Publications by authors named "D M Carrion"

Rapid urbanization and escalating climate crises place cities at the critical juncture of environmental and public health action. Urban areas are home to more than half of the global population, contributing ~ 75% of global greenhouse gas emissions. Structured surveys were completed by 191 leaders in city governments and civil society from 118 cities in 52 countries (February-April 2024).

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We extend existing techniques by using generative adversarial network (GAN) models to reduce the appearance of cast shadows in radiographs across various age groups. We retrospectively collected 11,500 adult and paediatric wrist radiographs, evenly divided between those with and without casts. The test subset consisted of 750 radiographs with cast and 750 without cast.

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Medical Physics departments primarily concentrate on clinical operations and regulatory compliance, which often restricts their ability to improve technical efficiencies. Nonetheless, developing technical capabilities is crucial as the healthcare sector increasingly depends on advanced technologies. A part-time software engineer was successfullyrecruited and integrated into the medical physics team to address operational needs and provide technical solutions.

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The Low Income Home Energy Assistance Program (LIHEAP) must adapt and evolve to keep pace with the challenges posed by climate change and increased economic strain. Urgent action is needed to improve LIHEAP to effectively address extreme heat and energy insecurity faced by low-income households and protect the health and well-being of disadvantaged groups spurred by climate change. In evaluating LIHEAP's shortcomings, we demonstrate that there is a substantial gap between program eligibility and enrollment, such that many households are not receiving this vital benefit or do so mainly when facing a crisis.

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Article Synopsis
  • Remote sensing technology enhances water quality monitoring by overcoming limitations of traditional methods, particularly in complex urban river networks.
  • The study introduces a new ensemble learning model that integrates spectral and environmental factors to improve water quality predictions in Shanghai's rivers, leveraging data from a local dataset.
  • Results show significant improvements in predictive accuracy, with the model achieving coefficient of determination (R) values around 0.52 to 0.58 for key water quality parameters, although the variability in error rates indicates room for improvement.
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