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The United States federal government has invested $7.5 billion into charging infrastructure, including the National Electric Vehicle Infrastructure Program, to build fast charging stations along designated highways for long-distance car travel. We develop a consecutive coverage metric to compute the percent of United States roads (traffic-weighted) that are consecutively accessible within 500 miles of each county. We answer (1) what the state of consecutive coverage is in each county and (2) what the increase in coverage is when designated highways receive fast chargers. In 2023, 10% of counties had at least 75% minimum viable coverage. We find that if all designated highways receive fast-charging stations, 94% of United States counties will reach at least 75% fast charger coverage. However, the remaining counties are rural. This demonstrates that federal funding for fast chargers will help connect most—but not all—counties to the national network of continuously accessible charging stations. Consecutive coverage of fast charging station access for long distance Electric Vehicle trips in the U.S. is lacking. However, if implemented as planned, federal funding for chargers will help most counties reach high consecutive coverage.

The widespread adoption of smartphones followed by an emergence of transportation network companies (TNC) have influenced the way individuals travel. The authors use the 2017 National Household Travel Survey to explore socioeconomic, frequency of use, and spatial characteristics associated with TNC users. The results indicate that TNC riders tend to be younger, earn higher incomes, have higher levels of education, and are more likely to reside in urban areas compared to the aggregate United States population. Of the TNC users, 60% hailed a ride three times or less in the previous month, indicating that TNC services are primarily used for special occasions. TNC users use public transit at higher rates and own fewer vehicles compared to the aggregate United States population. In fact, the TNC user population reported similar frequencies of use for both TNC services and public transit during the previous month. Approximately 40% of TNC users reside in regions with population densities greater than 10, 000 persons per square mile compared to only 15% for non-TNC users. Lastly, reported use of public transit for TNC users living in large cities (> 1 million) with access to heavy rail was almost three times greater when compared to similar sized cities without heavy rail. The average monthly frequency of TNC use was also elevated when heavy rail was present.

The paper develops a methodology, Grid-ECO, to optimally allocate electric vehicle charging stations (EVCS) within a distribution feeder, while considering EV charging demand at census-level granularity. The underlying problem is NP-hard and requires satisfying nonlinear, nonconvex, three-phase unbalanced AC network constraints while including integer decision variables. Existing works cannot guarantee AC feasibility nor optimality of this problem without either i) relaxing the integer decision variable space or ii) convexifying AC constraints. Proposed Grid-ECO exactly solves the underlying mixed-integer nonlinear program (MINLP) to near-zero optimality gap while prioritizing candidate locations based on grid voltage and current sensitivities. To solve the MINLP exactly, Grid-ECO exactly reformulates it into mixed-integer bilinear program (MIBLP), enabling global optimization using the spatial branch-and-bound algorithm (sBnB). To ensure computational tractability for large-scale feeders, we develop and include a novel presolving strategy based on Sequential Bound Tightening (SBT) with variable filtering and decomposition. Case studies demonstrate that Grid-ECO outperforms the off-the-shelf Gurobi sBnB solver by solving cases where no feasible solution is found within 167 hours. When feasible solution is found by off-the-shelf solver, Grid-ECO reduces solution time by up to 73\\% and sBnB node exploration by up to 97\\%, while achieving a 0\\% optimality gap and guaranteed AC feasibility.

Once introduced into a high school in New York City, the 2009 H1N1 virus spread quickly among students and staff, with an influenza-like illness developing in more than 800 people during a 2-week period. In this population, which had no previous exposure to this virus, the incubation period was estimated to be about 2 days, the median generation time 2.7 days, and the within-school reproduction number 3.3. Once introduced into a high school in New York City, the 2009 H1N1 virus spread quickly among students and staff, with an influenza-like illness developing in more than 800 people during a 2-week period in April 2009. In April 2009, clusters of cases of 2009 H1N1 influenza involving potential human-to-human transmission were reported in multiple countries. 1 One of the earliest and largest clusters identified in the United States was an acute outbreak of 2009 H1N1 influenza at a New York City high school. 2 This outbreak prompted an immediate and rapid investigation by the New York City Department of Health and Mental Hygiene. This report describes the clinical and epidemiologic findings from this investigation. On Thursday, April 23, 2009, a nurse from a high school in Queens, New York, that had an enrollment of 2686 students notified the . . .

\"Fans of such notables as C.J. Box, Peter Straub, and Joyce Carol Oates chiefly known for their novels will be pleased to see how well they write at shorter length.\"--Publishers Weekly \"Some people might tell you that crime short stories, unlike the more precious kind, are a kind of fictional ghetto, full of cardboard characters and clichéd situations. Not true. These stories are remarkably free of bullshit-al-though there's always a little, just to grease the wheels,\" writes guest editor John Sandford in his introduction. From an isolated Wyoming ranch to the Detroit boxing underworld, and from kidnapping and adultery in the Hollywood Hills to a serial killer loose in a nursing home, The Best American Mystery Stories 2017 hosts an entertaining abundance of crime, psychological suspense, and bad intentions.The Best American Mystery Stories 2017 includes C. J. BOX, GERRI BRIGHTWELL, JEFFERY DEAVER, BRENDAN DUBOIS, TRINA COREY, CRAIG JOHNSON, JOYCE CAROL OATES, PETER STRAUB, and others

Human pluripotent stem cell (hPSC)-derived tissues can be used to model diseases and validate targets in cell types that are challenging to harvest and study at scale, such as neutrophils. Neutrophil dysregulation, specifically unbalanced neutrophil extracellular trap (NET) formation, plays a critical role in the prognosis and progression of multiple diseases, including COVID-19. hPSCs can provide a limitless supply of neutrophils (iNeutrophils) to study these processes and discover and validate targets in vitro. However, current iNeutrophil differentiation protocols are inefficient and generate heterogeneous cultures consisting of different granulocytes and precursors, which can confound the study of neutrophil biology. Here, we describe a method to dramatically improve iNeutrophils′ yield, purity, functionality, and maturity through the deletion of the transcription factor GATA1. GATA1 knockout (KO) iNeutrophils are nearly identical to primary neutrophils in cell surface marker expression, morphology, and host defense functions. Unlike wild type (WT) iNeutrophils, GATA1 KO iNeutrophils generate NETs in response to the physiologic stimulant lipid polysaccharide (LPS), suggesting they could be used as a more accurate model when performing small-molecule screens to find NET inhibitors. Furthermore, we demonstrate that GATA1 KO iNeutrophils are a powerful tool in quickly and definitively determining involvement of a given protein in NET formation.Competing Interest StatementThe authors have declared no competing interest.