Search for: All records

A computational thermo-fluid flow model is used to study the effects of flow injection, flow rate, and methane concentration on microwave plasma pyrolysis of methane. Simulations of the operation of a microwave plasma torch with a mixture of argon and 1% or 10% methane in forward vortex flow mode show the confinement and advection of the power-deposition volume as well as its quenching with increasing methane concentration. 

Abstract Glycerol dialkyl glycerol tetraethers (GDGTs) are valuable proxies for reconstructing past environmental conditions but sources of analytical uncertainty remain unresolved, as highlighted by a recent inter‐laboratory comparison project. Analytical uncertainties owe in part to subjective solutions to manual peak integration, including baseline corrections, peak deconvolution, and signal smoothing. Here, we present chromatoPy, an open‐source Python package implementing a multi‐Gaussian fitting algorithm that automatically models peak co‐elution while requiring user approval of the fitted results, thereby improving peak area integration accuracy, enhancing reproducibility, and reducing the time required for peak processing. We evaluate chromatoPy through inter‐user comparisons and against manual integration using a global data set of GDGTs from marine, lacustrine, and loess sediments, demonstrating high concordance in peak areas and fractional abundances for both branched and isoprenoid GDGTs. Subtle but systematic differences are observed primarily for branched GDGTs prone to co‐elution, which is consistent with the deconvolution approach employed. By reducing analyst subjectivity and providing uncertainty estimates, chromatoPy facilitates more comparable GDGT measurements across laboratories and data sets, thereby strengthening the foundations of GDGT‐based paleoclimate and biogeochemical reconstructions. The package significantly decreases processing time while providing quantitative uncertainty estimates using Monte Carlo error propagation, enabling rapid replicate analyses. chromatoPy thus offers a robust, user‐friendly tool that enhances reproducibility and will ultimately yield more reliable paleoclimate reconstructions. 

Student focusing and noticing, which drive reasoning, are important but under researched aspects of student learning. Quadratic functions representations are perceptually and conceptually complex and thus, offer much for students to focus on and notice. Our study compared a teacher’s goals for student focusing and noticing during quadratic functions instruction with what students actually focused on and noticed. Qualitative analysis revealed some alignment but also informative ways that the teacher’s goals and student outcomes for focusing and noticing were misaligned. These results will further the field’s understanding of how students learn about quadratic functions and may have implications for student focusing and noticing of other mathematics topics as well. 

The topic of study in this report is student focusing and noticing. Specifically, we examined a teacher’s goals for student focusing and noticing and the student outcomes for focusing and noticing. The mathematics context for this research was quadratic functions and covariational reasoning. Two whole-class discussion episodes were analyzed. Results showed ways that the teacher’s goals and student outcomes were aligned and three ways that they were misaligned. These results could inform how quadratic functions are taught and how teachers can improve the alignment between their goals for student focusing and noticing and student outcomes for focusing and noticing. 

Abstract Quantum Chromodynamics predicts a phase transition from hadronic matter to quark–gluon plasma (QGP) at high temperatures and energy densities, where quarks and gluons (partons) are no longer confined within hadrons. The QGP forms in ultrarelativistic heavy-ion collisions. Anisotropic flow coefficients, quantifying the azimuthal expansion of produced matter, probe QGP properties. Flow measurements in high-energy heavy-ion collisions show a distinctive grouping of anisotropic flow for baryons and mesons at intermediate transverse momentum – a feature associated with flow imparted at the quark level, confirming QGP existence. The observation of QGP-like features in proton–proton and proton–ion collisions has sparked debate about QGP formation in smaller systems. For the first time, we demonstrate the distinctive grouping of anisotropic flow for baryons and mesons in high-multiplicity proton–lead and proton–proton collisions at the Large Hadron Collider (LHC). These results are described by a model including hydrodynamic flow followed by hadron formation via quark coalescence, consistent with the formation of partonic flowing systems in these collisions.