NCCN Cancer Center study demonstrates usability of Health Equity Report Card (HERC) tool for driving fair access to care
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Updates every hour. Last Updated: 22-Apr-2025 13:08 ET (22-Apr-2025 17:08 GMT/UTC)
Using a national survey of 88,183 adolescents in grades nine to 12, findings show marijuana use declined from 23.1% in 2011 to 15.8% in 2021, with first-time use before age 13 dropping from 8.1% to 4.9%. In 2021, use was highest among 12th graders (22.4%) and 11th graders (18.7%). Notably, in 2021, girls (17.8%) surpassed boys (13.6%) in reported use, reversing previous trends. While Asian, Hispanic, and white adolescents saw significant declines, Black adolescents reported a higher usage rate of 20.5% in 2021, revealing ongoing racial disparities in marijuana use.
Launch of a major new guidance document on conservation and human rights at CBD COP16 on Tuesday 29 October 2024..
The guidance supports the transition to human rights-based conservation, as outlined in the Kunming-Montreal Global Biodiversity Framework.
Practical tools for conservationists to support community-led conservation, by respecting and protecting the rights of Indigenous Peoples and local communities.
An authoritative introduction to international law and standards on human rights as they apply to conservation.
A shift from top-down conservation models to inclusive, community-led approaches is essential for fulfilling state commitments and meeting global biodiversity targets.
Besides helping to collect samples or spot butterflies for research projects — non-professionals can now conduct actual laboratory work alongside professional researchers. Together with Danish high schools, the University of Copenhagen has shown that "extreme citizen science" doesn’t just strengthen student motivation for science, but also provides a unique contribution to the monitoring of Denmark’s marine environment.
In earthquake-prone areas like Japan, there is a need for better prediction of soil stability to mitigate liquefaction risks. Towards this end, researchers have used machine learning models, including artificial neural networks and bagging techniques, to create accurate 3D maps of bearing layers using data from 433 locations in Setagaya, Tokyo. This approach can identify stable construction sites, enhance disaster planning, and contribute to safer urban development, making cities more resilient to liquefaction risks.