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Scientists use knowledge from climate system modeling to develop global prediction system for COVID-19 pandemic

The campus of Lanzhou University. Credit: Chuwei Liu

At the time of writing, coronavirus disease 2019 (COVID-19) is seriously threatening human lives and health throughout the world. Before effective vaccines and specific drugs are developed, non-pharmacological interventions and numerical model predictions are essential. To this end, a group led by Professor Jianping Huang from Lanzhou University, China, developed the Global Prediction System of the COVID-19 Pandemic (GPCP).

Jianping Huang is a Professor in the College of Atmospheric Sciences and a Director of the Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, China. He has long been dedicated to studying long-term climate , dust-cloud interaction, and semi-arid climate change by combining field observations and theoretical research. Lockdown in early 2020 seriously affected his research. Therefore, stuck at home, he held online discussions with his on how their experience of developing climate system models might be able to contribute to fighting the pandemic. He didn’t expect much response, but was surprised when many of his colleagues responded enthusiastically.

Therefore, he and his team combined the results of 30 years of work in statistical dynamic numerical weather prediction methods, and developed the GPCP based on the traditional Susceptible-Infected-Recovered (SIR) infectious disease . The improved methods and results were published in Atmospheric and Ocean Science Letters.

In order to combine epidemiological data and models, the Levenberg-Marquardt (LM) parameter optimization algorithm was proposed to identify epidemiological models, thereby constructing a Statistical-SIR model. The LM algorithm introduces a damping coefficient when calculating the Hessian matrix by the traditional least-squares method, thereby combining the advantage of the Gauss-Newton method and gradient descent method and improving the stability of parameters.

“From the simulation results of four selected countries with relatively high numbers of confirmed cases, the Statistical-Susceptible-Infected-Recovered model using the LM algorithm

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Lowering Your Cancer Risk | NIH News in Health

February 2021






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Healthy Living for Cancer Prevention

Most people know someone who’s had cancer: a family member, a friend, a loved one. Who gets it can sometimes seem random. But there are many things you can do to reduce your risk.

Cancer can start almost anywhere in the body. Normally, your cells grow and divide to form new cells as the body needs them. When a cell is old or becomes damaged, it dies. Then a new cell takes its place.

But when cancer develops, this orderly process breaks down. Cancer cells divide without stopping. They can then spread into surrounding tissues or other parts of the body.

Causes of Cancer

Cancer starts with damage to the genesSegments of DNA that contain instructions for building the molecules that make the body work. that control the way cells function. Many things you’re exposed to over your lifetime can damage genes. These include chemicals, radiation, tobacco, alcohol, and others. Your body has ways to repair the damage, but they don’t always work perfectly.

As you age, your body has had more time to build up damage. And the normal aging process causes other changes in cells that help cancer develop. These factors make cancer more likely to appear as you age.

“Fortunately, most cancers do not develop as a result of a single exposure,” explains NIH researcher Dr. Erikka Loftfield, who studies cancer prevention. “Typically, you don’t have just one cause for a given cancer. And some potential risk factors, like cigarette smoking and diet, are changeable.”

Because damage to your genes builds up slowly over time, there are many opportunities for prevention.

“Not smoking, maintaining a healthy weight, getting enough