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The outbreak of coronavirus disease 2019 (COVID-19) has led to significant challenges for schools and communities during the pandemic, requiring policy makers to ensure both safety and operational feasibility. In this paper, we develop mixed-integer programming models and simulation tools to redesign routes and bus schedules for operating a real university campus bus system during the COVID-19 pandemic. We propose a hub-and-spoke design and utilize real data of student activities to identify hub locations and bus stops to be used in the new routes. To reduce disease transmission via expiratory aerosol, we design new bus routes that are shorter than 15 minutes to travel and operate using at most 50% seat capacity and the same number of buses before the pandemic. We sample a variety of scenarios that cover variations of peak demand, social distancing requirements, and bus breakdowns to demonstrate the system resiliency of the new routes and schedules via simulation. The new bus routes were implemented and used during the academic year 2020–2021 to ensure social distancing and short travel time. Our approach can be generalized to redesign public transit systems with a social distancing requirement to reduce passengers’ infection risk. History: This paper was refereed. This article has been selected for inclusion in the Special Issue on Analytics Remedies to COVID-19. Funding: This work was supported by the National Science Foundation [Grant CMMI-2041745] and the University of Michigan, College of Engineering.more » « less
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In this paper, we consider an integrated vehicle routing and service scheduling problem for serving customers in distributed locations who need pick-up, drop-off, or delivery services. We take into account the random trip time, nonnegligible service time, and possible customer cancellations, under which an ill-designed schedule may lead to undesirable vehicle idleness and customer waiting. We build a stochastic mixed-integer program to minimize the operational cost plus expected penalty cost of customers’ waiting time, vehicles’ idleness, and overtime. Furthermore, to handle real-time arrived service requests, we develop K-means clustering-based algorithms to dynamically update planned routes and schedules. The algorithms assign customers to vehicles based on similarities and then plan schedules on each vehicle separately. We conduct numerical experiments based on diverse instances generated from census data and data from the Ford Motor Company’s GoRide service, to evaluate result sensitivity and to compare the in-sample and out-of-sample performance of different approaches. Managerial insights are provided using numerical results based on different parameter choices and uncertainty settings.more » « less
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Abstract Background Candidatus Nanohaloarchaeota, an archaeal phylum within the DPANN superphylum, is characterized by limited metabolic capabilities and limited phylogenetic diversity and until recently has been considered to exclusively inhabit hypersaline environments due to an obligate association withHalobacteria . Aside from hypersaline environments,Ca. Nanohaloarchaeota can also have been discovered from deep-subsurface marine sediments.Results Three metagenome-assembled genomes (MAGs) representing a new order within the
Ca. Nanohaloarchaeota were reconstructed from a stratified salt crust and proposed to represent a novel order,Nucleotidisoterales . Genomic features reveal them to be anaerobes capable of catabolizing nucleotides by coupling nucleotide salvage pathways with lower glycolysis to yield free energy. Comparative genomics demonstrated that these and otherCa. Nanohaloarchaeota inhabiting saline habitats use a “salt-in” strategy to maintain osmotic pressure based on the high proportion of acidic amino acids. In contrast, previously describedCa. Nanohaloarchaeota MAGs from geothermal environments were enriched with basic amino acids to counter heat stress. Evolutionary history reconstruction revealed that functional differentiation of energy conservation strategies drove diversification withinCa. Nanohaloarchaeota, further leading to shifts in the catabolic strategy from nucleotide degradation within deeper lineages to polysaccharide degradation within shallow lineages.Conclusions This study provides deeper insight into the ecological functions and evolution of the expanded phylum
Ca. Nanohaloarchaeota and further advances our understanding on the functional and genetic associations between potential symbionts and hosts.
