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Discover Latest #CERN News, Articles and Videos with Contenting
CERN, the European Organization for Nuclear Research, is a world-renowned particle physics research center located in Geneva, Switzerland. The organization is known for its large-scale scientific projects, such as the Large Hadron Collider, the world’s largest and most powerful particle accelerator. Every year, CERN produces news articles, videos, and other media that discuss the organization’s research and activities. These materials are available on the CERN website, through its various social media accounts, and through other news outlets. The following are some of the latest CERN news, articles, and videos. • CERN releases new video on the world’s largest particle accelerator • CERN announces new results from the Large Hadron Collider • CERN scientists explain the latest advances in particle physics • CERN celebrates the completion of its ambitious accelerator project • CERN scientists win Nobel Prize for groundbreaking discoveries • CERN releases new video on the science behind the Large Hadron Collider • CERN issues statement on the future of particle physics research • CERN announces the discovery of new particles • CERN releases new video on the history of particle physics • CERN announces
Do Multiple COVID-19 Vaccine Doses Affect Metabolism? | Research Communities by Springer Nature
COVID-19 vaccines save lives, but concerns remain about long-term effects after multiple doses. New research from Murdoch University’s Australian National Phenome Centre reveals that multiple doses do not cause lasting metabolic or inflammatory changes.
Rethinking Trust, Privacy, and Power in Digital Health Collaborations | Research Communities by Springer Nature
Explore the ethics behind digital health public-private partnerships in this blog post. A new scoping review published in npj Digital Medicine highlights privacy, trust, and governance concerns—and gives 15 practical recommendations to guide responsible collaborations.
Uncovering Risk Factors for Heart Disease and Predicting Outcomes Using Machine Learning Approaches | Research Communities by Springer Nature
This study aims to create a robust machine learning model capable of accurately discerning the presence of heart-related disorders. The aim of this study is to find the best machine learning classification model that is most suitable for predicting risk factors related to heart disease.
The potential of second-growth forests for bird diversity in a small holder landscape – The Applied Ecologist
Mareike Kortmann and co-authors share a summary about their latest study which focusses on the ability of sample coverage to impact diversity measures of bird communities in tropical lowland forests. Tropical old-growth forests are disappearing at an alarming rate, leading to concerning biodiversity loss. But amidst this global decline, some forest areas are also recovering.…
Hidden Chemistry in Winter Haze: How Aerosol Water Drives New Pollutant Formation | Research Communities by Springer Nature
Chemicals of emerging concern (CECs) are raising new challenges for environmental health. Our study reveals how aerosol water drives their transformation in the atmosphere, calling for greater attention to transformation products in chemical risk assessment and management.
Modeling Forest Growth in a Changing Climate: Addressing the "Chicken-and-Egg" Paradox of Cause and Consequence | Research Communities by Springer Nature
A recent article published in Current Forestry Reports offers a comprehensive review of both established and emerging theories for modeling growth in forest ecosystems, with particular emphasis on the longstanding "chicken-and-egg dilemma" concerning the interplay between carbon sources and sinks