Artificial intelligence (AI) technology may soon be a useful tool for doctors. It may help them better understand and treat diseases like breast cancer in ways that were never before possible. 

Rishi Rawat teaches AI at the University of Southern California' s (USC) Clinical Science Center in Los Angeles. He is part of a team of scientists who are researching how AI and machine learning can more easily recognize cancerous growths in the  breast. Rawat provides information about cancer cells to a computer. He says this data helps the machine learn. " . . You can put the data into them and they will learn the patterns and the pattern recognition. That'  s important to make decisions. "

David Agus is another USC researcher. He believes that"machines are not going to take the place of doctors. " "Computers will not treat patients, but they will help make certain decisions and look for things that the human brain can' t recognize these patterns by itself. Once a confirmed cancerous growth is removed, doctors still have to treat the patient to reduce the risk of cancer returning. The form of treatment depends on the kind of cancer. Currently, researchers take a thin piece of tissue, put it on a small piece of glass and add color to better see the cells.

That process could take days or even longer. Scientists say AI can do something better than just count cells Trough machine learning it can recognize complex patterns or structures, and learn how the cells are organized. The hope is that machines will soon be able to make a quick identification of cancer that is free of human mistakes. "All of a sudden, we have the computing power to really do it in real time. . . We couldn' t have done this, we didn' t have the computing power to do this several years ago, but now it' s all changed. "Agus adds that the process could be done "for almost no cost in the developing world. " He says that having a large amount of information about patients is important for a machine to effectively do its job in medicine.

The University of Southern California researchers are now only studying breast cancer. But doctors predict AI will one day make a difference in all forms of cancer. 

A recent study conducted by the Massachusetts Institute of Technology （MIT） has discovered that river erosion （侵蚀） can lead to increased biodiversity in areas with minimal tectonic（地壳构造的） activity. The researchers focused their attention on the Tennessee River Basin and examined how the erosion of various rock types by the river had led to the separation and diversification of a type of fish called the greenfin darter. As time passed, these separate fish populations evolved into distinct families with genetic differences.

Scientist Thomas Near observed that the greenfin darter was exclusively found in the southern half of the Tennessee River Basin. The researchers analyzed the genes of each fish in Near's data set and constructed an evolutionary tree. This tree helped them comprehend the evolution and differences of the greenfin darter species. They discovered that the fish within the same branch of the river were more closely related to each other than to the fish in other branches.

This study provides evidence that river erosion significantly impacts biodiversity in regions with low tectonic activity. It illustrates how changes in the landscape caused by river erosion can lead to the division and diversification of species over time, even in peaceful environments. These findings enhance our understanding of the mechanisms（机制） that drive biodiversity and evolution, even in areas that are not typically associated with intense tectonic activity.

Subsequently, the team discovered a strong correlation between the habitats of the greenfin darter and the type of rocks present. The southern half of the Tennessee River Basin consists of hard, tightly packed rocks, resulting in turbulent（湍急的） waves in the rivers that flow through it. This characteristic may be favored by the greenfin darter. As a result, the team assumed whether the distribution of greenfin darter habitats had been influenced by the changing rock types, as the rivers eroded the land over time. To test this assumption, the researchers developed a simulation model. Remarkably, the results confirmed their assumption.

The sun produces more than enough energy for human activities, but we still can't capture enough of it. While solar panels (太阳能电池板) have made big advances in recent years, becoming cheaper and more efficient, they just provide electricity, not storable liquid fuels, which are still in great demand.

"If you look at the global energy structure and what's needed, electricity only covers maybe 20-25%. So the question is when we have covered that 25%, what do we do next? asks Professor Reisner from Cambridge University.

His answer is to look to nature: "Plants are a huge inspiration, because they have learned over millions of years how to take up sunlight and store the energy in energy carriers. I really believe that artificial photosynthesis (光合作用) will be one part of that energy structure over the next two decades. "

When plants photosynthesize, they take up water and carbon dioxide, and use light from the sun to change these raw materials into the carbohydrates they need for growth. "We want to copy this, but we don't really want to make carbohydrates because they make a low-quality fuel, so instead of making carbohydrates we try to make something that can be more readily used," says Prof Reisner.

"We have a great theory effort, and the theory and the experiment go hand in hand," says the project leader, Prof Harry Atwater of Caltech. "We now have what's actually the worlds largest database. The bad news is that we're not likely to see fields full of photosynthesis panels any time soon. There are still major stumbling blocks. "