![Microbes Cultured from Garden Soil Positively Impact Seed Germination and Plant Growth](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBdk1IIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--754c4c47c65141131eef8e980acf81e7e370b181/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/Revised%20Figure%205.jpg)
In this study, the authors investigate whether the addition of microbes from native soil enhanced the seed germination and growth of mung beans, pumpkins, and pea flower plants.
Read More...Microbes Cultured from Garden Soil Positively Impact Seed Germination and Plant Growth
In this study, the authors investigate whether the addition of microbes from native soil enhanced the seed germination and growth of mung beans, pumpkins, and pea flower plants.
Read More...Contrast-Enhanced Magnetic Resonance Imaging at Earth’s Magnetic Field Using Trace Gd3+ and Ho3+ Salts
In this study, the authors explore contrast-enhanced magnetic resonance imaging at Earth's field.
Read More...Money matters: Significant knowledge gaps exist about basic finance
In this study, the authors survey students and adults to better understand their basic financial knowledge and money saving skills to measure the extent of knowledge in each group and make comparisons between.
Read More...The Development of a Superhydrophobic Surface Using Electrolytic Deposition & Polymer Chains Precipitation
In this study, the authors were interested in developing a hydrophobic surface that will extend the lifespan of metals by reducing water exposure and other damage. The used a zinc coating on steel to pursue this effort.
Read More...Alkaloids Detection in Commonly Found Medicinal Plants with Marquis Reagent
This study investigates the presence of alkaloids in a variety of medicinal plants using the Marquis reagent. They reveal some surprising results and how useful the Marquis reagent is.
Read More...Using Graphene Oxide to Efficiently Filter Particulate Matter at High Concentrations
Air pollution has detrimental effects on both the environment and humans. Here, researchers use graphene oxide to filter particulate matter from the air. Graphene oxide filters performed better than commercially available filters, effectively removing particulate matter from the air.
Read More...The Effects of Confinement on the Associative Learning of Gallus gallus domesticus
This study aimed to determine if confinement affects associative learning in chickens. The research found that the difference in time lapsed before chickens began to consume cottage cheese before and after confinement was significant. These results suggest that confinement distresses chickens, as it impairs associative learning without inducing confusion.
Read More...The most efficient position of magnets
Here, the authors investigated the most efficient way to position magnets to hold the most pieces of paper on the surface of a refrigerator. They used a regression model along with an artificial neural network to identify the most efficient positions of four magnets to be at the vertices of a rectangle.
Read More...Effects of various alkaline carbonic solutions on the growth of the freshwater algae Chlorophyceae
Modern day fossil fuels are prone to polluting our environment, which can provide major habitat loss to many animals in our ecosystems. Algae-based biofuels have become an increasingly popular alternative to fossil fuels because of their sustainability, effectiveness, and environmentally-friendly nature. To encourage algae growth and solidify its role as an emerging biofuel, we tested basic (in terms of pH) solutions on pond water to determine which solution is most efficient in inducing the growth of algae.
Read More...Prediction of molecular energy using Coulomb matrix and Graph Neural Network
With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.
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