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Middle school math forms the basis for advanced mathematical courses leading up to the university level. Large language models (LLMs) have the potential to power next-generation educational technologies, acting as digital tutors to students. The main objective of this study was to determine whether LLMs like ChatGPT, Bard, and Llama 2 can serve as reliable middle school math tutoring assistants on three tutoring tasks: hint generation, comprehensive solution, and exercise creation.

The sequence of nitrogenous bases that make up the DNA of organisms can contain hidden mathematical sequences. Here the authors used BioPython, a programming tool, to find an organism that displays Gijswijt’s Sequence in its genome. In this manner they found that the common carp best displays Gijswijt’s Sequence in its genome.

This article investigates the study methodologies, learning strategies, and motives of spelling bee participants. The authors identify several important educational implications of this work.

This study utilizes machine learning models to predict missing and unclear signs from the Indus script, a writing system from an ancient civilization in the Indian subcontinent.

Here, the authors wanted to explore mathematical paradoxes in which there are multiple contradictory interpretations or analyses for a problem. They used ChatGPT to generate a novel dataset of fairy tales. They found statistical differences between the artificially generated text and human produced text based on the distribution of parts of speech elements.

In this study, the authors investigate whether phototaxis and odortaxis in Drosophila melanogaster occurs through linear summation of cues including light and attractive odorants.

In this study the authors looked the trajectories of cosmic rays moving through a dipole field. They found that the trajectories of cosmic rays are determined by a particle's energy and interaction with Earth's B field.

Molecules which bind to proteins that aggregate abnormally in neurodegenerative diseases could be promising drugs for these diseases. In this study, Zhang, Wu, Zhang, and Dang simulate the binding behavior of various molecules to screen for candidates which could be promising candidates for drug development.

With growing demands for ethanol, many researchers are turning to Panicum virgatum (switchgrass) as a feedstock of cellulosic ethanol. In this study, Ferris and Gillan examine the germination, biomass, nitrogen, survival, and chlorophyll absorbance of two switchgrass cultivars of grown in competition with Bromus inermis (smooth brome) with two varying levels of nitrogen fertilizer. Results presented indicate that during establishment, competition from other species has a greater effect than nitrogen fertilizer.

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors that bind to the HIV reverse transcriptase and prevent replication. Indolyl aryl sulfones (IAS) and IAS derivatives have been found to be highly effective against mutant strains of HIV-1 reverse transcriptase. Here, we analyzed molecules designed using aryl sulfone scaffolds paired to cyclic compounds as potential NNRTIs through the computational design and docking of 100 novel NNRTI candidates. Moreover, we explored the specific combinations of functional groups and aryl sulfones that resulted in the NNRTI candidates with the strongest binding affinity while testing all compounds for carcinogenicity. We hypothesized that the combination of an IAS scaffold and pyrimidine would produce the compounds with the best binding affinity. Our hypothesis was correct as the series of molecules with an IAS scaffold and pyrimidine exhibited the best average binding affinity. Additionally, this study found 32 molecules designed in this procedure with higher or equal binding affinities to the previously successful IAS derivative 5-bromo-3-[(3,5-dimethylphenyl)sulfonyl]indole-2-carboxyamide when docked to HIV-1 reverse transcriptase.