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Presoaking Seeds with Vinegar Improves Seed Development and Drought Tolerance in Maize Plants

D'Agate et al. | Jul 24, 2020

Presoaking Seeds with Vinegar Improves Seed Development and Drought Tolerance in Maize Plants

Climate change has contributed to the increasing annual temperatures around the world and poses a grave threat to Maize crops. Two methods proven to help combat plant drought stress effects are presoaking seeds (seeds are soaked in a liquid before planting) and the application of Acetic Acid (vinegar) to soil. The purpose of this experiment was to explore if combining these two methods by presoaking seeds with a vinegar solution can improve the seed development and plant drought tolerance of Maize plants during drought conditions.

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Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

Ramprasad et al. | Mar 18, 2020

Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

In this study, the authors test whether providing a larger dataset of glass transition temperatures (Tg) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and Tg is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's Tg, providing valuable improvements to this useful platform.

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Measuring Exoplanetary Radii Using Transit Photometry

Tang et al. | May 07, 2019

Measuring Exoplanetary Radii Using Transit Photometry

Studying exoplanets, or planets that orbit a star other than the Sun, is critical to a greater understanding the formation of planets and how Earth's solar system differs from others. In this study the authors analyze the transit light curves of three hot Jupiter exoplanets to ultimately determine if and how these planets have changed since their discovery.

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Reducing Crop Damage Caused by Folsomia candida by Providing an Alternate Food Source

Tamura et al. | May 28, 2018

Reducing Crop Damage Caused by Folsomia candida by Providing an Alternate Food Source

Tamura and Moché found that Folsomia candida, a common crop pest, prefers to consume yeast instead of lettuce seedlings. The authors confirmed that even with the availability of both lettuce seedlings and yeast in the same dish, Folsomia candida preferred to eat the yeast, thereby reducing the number of feeding injuries on the lettuce seedlings. The authors propose that using this preference for yeast may be a way to mitigate crop damage by this pest.

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An explainable AI framework for studying query complexity and hallucinations in LLM scheduling tasks

Thantron et al. | Nov 09, 2026

An explainable AI framework for studying query complexity and hallucinations in LLM scheduling tasks
Image credit: Immo Wegmann

In this study, we investigated how the complexity of a query can influence tool-use hallucinations in large language models that were tasked with setting an appointment. Using explainable AI (XAI) as a tool to test the hypothesis, we analyzed trends in hallucination rates by the type of query and saw results that when complexity and ambiguity of the query increased (such as asking for multiple days or unclear time ranges), the model was more likely to make errors due to misunderstanding time-related data from tool outputs. This shows that making large language models (LLMs) understand what seems logical to a human is still difficult, especially in complex tasks, and that knowing what causes these errors can help build more trustworthy AI systems.

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Determining the Hubble constant through the analysis of Abell clusters

Lee et al. | Sep 28, 2026

Determining the Hubble constant through the analysis of  Abell clusters
Image credit: NASA Hubble Space Telescope

Galaxy clusters offer several advantages for measuring H0 compared to traditional methods, such as Cepheid variables or Type Ia supernovae. Unlike individual stars or supernovae, clusters are less affected by local variations in stellar population or interstellar medium properties, providing a more stable and consistent measure over large cosmological distances. This work proposes using galaxy clusters as an alternative method for determining the H0. It provides an independent perspective on the H0 debate and contribute to ongoing efforts to reconcile the differing values obtained from the other two measurements.

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