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  1. Free, publicly-accessible full text available April 16, 2025
  2. This work in progress paper presents and motivates the design of a novel extended reality (XR) environment for artificial intelligence (AI) education, and presents its first implementation. The learner is seated at a table and wears an XR headset that allows them to see both the real world and a visualization of a neural network. The visualization is adjustable. The learner can inspect each layer, each neuron, and each connection. The learner can also choose a different input image, or create their own image to feed to the network. The inference is computed on the headset, in real time. The neural network configuration and its weights are loaded from an onnx file, which supports a variety of architectures as well as changing the weights to illustrate the training process. 
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    Free, publicly-accessible full text available March 21, 2025
  3. Free, publicly-accessible full text available February 1, 2025
  4. Abstract

    Mercury (Hg) is a global pollutant whose atmospheric deposition is a major input to the terrestrial and oceanic ecosystems. Gas‐particle partitioning (GPP) of gaseous oxidized mercury (GOM) redistributes speciated Hg between gas and particulate phase and can subsequently alter Hg deposition flux. Most 3‐dimensional chemical transport models either neglected the Hg GPP process or parameterized it with measurement data limited in time and space. In this study, CMAQ‐newHg‐Br (Ye et al., 2018,https://doi.org/10.1002/2017ms001161) was updated to CMAQ‐newHg‐Br v2 by implementing a new GPP scheme and the most up‐to‐date Hg redox chemistry and was run for the northeastern United States over January‐November 2010. CMAQ‐newHg‐Br v2 reproduced the measured spatiotemporal distributions of gaseous elemental mercury (GEM) and particulate bound mercury (PBM) concentrations and Hg wet deposition flux within reasonable ranges and simulated dry deposition flux in agreement with previous studies. The GPP scheme improved the simulation of PBM via increasing winter‐, spring‐ and fall‐time PBM concentrations by threefold. It also improved simulated Hg wet deposition flux with an increase of 2.1 ± 0.7 μgm2in the 11‐month accumulated amount, offsetting half of the decreasing effect of the updated chemistry (−4.2 ± 1.8 μgm2). Further, the GPP scheme captured the observedKp‐T relationship as reported in previous studies without using measurement data and showed advantages at night and in rural/remote areas where existing empirical parameterizations failed. Our study demonstrated CMAQ‐newHg‐Br v2 a promising assessment tool to quantify impacts of climate change and emission reduction policy on Hg cycling.

     
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    Free, publicly-accessible full text available March 1, 2025
  5. This study investigates the potential use of circulating extracellular vesicles’ (EVs) DNA and protein content as biomarkers for traumatic brain injury (TBI) in a mouse model. Despite an overall decrease in EVs count during the acute phase, there was an increased presence of exosomes (CD63+ EVs) during acute and an increase in microvesicles derived from microglia/macrophages (CD11b+ EVs) and astrocytes (ACSA-2+ EVs) in post-acute TBI phases, respectively. Notably, mtDNA exhibited an immediate elevation post-injury. Neuronal (NFL) and microglial (Iba1) markers increased in the acute, while the astrocyte marker (GFAP) increased in post-acute TBI phases. Novel protein biomarkers (SAA, Hp, VWF, CFD, CBG) specific to different TBI phases were also identified. Biostatistical modeling and machine learning identified mtDNA and SAA as decisive markers for TBI detection. These findings emphasize the importance of profiling EVs’ content and their dynamic release as an innovative diagnostic approach for TBI in liquid biopsies 
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    Free, publicly-accessible full text available February 16, 2025
  6. Free, publicly-accessible full text available November 29, 2024
  7. Systematic investigations of electronic energy loss (Se) effects on pre-existing defects in crystalline silicon (Si) are crucial to provide reliance on the use of ionizing irradiation to anneal pre-existing defects, leading to successful implementation of this technology in the fabrication of Si-based devices. In this regard, the Se effects on nonequilibrium defect evolution in pre-damaged Si single crystals at 300 K has been investigated using intermediate-energy ions (12 MeV O and Si ions) that interact with the pre-damaged surface layers of Si mainly by ionization, except at the end of their range where the nuclear energy loss (Sn) is no longer negligible. Under these irradiation conditions, experimental results and molecular dynamics simulations have revealed that pre-existing disorder in Si can be almost fully annealed by subsequent irradiation with intermediate-energy incident ions with Se values as low as 1.5 - 3.0 keV/nm. Selective annealing of pre-existing defect levels in Si at room temperature can be considered as an effective strategy to mediate the transient enhanced diffusion of dopants in Si. This approach is more desirable than the regular thermal annealing, which is not compatible with the processing requirements that fall below the typical thermal budget. 
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    Free, publicly-accessible full text available December 1, 2024
  8. The finite-difference time-domain (FDTD) method is a widespread numerical tool for full-wave analysis of electromagnetic fields in complex media and for detailed geometries. Applications of the FDTD method cover a range of time and spatial scales, extending from subatomic to galactic lengths and from classical to quantum physics. Technology areas that benefit from the FDTD method include biomedicine — bioimaging, biophotonics, bioelectronics and biosensors; geophysics — remote sensing, communications, space weather hazards and geolocation; metamaterials — sub-wavelength focusing lenses, electromagnetic cloaks and continuously scanning leaky-wave antennas; optics — diffractive optical elements, photonic bandgap structures, photonic crystal waveguides and ring-resonator devices; plasmonics — plasmonic waveguides and antennas; and quantum applications — quantum devices and quantum radar. This Primer summarizes the main features of the FDTD method, along with key extensions that enable accurate solutions to be obtained for different research questions. Additionally, hardware considerations are discussed, plus examples of how to extract magnitude and phase data, Brillouin diagrams and scattering parameters from the output of an FDTD model. The Primer ends with a discussion of ongoing challenges and opportunities to further enhance the FDTD method for current and future applications. 
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    Free, publicly-accessible full text available December 1, 2024
  9. Free, publicly-accessible full text available July 23, 2024
  10. Free, publicly-accessible full text available August 15, 2024