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Marine heatwaves (MHWs) are warm sea surface temperature (SST) anomalies with substantial ecological and economic consequences. Observations of MHWs are based on relatively short instrumental records, which limit the ability to forecast these events on decadal and longer timescales. Paleoclimate reconstructions can extend the observational record and help to evaluate model performance under near future conditions, but paleo-MHW reconstructions have received little attention, primarily because marine sediments lack the temporal resolution to record short-lived events. Individual foraminifera analysis (IFA) of paleotemperature proxies presents an intriguing opportunity to reconstruct past MHW variability if strong relationships exist between SST distributions and MHW metrics. Here, we describe a method to test this idea by systematically evaluating relationships between MHW metrics and SST distributions that mimic IFA data using a 2000-member linear inverse model (LIM) ensemble. Our approach is adaptable and allows users to define MHWs based on multiple duration and intensity thresholds and to model seasonal biases in five different foraminifera species. It also allows uncertainty in MHW reconstructions to be calculated for a given number of IFA measurements. An example application of our method at 12 north Pacific locations suggests that the cumulative intensity of short-duration, low-intensity MHWs is the strongest target for reconstruction, but that the error on reconstructions will rely heavily on sedimentation rate and the number of foraminifera analyzed. This is evident when a robust transfer function is applied to new core-top oxygen isotope data from 37 individualGlobigerina bulloidesat a site with typical marine sedimentation rates. In this example application, paleo-MHW reconstructions have large uncertainties that hamper comparisons to observational data. However, additional tests demonstrate that our approach has considerable potential to reconstruct past MHW variability at high sedimentation rate sites where hundreds of foraminifera can be analyzed. 

The ability to manufacture complex design geometries via Additive Manufacturing (AM) has led to a rapid growth in advancing the design methods, fabrication, and application of Triply Periodic Minimal Surface (TPMS) lattices with minimal surface topologies. Due to its zero-mean curvature, TPMS lattices can be additively manufactured without any sacrificial support structures and offer both design and manufacturing engineers, unprecedented control over the local physical properties (surface area, relative density, etc.) and local mechanical properties (flexural strength, Young’s modulus, etc.). TPMS lattices are of high interest for a wide range of applications such as biomedical implants, energy absorption, and surface fluidic applications such as heat exchangers, and energy storage. Recent advancements in functionally graded TPMS lattice design by varying local lattice geometry has shown to result in different mechanical performance. However, there have been limited studies in understanding the functional grading of AM process conditions (e.g., Laser-Powder Bed Fusion in this study) and lattice sheet thickness to better map the design-processing conditions-properties. The goal of this study is to achieve similar mechanical properties in TPMS sheet lattices with two different TPMS sheet thicknesses by varying laser processing conditions (e.g., contour and hatch conditions in this study). Quasi-static tensile testing of solid samples with corresponding AM conditions and 3-point bending tests of TPMS lattices were performed in accordance with ASTM E8 and ASTM E290, respectively. It was observed that the flexural properties of the 0.75 mm and 0.25 mm TPMS lattices are similar and exhibit different properties with different scan strategies and speed variations under contour-only and hatch-only laser scanning strategies. Also, the 0.75 mm TPMS sheet lattices exhibited 79 % higher flexural stiffness than the 0.25 mm sheet lattices. It was also observed that this observed trend was reversed in the case of tensile properties. Findings from this study can provide new directions towards achieving gradient TPMS lattice designs with varying local mechanical performance by grading the laser scanning strategies to achieve desired mechanical properties and surface topologies. 

Segmenting autophagic bodies in yeast TEM images is a key technique for measuring changes in autophagosome size and number in order to better understand macroautophagy/autophagy. Manual segmentation of these images can be very time consuming, particularly because hundreds of images are needed for accurate measurements. Here we describe a validated Cellpose 2.0 model that can segment these images with accuracy comparable to that of human experts. This model can be used for fully automated segmentation, eliminating the need for manual body outlining, or for model-assisted segmentation, which allows human oversight but is still five times as fast as the current manual method. The model is specific to segmentation of autophagic bodies in yeast TEM images, but researchers working in other systems can use a similar process to generate their own Cellpose 2.0 models to attempt automated segmentations. Our model and instructions for its use are presented here for the autophagy community. 

This Perspectives on Practice manuscript focuses on an innovation associated with “Engaging Teachers in the Powerful Combination of Mathematical Modeling and Social Justice: The Flint Water Task” from Volume 7, Issue 2 ofMTE. We built on Aguirre et al.’s (2019) integration of mathematical modeling and social justice issues in mathematics teacher education to similarly integrate statistical investigations with social justice issues. 

In 1908, Felix Klein suggested that to mend the discontinuity that prospective secondary teachers face, university instruction must account for teachers’ needs. More than a century later, problems of discontinuity remain. Our project addresses the dilemma of discontinuity in university mathematics courses through simulating core teaching practices in mathematically intensive ways. In other words, we interpret teachers’ needs to include integrating content and pedagogy. We argue that doing so has the potential to impact teachers’ competence. To make this argument, we report fndings from the Mathematics of Doing, Understanding, Learning, and Educating for Secondary Schools (MODULE(S2)) project. The results are based on data from 324 prospective secondary mathematics teachers (PSMTs) enrolled in courses using curricular materials developed by the project in four content areas (algebra, geometry, modeling, and statistics). We operationalized competence in terms of PSMTs’ content knowledge for teaching and their motivation for enacting core teaching practices. We examined pre- and post-term data addressing these constructs. We found mean increases in PSMTs’ outcomes in content knowledge for teaching and aspects of motivation. 

There is a lack of teacher education materials that develop equity literacy in content courses for preservice secondary mathematics teachers. In response, we created teacher education curriculum materials for introductory statistics that include an integrated focus on developing equity literacy and critical statistical literacy. In this article, we provide an overview of our materials’ design along with a detailed look at one activity regarding racial demographics and tracking in high school STEM courses. We present evidence regarding the positive impact of these materials on the teacher candidates’ competency, value, and likelihood of applying their equity literacy and critical statistical literacy. Implications for mathematics teacher educators working to develop equity literacy together with content knowledge are discussed. 

In the past two decades, there has been a trend in materials for mathematics courses for prospective secondary teachers: more opportunities for teachers to “apply mathematics to teaching”. That is, materials increasingly highlight how mathematical knowledge learned in the course can be useful in secondary teaching, and provide opportunities for teachers to harness this knowledge in simulations of teaching. There is little known about the effects of this curricular reform on teachers’ competence. In this report, we use data from the Mathematics of Doing, Understanding, Learning, and Educating for Secondary Schools MODULE(S2) project to examine the potential impact of using such curricular materials. The data include over 300 prospective secondary teachers’ responses to 3 sets of Likert pre-/post-term surveys addressing: mathematical knowledge for teaching; expectancy for enacting selected core teaching practices; and valuing of enacting these practices. We found mean increases across the survey results. We conclude with directions for future research on the impact of this curricular reform.