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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. 

Exhumation and cooling pathways of mid‐crustal metamorphic rocks in the western Nepal Himalaya can be replicated by fold‐thrust belt structures with displacement localized along discrete décollements. New and published muscovite⁴⁰Ar/³⁹Ar, zircon U‐Th/He, and apatite fission track cooling ages, peak temperature estimates, geologic mapping, and basin data are integrated with thermokinematic forward models to constrain the geometry, kinematics, and rates of shortening in far western Nepal. The best fit to peak temperatures, cooling ages, and basin accumulation data is achieved with a largely in‐sequence kinematic order, with out‐of‐sequence motion on the Ramgarh‐Munsiari thrust. Fast rates (∼20–40 mm/yr) are required during shortening on early, large displacement faults at ∼23–12 Ma and decrease to ∼10–15 mm/yr during formation of the Lesser Himalayan duplex until ∼1 Ma. Thermokinematic models highlight the relationship between peak temperature, geometry, and shortening on the large displacement Main Central and Ramgarh‐Munsiari thrusts. In the thermokinematic models, we observe a relationship between the location of frontal ramps for the faults that displace lower Lesser Himalayan units and the ∼375°C isotherm, immediately before the ramp becomes active. These correlations suggest that temperature exerts a first‐order control on thrust geometry in a hot orogen. Viable models highlight the position of active ramps, kinematic order of faults, timing of fault motion, and reduction in shortening rates that are required to reproduce the surface geology, basin accumulation, peak temperature conditions, and timing of exhumation. Cooling ages are far more sensitive to the age of fault motion than the rate of fault motion.

 

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. 

Infrared thermography (IRT) is a non-destructive technique capable of detection and localisation of hidden subsurface defects in components of transportation infrastructure, such as concrete bridges, thereby contributing to structural health monitoring (SHM). Addressing the lack of research on subsurface defect detection in concretes by convection heat exchange, and regarding the importance of laboratory studies for proper implementation of IRT, this paper presents results from recent laboratory investigations of IRT on concrete slabs with simulated hidden defects using a convective thermal excitation mechanism. The concrete slabs in this study had simulated defects ranging 5–25 mm in depth from the surface. These studies show the effect of initial temperature, heating/cooling process, temperature range and defect depth on thermal contrast in the concrete slabs. Furthermore, this paper compares the performance of the IRT as a non-contact sensor and thermocouples attached to the surface, in the evaluation of the thermal contrast on slabs with various defect depth. The dependence of maximum thermal contrast on the initial temperature and defect depth is explored using multivariate linear regression.

 

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 

A search for the nonresonant production of Higgs boson pairs in the$HH\to b\overline{b}{\tau }^{+}{\tau }^{-}$channel is performed using$140{\mathrm{fb}}^{-1}$of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. The analysis strategy is optimized to probe anomalous values of the Higgs boson self-coupling modifier${\kappa }_{\lambda }$and of the quartic$HHVV$($V=W,Z$) coupling modifier${\kappa }_{2V}$. No significant excess above the expected background from Standard Model processes is observed. An observed (expected) upper limit${\mu }_{HH}<5.9(3.3)$is set at 95% confidence-level on the Higgs boson pair production cross section normalized to its Standard Model prediction. The coupling modifiers are constrained to an observed (expected) 95% confidence interval of$-3.1<{\kappa }_{\lambda }<9.0$($-2.5<{\kappa }_{\lambda }<9.3$) and$-0.5<{\kappa }_{2V}<2.7$($-0.2<{\kappa }_{2V}<2.4$), assuming all other Higgs boson couplings are fixed to the Standard Model prediction. The results are also interpreted in the context of effective field theories via constraints on anomalous Higgs boson couplings and Higgs boson pair production cross sections assuming different kinematic benchmark scenarios.

© 2024 CERN, for the ATLAS Collaboration2024CERN 

A search for leptoquark pair production decaying into$$te^- \bar{t}e^+$$$t{e}^{-}\overline{t}{e}^{+}$or$$t\mu ^- \bar{t}\mu ^+$$$t{\mu }^{-}\overline{t}{\mu }^{+}$in final states with multiple leptons is presented. The search is based on a dataset ofppcollisions at$$\sqrt{s}=13~\text {TeV} $$$\sqrt{s}=13\text{TeV}$recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$$^{-1}$$$_{}^{-1}$. Four signal regions, with the requirement of at least three light leptons (electron or muon) and at least two jets out of which at least one jet is identified as coming from ab-hadron, are considered based on the number of leptons of a given flavour. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No excess above the Standard Model background prediction is observed and 95% confidence level limits on the production cross section times branching ratio are derived as a function of the leptoquark mass. Under the assumption of exclusive decays into$$te^{-}$$$t{e}^{-}$($$t\mu ^{-}$$$t{\mu }^{-}$), the corresponding lower limit on the scalar mixed-generation leptoquark mass$$m_{\textrm{LQ}_{\textrm{mix}}^{\textrm{d}}}$$$m_{{\text{LQ}}_{\text{mix}}^{\text{d}}}$is at 1.58 (1.59) TeV and on the vector leptoquark mass$$m_{{\tilde{U}}_1}$$$m_{{\tilde{U}}_1}$at 1.67 (1.67) TeV in the minimal coupling scenario and at 1.95 (1.95) TeV in the Yang–Mills scenario.