Publications by authors named "B B Love"

Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts.

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Experimental efforts supplemented by modeling gauged whether common additives found in soaps and laundry detergents interfered with polyacrylate adhesive-based capture of microplastics. On the experimental front, poly(2-ethylhexyl acrylate) (PEHA) samples were evaluated using gravimetric analysis, probe tack, and functional assessments of adhesive-coated glass slides immersed into DI water solutions containing both microparticles and additives (solvents, softeners, and non-ionic surfactants). Nylon-6 spheres and polyethylene terephthalate microplastics were chosen for adsorption using a count-based method by ImageJ imaging analysis.

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Pulmonary vein stenosis is challenging to treat due to high rate of recurrence. Multiple interventions exist but are limited by high rates of restenosis. One theory for the high rate of recurrence is vascular inflammation.

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Article Synopsis
  • Humans and machines often learn without direct feedback or supervision, relying heavily on unsupervised data.
  • There is debate around whether unsupervised learning is beneficial for humans, with mixed empirical results suggesting that self-reinforcement of predictions can be advantageous or detrimental based on the alignment of those predictions with the task.
  • The authors propose a framework to explain these mixed results and offer insights into effective learning strategies relevant to education and lifelong learning.
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