Search for: All records

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD. 

Understanding the preferences for new and future transportation technologies is important to ensure an efficient and equitable future transportation system. A survey was conducted of Americans’ preferences for several such technologies. Americans are concerned about vehicle range and charging station availability for electric vehicles (EVs) and hesitant about autonomous vehicle (AV) safety. Opinions about many transportation technologies, such as vertical takeoff and landing (i.e., air taxis), shared parking, and air-drone delivery are mixed. These less familiar technologies require continued tracking of preferences. A 55% increase is estimated in the probability of an individual choosing a battery electric vehicle (BEV) pickup truck if its fuel economy increases by about 9%. This result supports a market for BEV pickup trucks currently under development by many automakers. The preference for vehicle autonomation appears to depend on the use case. Driving task automation is preferred by residents of low-density, car-dependent areas where long commutes are common. In contrast, automated parking technologies are favored by those living in denser communities. Intermittent bus lanes are favored by those living in high population density areas, but not among those in areas with high shares of zero-vehicle households. These results provide indications of where to direct future research in the field. 

Abstract The neutrino signal from the next galactic core-collapse supernova will provide an invaluable early warning of the explosion. By combining the burst trigger from several neutrino detectors, the location of the explosion can be triangulated minutes to hours before the optical emission becomes visible, while also reducing the rate of false-positive triggers. To enable multi-messenger follow-up of nearby supernovae, the SuperNova Early Warning System 2.0 (SNEWS 2.0) will produce a combined alert using a global network of neutrino detectors. This paper describes the trigger publishing and alert formation framework of the SNEWS 2.0 network. The framework is built on the HOPSKOTCH publish-subscribe system to easily incorporate new detectors into the network, and it implements a coincidence system to form alerts and estimate a false-positive rate for the combined triggers. The paper outlines the structure of the SNEWS 2.0 software and the initial testing of coincident signals. 

Arctic biodiversity is under threat from both climate-induced environmental change and anthropogenic activity. However, the rapid rate of change and the challenging conditions for studying Arctic environments mean that many research questions must be answered before we can strategically allocate resources for management. Addressing threats to biodiversity in the Arctic is further complicated by the region's complex geopolitics, as eight countries claim jurisdiction over the area, with multiple local considerations such as Indigenous sovereignty and resource rights. Here, we identify research priorities to serve as a starting point for addressing the most pressing threats to Arctic biodiversity. We began by collecting pressing research questions about Arctic biodiversity, thematizing them as either threats or actions, and then categorizing them further into 18 groups. Then, drawing on cross-disciplinary and global expertise of professionals in Arctic science, management, and policy, we considered the barriers to answering these questions and proposed potential solutions that could be implemented if barriers were overcome. Overall, our horizon scan provides an expert assessment of threats (e.g., species’ responses to climate change) and actions (e.g., a lack of fundamental information regarding Arctic biodiversity) needing attention and is intended to guide future conservation action within the Arctic. 

Tardigrades, commonly known as ‘waterbears’, are eight-legged microscopic invertebrates renowned for their ability to withstand extreme stressors, including high osmotic pressure, freezing temperatures, and complete desiccation. Limb retraction and substantial decreases to their internal water stores results in the tun state, greatly increasing their ability to survive. Emergence from the tun state and/or activity regain follows stress removal, where resumption of life cycle occurs as if stasis never occurred. However, the mechanism(s) through which tardigrades initiate tun formation is yet to be uncovered. Herein, we use chemobiosis to demonstrate that tardigrade tun formation is mediated by reactive oxygen species (ROS). We further reveal that tuns are dependent on reversible cysteine oxidation, and that this reversible cysteine oxidation is facilitated by the release of intracellular reactive oxygen species (ROS). We provide the first empirical evidence of chemobiosis and map the initiation and survival of tardigrades via osmobiosis, chemobiosis, and cryobiosis.In vivoelectron paramagnetic spectrometry suggests an intracellular release of reactive oxygen species following stress induction; when this release is quenched through the application of exogenous antioxidants, the tardigrades can no longer survive osmotic stress. Together, this work suggests a conserved dependence of reversible cysteine oxidation across distinct tardigrade cryptobioses. 

This article describes the use of a comic book to anchor a cryptology and cybersecurity curriculum for upper elementary students. Perceptions about the comic book from 138 students across 11 afterschool programs were examined using survey, classroom observation, and interviews. Data analysis revealed that the comic book created a “macrocontext” to situate learners in an exciting adventure about cryptology and cybersecurity. Students found the characters relatable, and their perceptions were tightly tied to other components of the curriculum. Reading the word bubbles was chal- lenging at first, but got easier over time. This study illustrates how comic books can anchor unfamiliar STeM content for younger learners. 

Abstract Radiogenic neutrons emitted by detector materials are one of the most challenging backgrounds for the direct search of dark matter in the form of weakly interacting massive particles (WIMPs). To mitigate this background, the XENONnT experiment is equipped with a novel gadolinium-doped water Cherenkov detector, which encloses the xenon dual-phase time projection chamber (TPC). The neutron veto (NV) can tag neutrons via their capture on gadolinium or hydrogen, which release$$\gamma $$ $\gamma$-rays that are subsequently detected as Cherenkov light. In this work, we present the first results of the XENONnT NV when operated with demineralized water only, before the insertion of gadolinium. Its efficiency for detecting neutrons is$$({82\pm 1}){\%}$$ $\left(82\pm 1\right)\%$, the highest neutron detection efficiency achieved in a water Cherenkov detector. This enables a high efficiency of$$({53\pm 3}){\%}$$ $\left(53\pm 3\right)\%$for the tagging of WIMP-like neutron signals, inside a tagging time window of$${250}~{\upmu }\hbox {s}$$ $250\mu \text{s}$between TPC and NV, leading to a livetime loss of$${1.6}{\%}$$ $1.6\%$during the first science run of XENONnT.