Food Rescue Program Evaluation Three Square Food Bank

With 48 million Americans currently struggling with hunger, addressing food insecurity in U.S. communities remains a persistent issue in need of a remedy. Conversely, food waste is the single largest material deposited in American landfills, with an estimated 70 billion pounds wasted annually. The recovery of this food waste, or “food rescue” in food banking jargon, offers an ideal solution to fight hunger in our communities. With Three Square Food Bank (Three Square) consistently seeking to increase food rescue and distribution in its efforts to eliminate hunger, the need to ensure operational effectiveness and efficiency through programmatic change and improvement is a constant driving force within the organization. This report provides an examination and evaluation of Three Square’s Food Rescue program in Southern Nevada

Enhancing Gravitational-Wave Science with Machine Learning

[eng] Machine learning has emerged as a popular and powerful approach for solving problems in astrophysics. We review applications of machine learning techniques for the analysis of ground-based gravitational-wave detector data. Examples include techniques for improving the sensitivity of Advanced LIGO and Advanced Virgo gravitational-wave searches, methods for fast measurements of the astrophysical parameters of gravitational-wave sources, and algorithms for reduction and characterization of non-astrophysical detector noise. These applications demonstrate how machine learning techniques may be harnessed to enhance the science that is possible with current and future gravitational-wave detectors