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For transportation hubs, leveraging pedestrian flows for commercial activities presents an effective strategy for funding maintenance and infrastructure improvements. However, this introduces new challenges, as consumer behaviors can disrupt pedestrian flow and efficiency. To optimize both retail potential and pedestrian efficiency, careful strategic planning in store layout and facility dimensions was done by expert judgement due to the complexity in pedestrian dynamics in the retail areas of transportation hubs. This paper introduces an attention-based movement model to simulate these dynamics. By simulating retail potential of an area through the duration of visual attention it receives, and pedestrian efficiency via speed loss in pedestrian walking behaviors, the study further explores how design features can influence the retail potential and pedestrian efficiency in a bi-directional corridor inside a transportation hub. 

For short-wavelength infrared (SWIR) avalanche photodiodes, a separate absorption, charge, and multiplication design is widely used. AlInAsSb on an InP substrate is a potential multiplication layer with a lattice match to absorber candidates across the SWIR. Our new measurements demonstrate that AlInAsSb on InP is a promising multiplier candidate with a relatively low dark current density of 10−4 A/cm2 at a gain of 30; a high gain, measured up to 245 in this study; and a large differentiation of electron and hole ionization leading to a low excess noise, measured to be 2.5 at a gain of 30. These characteristics are all improvements over commercially available SWIR detectors incorporating InAlAs or InP as the multiplier. We measured and analyzed gain for multiple wavelengths to extract the ionization coefficients as a function of an electric field over the range 0.33–0.6 MV/cm. 

Abstract NRLMSIS® 2.0 is an empirical atmospheric model that extends from the ground to the exobase and describes the average observed behavior of temperature, eight species densities, and mass density via a parametric analytic formulation. The model inputs are location, day of year, time of day, solar activity, and geomagnetic activity. NRLMSIS 2.0 is a major, reformulated upgrade of the previous version, NRLMSISE‐00. The model now couples thermospheric species densities to the entire column, via an effective mass profile that transitions each species from the fully mixed region below ~70 km altitude to the diffusively separated region above ~200 km. Other changes include the extension of atomic oxygen down to 50 km and the use of geopotential height as the internal vertical coordinate. We assimilated extensive new lower and middle atmosphere temperature, O, and H data, along with global average thermospheric mass density derived from satellite orbits, and we validated the model against independent samples of these data. In the mesosphere and below, residual biases and standard deviations are considerably lower than NRLMSISE‐00. The new model is warmer in the upper troposphere and cooler in the stratosphere and mesosphere. In the thermosphere, N₂and O densities are lower in NRLMSIS 2.0; otherwise, the NRLMSISE‐00 thermosphere is largely retained. Future advances in thermospheric specification will likely require new in situ mass spectrometer measurements, new techniques for species density measurement between 100 and 200 km, and the reconciliation of systematic biases among thermospheric temperature and composition data sets, including biases attributable to long‐term changes.