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Artificial intelligence is impacting society on a very large scale and should be included in K-12 educational content in some capacity to provide meaningful STEM experiences. Computer vision (a field of research that heavily leverages artificial intelligence) was emphasized in professional development for in-service teachers. The teachers received two to three weeks of training across two states (Arizona and Georgia) that emphasized image processing, computer vision, and machine learning using visual media. Personal Construct Theory (Kelly, 1955) was used to map changes in thinking using hierarchical cluster analysis. The research question was: How did in-service teachers' thinking regarding artificial intelligence change after partaking in remote professional development emphasizing computer vision? Dendrograms and descriptive statistics showed changes in thinking for in-service teachers in relation to artificial intelligence. There were four clusters in both the pre- and post-professional development dendrograms, but constructs shifted within clusters. Implications for practice and research are discussed. 

For decades, the use of computer vision as a component of STEM learning has been encouraged at all levels of education—from K-12 to the university levels. A program was developed to support in-service teachers’ development of computer vision. Professional development was provided to middle school teachers while middle school students also attended a summer camp on computer vision. Our research question was: After in-service teachers engaged in artificial intelligence professional development emphasizing computer vision, how did their perceptions of computer vision change? Personal Construct Theory (Kelly, 1955) was used as our methodology. Pairwise comparisons yielded constructs administered in the form of repertory grids. Hierarchical cluster analysis was performed and clusters were identified. Results showed that in-service teachers’ perspectives of computer vision changed after engaging in computer vision-based professional development. 

Artificial intelligence is impacting society on a very large scale and should be included in K-12 educational content in some capacity to provide meaningful STEM experiences. Computer vision (a field of research that heavily leverages artificial intelligence) was emphasized in professional development for in-service teachers. The teachers received two to three weeks of training across two states (Arizona and Georgia) that emphasized image processing, computer vision, and machine learning using visual media. Personal Construct Theory (Kelly, 1955) was used to map changes in thinking using hierarchical cluster analysis. The research question was: How did in-service teachers’ thinking regarding artificial intelligence change after partaking in remote professional development emphasizing computer vision? Dendrograms and descriptive statistics showed changes in thinking for in-service teachers in relation to artificial intelligence. There were four clusters in both the pre- and post-professional development dendrograms, but constructs shifted within clusters. Implications for practice and research are discussed. 

IODP Expedition 379 to the Amundsen Sea continental rise recovered latest Miocene-Holocene sediments from two sites on a drift in water depths >3900m. Sediments are dominated by clay and silty clay with coarser-grained intervals and ice-rafted detritus (IRD) (Gohl et al. 2021, doi:10.14379/iodp.proc.379.2021). Cobble-sized dropstones appear as fall-in, in cores recovered from sediments >5.3 Ma. We consider that abundant IRD and the sparse dropstones melted out of icebergs formed due to Antarctic ice-sheet calving events. We are using petrological and age characteristics of the clasts from the Exp379 sites to fingerprint their bedrock provenance. The results may aid in reconstruction of past changes in icesheet extent and extend knowledge of subglacial bedrock. Mapped onshore geology shows pronounced distinctions in bedrock age between tectonic provinces of West or East Antarctica (e.g. Cox et al. 2020, doi:10.21420/7SH7-6K05; Jordan et al. 2020, doi.org/10.1038/s43017-019-0013-6). This allows us to use geochronology and thermochronology of rock clasts and minerals for tracing their provenance, and ascertain whether IRD deposited at IODP379 drillsites originated from proximal or distal Antarctic sources. We here report zircon and apatite U-Pb dates from four sand samples and five dropstones taken from latest Miocene, early Pliocene, and Plio-Pleistocene-boundary sediments. Additional Hf isotope data, and apatite fission track and 40Ar/39Ar Kfeldspar ages for some of the same samples help to strengthen provenance interpretations. The study revealed three distinct zircon age populations at ca. 100, 175, and 250 Ma. Using Kolmogorov-Smirnov (K-S) statistical tests to compare our new igneous and detrital zircon (DZ) U-Pb results with previously published data, we found strong similarities to West Antarctic bedrock, but low correspondence to prospective sources in East Antarctica, implying a role for icebergs calved from the West Antarctic Ice Sheet (WAIS). The ~100 Ma age resembles plutonic ages from Marie Byrd Land and islands in Pine Island Bay. The ~250 and 175 Ma populations match published mineral dates from shelf sediments in the eastern Amundsen Sea Embayment as well as granite ages from the Antarctic Peninsula and the Ellsworth-Whitmore Mountains (EWM). The different derivation of coarse sediment sources requires changes in iceberg origin through the latest Miocene, early Pliocene, and Plio/Pleistocene, likely the result of changes in WAIS extent. One unique dropstone recovered from Exp379 Site U1533B is green quartz arenite, which yielded mostly 500-625 Ma detrital zircons. In visual appearance and dominant U-Pb age population, it resembles a sandstone dropstone recovered from Exp382 Site U1536 in the Scotia Sea (Hemming et al. 2020, https://gsa.confex.com/gsa/2020AM/meetingapp.cgi/Paper/357276). K-S tests yield high values (P ≥ 0.6), suggesting a common provenance for both dropstones recovered from late Miocene to Pliocene sediments, despite the 3270 km distance separating the sites. Comparisons to published data, in progress, narrow the group of potential on-land sources to exposures in the EWM or isolated ranges at far south latitudes in the Antarctic interior. If both dropstones originated from the same source area, they could signify dramatic shifts in the WAIS grounding line position, and the possibility of the periodic opening of a seaway connecting the Amundsen and Weddell Seas. https://meetingorganizer.copernicus.org/EGU21/EGU21-9151.html 

This paper presents a search for massive, charged, long-lived particles with the ATLAS detector at the Large Hadron Collider using an integrated luminosity of $$140~fb^{−1}$$ of proton-proton collisions at $$\sqrt{s}=13$$~TeV. These particles are expected to move significantly slower than the speed of light. In this paper, two signal regions provide complementary sensitivity. In one region, events are selected with at least one charged-particle track with high transverse momentum, large specific ionisation measured in the pixel detector, and time of flight to the hadronic calorimeter inconsistent with the speed of light. In the other region, events are selected with at least two tracks of opposite charge which both have a high transverse momentum and an anomalously large specific ionisation. The search is sensitive to particles with lifetimes greater than about 3 ns with masses ranging from 200 GeV to 3 TeV. The results are interpreted to set constraints on the supersymmetric pair production of long-lived R-hadrons, charginos and staus, with mass limits extending beyond those from previous searches in broad ranges of lifetime 

This report presents a comprehensive collection of searches for new physics performed by the ATLAS Collaboration during the Run~2 period of data taking at the Large Hadron Collider, from 2015 to 2018, corresponding to about 140~$$^{-1}$$ of $$\sqrt{s}=13$$~TeV proton--proton collision data. These searches cover a variety of beyond-the-standard model topics such as dark matter candidates, new vector bosons, hidden-sector particles, leptoquarks, or vector-like quarks, among others. Searches for supersymmetric particles or extended Higgs sectors are explicitly excluded as these are the subject of separate reports by the Collaboration. For each topic, the most relevant searches are described, focusing on their importance and sensitivity and, when appropriate, highlighting the experimental techniques employed. In addition to the description of each analysis, complementary searches are compared, and the overall sensitivity of the ATLAS experiment to each type of new physics is discussed. Summary plots and statistical combinations of multiple searches are included whenever possible. 

Top-quark pair production is observed in lead–lead ( $\mathrm{Pb}+\mathrm{Pb}$) collisions at $\sqrt{s_{\mathrm{NN}}}=5.02\mathrm{TeV}$at the Large Hadron Collider with the ATLAS detector. The data sample was recorded in 2015 and 2018, amounting to an integrated luminosity of $1.9{\mathrm{nb}}^{-1}$. Events with exactly one electron and one muon and at least two jets are selected. Top-quark pair production is measured with an observed (expected) significance of 5.0 (4.1) standard deviations. The measured top-quark pair production cross section is ${\sigma }_{t\overline{t}}=3.6{}_{-0.9}^{+1.0}\left(\mathrm{stat}\right){}_{-0.5}^{+0.8}\left(\mathrm{syst}\right)\mathrm{\mu }\mathrm{b}$, with a total relative uncertainty of 31%, and is consistent with theoretical predictions using a range of different nuclear parton distribution functions. The observation of this process consolidates the evidence of the existence of all quark flavors in the preequilibrium stage of the quark-gluon plasma at very high energy densities, similar to the conditions present in the early Universe. © 2025 CERN, for the ATLAS Collaboration2025CERN