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Artificial Intelligence Networks Towards Learning Without Forgetting

Kreiman et al. | Oct 26, 2018

Artificial Intelligence Networks Towards Learning Without Forgetting

In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.

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Characterization and Phylogenetic Analysis of the Cytochrome B Gene (cytb) in Salvelinus fontinalis, Salmo trutta and Salvelinus fontinalis X Salmo trutta Within the Lake Champlain Basin

Palermo et al. | Jan 24, 2014

Characterization and Phylogenetic Analysis of the Cytochrome B Gene (<em>cytb</em>) in <em>Salvelinus fontinalis</em>,<em> Salmo trutta</em> and <em>Salvelinus fontinalis X Salmo trutta</em> Within the Lake Champlain Basin

Recent declines in the brook trout population of the Lake Champlain Basin have made the genetic screening of this and other trout species of utmost importance. In this study, the authors collected and analyzed 21 DNA samples from Lake Champlain Basin trout populations and performed a phylogenetic analysis on these samples using the cytochrome b gene. The findings presented in this study may influence future habitat decisions in this region.

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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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Covalently Entrapping Catalase into Calcium Alginate Worm Pieces Using EDC Carbodiimide as a Crosslinker.

Suresh et al. | Mar 31, 2019

Covalently Entrapping Catalase into Calcium Alginate Worm Pieces Using EDC Carbodiimide as a Crosslinker.

Catalase is a biocatalyst used to break down toxic hydrogen peroxide into water and oxygen in industries such as cheese and textiles. Improving the efficiency of catalase would help us to make some industrial products, such as cheese, less expensively. The best way to maintain catalase’s conformation, and thus enhance its activity, is to immobilize it. The primary goal of this study was to find a new way of immobilizing catalase.

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Leveraging E-Waste to Enhance Water Condensation by Effective Use of Solid-state Thermoelectric Cooling

Joshi et al. | Dec 02, 2020

Leveraging E-Waste to Enhance Water Condensation by Effective Use of Solid-state Thermoelectric Cooling

Water scarcity affects upwards of a billion people worldwide today. This project leverages the potential of capturing humidity to build a high-efficiency water condensation device that can generate water and be used for personal and commercial purposes. This compact environment-friendly device would have low power requirements, which would potentially allow it to utilize renewable energy sources and collect water at the most needed location.

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