Americans willing to pay nearly $100 billion to reduce gun violence
Peer-Reviewed Publication
Updates every hour. Last Updated: 15-Jul-2025 16:11 ET (15-Jul-2025 20:11 GMT/UTC)
Gun violence takes many forms—whether it’s a school shooting, the assassination of a public figure, or the everyday realities of gang-related crime and armed robbery. Beyond the loss of life, gun violence shapes where people choose to live, affects local economies, and weighs heavily on public well-being. New research finds that Americans are willing to pay nearly $100 billion for policies that reduce gun violence by 20%, underscoring the widespread desire for stronger intervention.
A new study published in the Strategic Management Journal uncovers a significant and often-overlooked risk in microfinance: while social capital fosters financial stability in normal times, it can exacerbate default rates during crises. The research, conducted by Arzi Adbi, Matthew Lee, and Jasjit Singh, examines the loan repayment behavior of nearly two million low-income borrowers in the aftermath of India’s 2016 demonetization policy, revealing the unintended consequences of peer accountability in financial markets.
Over the past fifty years, microfinance has been hailed as a revolutionary tool for financial inclusion, particularly through group-lending models. These models rely on social connections and peer accountability to encourage loan repayment among low-income borrowers. However, as this study demonstrates, the very mechanisms that drive repayment in stable times can accelerate default rates when external crises arise.
Sarah Huskisson, doctoral candidate, Environmental Science and Policy, College of Science, received funding for the study: “A Novel Characterization of Red Panda (Ailurus spp.) Gut Health using Short-Chain Fatty Acid and Stress Hormone Concentrations.”
Researchers at the University of Plymouth and Plymouth Marine Laboratory are examining the environmental effects of sunscreen chemicals, with a new study - published in the journal Marine Pollution Bulletin - highlighting there are significant gaps in our understanding of how they might affect marine ecosystems
Machine learning is transforming the control of particle accelerators, enabling "autonomous driving" for these complex systems. Researchers from the Institute of Modern Physics and Xiamen University have developed innovative solutions to improve accelerator operation, reducing manual intervention and enhancing efficiency. By integrating reinforcement learning and virtual accelerators, they achieved seamless transfer to real-world applications, marking a significant breakthrough. This research paves the way for more efficient, intelligent control technologies in particle accelerators and sets a milestone in AI's application to advanced scientific tools.