The authors use pictures of candy wrappers and neural networks to improve nutritional accuracy of diet-tracking apps.
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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.
Read More...Investigating momentum transfer with gall-forming wasps
The authors use the unique movements of the jumping gall wasp to study momentum transfer with potential applications in robotics and extraterrestrial research.
Read More...Identification of a Free Radical Scavenger as an Additive for Lung Transplant Preservation Solution to Inhibit Coagulative Necrosis and Extend Organ Preservation
During transfer of organs from a donor to a patient, the organs deteriorate in part due to damage by free radicals. Application of antioxidant solutions could extend organ preservation times. The authors found that vitamin E and butylated hydroxytoluene seemed to be most effective in arresting cell damage of a bovine lung.
Read More...Analyzing the effect of mycorrhizal fungi on plant communication of nutrients
The authors looked at the ability of plants to transfer phosphate between each other through mycorrhizal fungi. Specifically, they looked at whether plants with excess phosphate would transfer this nutrient to other plants that had depleted levels of phosphate.
Read More...The effects of container materials on food microwave heat times
The authors analyzed the heat transfer of different containers in the microwave aiming to identify the most optimal material of container to reduce heating time.
Read More...Effects of noise on information corruption in the quantum teleportation algorithm
In quantum computing, noise disrupts experimental results, particularly affecting the quantum teleportation algorithm used to transfer qubit states. This study explores how noise impacts this algorithm across different platforms—a perfect simulation, a noisy simulation, and real hardware.
Read More...Heat conduction: Mathematical modeling and experimental data
In this experiment, the authors modify the heat equation to account for imperfect insulation during heat transfer and compare it to experimental data to determine which is more accurate.
Read More...Analysis of the effects of positive ions and boundary layer temperature at various hypersonic speeds on boundary layer density
This study's goal was to identify the Mach numbers for which electrostatic drag and heat transfer manipulation would be most applicable inside the stratosphere. The experiments were conducted using computational fluid dynamics software. The study demonstrated that, on average, higher Mach speeds resulted in a considerably higher potential decrease in density. The study highlights that further research on the surface charge method is warranted to explore higher hypersonic speeds within the stratosphere.
Read More...Error mitigation of quantum teleportation on IBM quantum computers
Quantum computers can perform computational tasks beyond the capability of classical computers, such as simulating quantum systems in materials science and chemistry. Quantum teleportation is the transfer of quantum information across distances, relying on entangled states generated by quantum computing. We sought to mitigate the error of quantum teleportation which was simulated on IBM cloud quantum computers.
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