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This exploratory study delves into the complex challenge of analyzing and interpreting student responses to mathematical problems, typically conveyed through image formats within online learning platforms. The main goal of this research is to identify and differentiate various student strategies within a dataset comprising image-based mathematical work. A comprehensive approach is implemented, including various image representation, preprocessing, and clustering techniques, each evaluated to fulfill the study’s objectives. The exploration spans several methods for enhanced image representation, extending from conventional pixel-based approaches to the innovative deployment of CLIP embeddings. Given the prevalent noise and variability in our dataset, an ablation study is conducted to meticulously evaluate the impact of various preprocessing steps, assessing their potency in eradicating extraneous backgrounds and noise to more precisely isolate relevant mathematical content. Two clustering approaches—k-means and hierarchical clustering—are employed to categorize images based on student strategies that underlies their responses. Preliminary results underscore the hierarchical clustering method could distinguish between student strategies effectively. Our study lays down a robust framework for characterizing and understanding student strategies in online mathematics problem-solving, paving the way for future research into scalable and precise analytical methodologies while introducing a novel open-source image dataset for the learning analytics research community. 

A few key methodological uncertainties remain for the carbonate clumped isotope community. One is how to compare data among published data sets that are not anchored to the InterCarb Carbon Dioxide Equilibrium Scale (I‐CDES). A second is how temperature calibrations of calcite compare to those of other carbonate minerals in the I‐CDES—particularly dolomite and apatite—which can elucidate several Earth system dynamics. Previous calibrations of the clumped isotope thermometer for dolomite are discrepant from one another and variably (dis)agree with calibrations developed for calcite; apatite calibrations have not yet been compared between laboratories using carbonate‐based standardization. Here we report I‐CDES standardized values for a suite of 11 carbonates that are commonly measured by the clumped isotope community to aid future comparisons of non‐I‐CDES data sets. In addition, 17 dolomite samples (25–1,200°C) and five apatite samples (1–38°C) of known precipitation temperature were measured using carbonate‐based standardization. Excellent agreement between calcites and dolomites heated to similar temperatures (1,100–1,200°C) suggests no mineral‐specific differences in absolute acid fractionation factor. We show that calcite and dolomite regressions largely agree but are sensitive to sample characteristics, regression method, and how equations are statistically compared. We suggest that there is no need for a dolomite‐specific clumped isotope calibration, although our results suggest that further work is necessary to determine the influence of sample characteristics on this relationship. The apatite calibration equation defined in this study is statistically indistinguishable from calcite‐based calibrations; we corroborate previous findings that an apatite‐specific calibration is unnecessary.

 

An oxygenated atmosphere changed life on Earth but it also provided a negative feedback to organic matter accumulation by increasing decomposition rates. Nonetheless, dissolved organic carbon (DOC) is a huge carbon pool (> 750 Pg) and it can accumulate to high concentrations (20–100 mg C L⁻¹) in some freshwater aquatic systems, yet it is not clear why. Here, we examine DOC in several Greenland lakes with varying DOC concentrations and identify processes that could alter its composition to make it increasingly recalcitrant. Δ¹⁴C aging of DOC corresponded with increased DOC concentrations, slower degradation rates, changes in isotope ratios and optical properties, all suggesting that photochemical and microbial degradation processes contributed to recalcitrance. Young DOC degradation was stimulated by phosphorus, but older DOC was not, suggesting an important role for nutrients early in degradation. Photochemical processing coupled with decreased habitat diversity in hydrologically isolated systems may enable recalcitrant DOC to accumulate with important implications for Earth's carbon and oxygen cycles.

 

The 2nd Annual WPI-UMASS-UPENN EDM Data Min- ing Challenge required contestants to predict efficient test taking based on log data. In this paper, we describe our theory-driven and psychometric modeling approach. For feature engineering, we employed the Log-Normal Response Time Model for estimating latent person speed, and the Generalized Partial Credit Model for estimating latent person ability. Additionally, we adopted an n-gram feature approach for event sequences. For training a multi-label classifier, we distinguished inefficent test takers who were going too fast and those who were going too slow, instead of using the provided binary target label. Our best-performing ensemble classifyer comprised three sets of low-dimensional classiers, dominated by test-taker speed. While our classi- er reached moderate performance, relative to competition leaderboard, our approach makes two important contributions. First, we show how explainable classiers could provide meaningful predictions if results can be contextualized to test administrators who wish to intervene or take action. Second, our re-engineering of test scores enabled us to incorporate person ability into the estimation. However, ability was hardly predictive of efficient behavior, leading to the conclusion that the target label's validity needs to be questioned. The paper concludes with tools that are helpful for substantively meaningful log data mining. 

Transplantation of human embryonic stem cell (hESC)-derived neural progenitors is a potential treatment for neurological disorders, but relatively little is known about the time course for human neuron maturation after transplantation and the emergence of morphological and electrophysiological properties. To address this gap, we transplanted hESC-derived human GABAergic interneuron progenitors into the mouse hippocampus, and then characterized their electrophysiological properties and dendritic arborizations after transplantation by means of ex vivo whole-cell patch clamp recording, followed by biocytin staining, confocal imaging and neuron reconstruction software. We asked whether particular electrophysiological and morphological properties showed maturation-dependent changes after transplantation. We also investigated whether the emergence of particular electrophysiological properties were linked to increased complexity of the dendritic arbors. Human neurons were classified into five distinct neuronal types (Type I-V), ranging from immature to mature fastspiking interneurons. Hierarchical clustering of the dendritic morphology and Sholl analyses suggested four morphologically distinct classes (Class A-D), ranging from simple/immature to highly complex. Incorporating all of our data regardless of neuronal classification, we investigated whether any electrophysiological and morphological features correlated with time post-transplantation. This analysis demonstrated that both dendritic arbors and electrophysiological properties matured after transplantation. 

GABAergic interneuron dysfunction has been implicated in temporal lobe epilepsy (TLE), autism, and schizophrenia. Inhibitory interneuron progenitors transplanted into the hippocampus of rodents with TLE provide varying degrees of seizure suppression. We investigated whether human embryonic stem cell (hESC)-derived interneuron progenitors (hESNPs) could differentiate, correct hippocampal-dependent spatial memory deficits, and suppress seizures in a pilocarpine-induced TLE mouse model. We found that transplanted ventralized hESNPs differentiated into mature GABAergic interneurons and became electrophysiologically active with mature firing patterns. Some mice developed hESNP-derived tumor-like NSC clusters. Mice with transplants showed significant improvement in the Morris water maze test, but transplants did not suppress seizures. The limited effects of the human GABAergic interneuron progenitor grafts may be due to cell type heterogeneity within the transplants. 

Increased use and improved methodology of carbonate clumped isotope thermometry has greatly enhanced our ability to interrogate a suite of Earth‐system processes. However, interlaboratory discrepancies in quantifying carbonate clumped isotope (Δ₄₇) measurements persist, and their specific sources remain unclear. To address interlaboratory differences, we first provide consensus values from the clumped isotope community for four carbonate standards relative to heated and equilibrated gases with 1,819 individual analyses from 10 laboratories. Then we analyzed the four carbonate standards along with three additional standards, spanning a broad range of δ⁴⁷and Δ₄₇values, for a total of 5,329 analyses on 25 individual mass spectrometers from 22 different laboratories. Treating three of the materials as known standards and the other four as unknowns, we find that the use of carbonate reference materials is a robust method for standardization that yields interlaboratory discrepancies entirely consistent with intralaboratory analytical uncertainties. Carbonate reference materials, along with measurement and data processing practices described herein, provide the carbonate clumped isotope community with a robust approach to achieve interlaboratory agreement as we continue to use and improve this powerful geochemical tool. We propose that carbonate clumped isotope data normalized to the carbonate reference materials described in this publication should be reported as Δ₄₇(I‐CDES) values for Intercarb‐Carbon Dioxide Equilibrium Scale.