such as chemical reactions that involve a relatively localized change in electronic structure and where the surrounding environment contributes to these changes but can be represented with more computationally efficient functional forms. Despite their utility, however, these potentials are not always straightforward to apply since the extent of significant electronic structure changes occurring in the condensed phase process may not be intuitively obvious. To facilitate their use, we have developed an open-source graphical plug-in, GTKDynamo that links the PyMOL visualization program and the pDynamo QC/MM simulation library. This article describes the implementation of GTKDynamo and its capabilities and illustrates its application to QC/MM simulations.