Search for: All records

Amid corrosion degradation of metallic structures causing expenses nearing 3 trillion or 4% of the GDP annually along with major safety risks, the adoption of AI technologies for accelerating the materials science life-cycle for developing materials with better corrosive properties is paramount. While initial machine learning models for corrosion assessment are being proposed in the literature, their incorporation into end-to-end tools for field experimentation by corrosion scientists remains largely unexplored. To fill this void, our university data science team in collaboration with the materials science unit at the Army Research Lab have jointly developed MOSS, an innovative AI-based digital platform to support material science corrosion research. MOSS features user-friendly iPadOS app for in-field corrosion progression data collection, deep-learning corrosion assessor, robust data repository system for long-term experimental data modeling, and visual analytics web portal for material science research. In this demonstration, we showcase the key innovations of the MOSS platform via use cases supporting the corrosion exploration processes, with the promise of accelerating the discovery of new materials. We open a MOSS video demo at: https://www.youtube.com/watch?v=CzcxMMRsxkE 

Improving teaching strategies through a simulated teaching environment has been shown to improve teacher self-efficacy, teaching skills, classroom management and multicultural awareness. The current study is using the simulation program to help educators recognize possible bias with the goal of recognizing, reflecting and remediating any biases that may exist. Both self-report survey data as well as simulation-captured data are used to understand the changes that occur as educators have the opportunity for many trials of teaching using feedback for improvement each time. 

Abstract The recent IceCube detection of TeV neutrino emission from the nearby active galaxy NGC 1068 suggests that active galactic nuclei (AGNs) could make a sizable contribution to the diffuse flux of astrophysical neutrinos. The absence of TeVγ-rays from NGC 1068 indicates neutrino production in the vicinity of the supermassive black hole, where the high radiation density leads toγ-ray attenuation. Therefore, any potential neutrino emission from similar sources is not expected to correlate with high-energyγ-rays. Disk-corona models predict neutrino emission from Seyfert galaxies to correlate with keV X-rays because they are tracers of coronal activity. Using through-going track events from the Northern Sky recorded by IceCube between 2011 and 2021, we report results from a search for individual and aggregated neutrino signals from 27 additional Seyfert galaxies that are contained in the Swift's Burst Alert Telescope AGN Spectroscopic Survey. Besides the generic single power law, we evaluate the spectra predicted by the disk-corona model assuming stochastic acceleration parameters that match the measured flux from NGC 1068. Assuming all sources to be intrinsically similar to NGC 1068, our findings constrain the collective neutrino emission from X-ray bright Seyfert galaxies in the northern sky, but, at the same time, show excesses of neutrinos that could be associated with the objects NGC 4151 and CGCG 420-015. These excesses result in a 2.7σsignificance with respect to background expectations. 

We report a study of the inelasticity distribution in the scattering of neutrinos of energy 80–560 GeV off nucleons. Using atmospheric muon neutrinos detected in IceCube’s sub-array DeepCore during 2012–2021, we fit the observed inelasticity in the data to a parameterized expectation and extract the values that describe it best. Finally, we compare the results to predictions from various combinations of perturbative QCD calculations and atmospheric neutrino flux models. Published by the American Physical Society2025 

Abstract The nature of dark matter remains unresolved in fundamental physics. Weakly Interacting Massive Particles (WIMPs), which could explain the nature of dark matter, can be captured by celestial bodies like the Sun or Earth, leading to enhanced self-annihilation into Standard Model particles including neutrinos detectable by neutrino telescopes such as the IceCube Neutrino Observatory. This article presents a search for muon neutrinos from the center of the Earth performed with 10 years of IceCube data using a track-like event selection. We considered a number of WIMP annihilation channels ($$\chi \chi \rightarrow \tau ^+\tau ^-$$ $\chi \chi \to {\tau }^{+}{\tau }^{-}$/$$W^+W^-$$ $W^{+}{W}^{-}$/$$b\bar{b}$$ $b\overline{b}$) and masses ranging from 10 GeV to 10 TeV. No significant excess over background due to a dark matter signal was found while the most significant result corresponds to the annihilation channel$$\chi \chi \rightarrow b\bar{b}$$ $\chi \chi \to b\overline{b}$for the mass$$m_{\chi }=250$$ $m_{\chi }=250$ GeV with a post-trial significance of$$1.06\sigma $$ $1.06\sigma$. Our results are competitive with previous such searches and direct detection experiments. Our upper limits on the spin-independent WIMP scattering are world-leading among neutrino telescopes for WIMP masses$$m_{\chi }>100$$ $m_{\chi }>100$ GeV.