The benefits of regular exercise are well documented but there's a new bonus to add to the ever-growing list. New researchers found that middle-aged women who were physically fit could be nearly 90 percent less likely to develop dementia (失智症) in later life and is they did, it came on a decade later than less sporty women.

Lead researcher Dr. Helena Horder, of the University of Gothenburg in Sweden, said: "These findings are exciting because it's possible that improving people's cardiovascular (心血管的) fitness in middle age could delay or even prevent them from developing dementia."

For the study, 191 women with an average age of 50 took a bicycle exercise test until they were exhausted to measure their peak (最大值的) cardiovascular capacity. The average peak workload was measured at 103 watts. A total of 40 women met the criteria for a high fitness level, or 120 watts or higher.

A total of 92 women were in the medium fitness category: and 59 women were in the low fitness category, defined as a peak workload of 80 watts or less, or having their exercise tests stopped because of high blood pressure, chest pain or other cardiovascular problems.

These women were then tested for dementia six times over the following four decades. During that time, 44 of the women developed dementia. Five percent of the highly fit women developed dementia, compared to 25 percent of the women with medium fitness and 32 percent of the women with low fitness

"However, this study does not show cause and effect between cardiovascular fitness and dementia it only shows an association. More research is needed to see if improved fitness could have a positive effect on the risk of dementia and also to look at when during a lifetime a high fitness level is most important" She also admitted that a relatively small number of women were studied, all of whom were form Sweden so the results might not be applicable to other groups.

A machine can now not only beat you at chess, it can also outperform you in debate. Last week, in a public debate in San Francisco, a software program called Project Debater beat its human opponents, including Noa Ovadia, Israel's former national debating champion.

Brilliant though it is, Project Debater has some weaknesses. It takes sentences from its library of documents and prebuilt arguments and strings them together. This can lead to the kinds of errors no human would make. Such wrinkles will no doubt be ironed out, yet they also point to a fundamental problem. As Kristian Hammond, professor of electrical engineering and computer science at Northwestern University, put it: "There's never a stage at which the system knows what it's talking about."

What Hammond is referring to is the question of meaning, and meaning is central to what distinguishes the least intelligent of humans from the most intelligent of machines. A computer works with symbols. Its program specifies a set of rules to transform one string of symbols into another. But it does not specify what those symbols mean. Indeed, to a computer, meaning is irrelevant. Humans, in thinking, talking, reading and writing, also work with symbols. But for humans, meaning is everything. When we communicate, we communicate meaning. What matters is not just the outside of a string of symbols, but the inside too, not just how they are arranged but what they mean.

Meaning emerges through a process of social interaction, not of computation, interaction that shapes the content of the symbols in our heads. The rules that assign meaning lie not just inside our heads, but also outside, in society, in social memory, social conventions and social relations. It is this that distinguishes humans from machines. And that's why, however astonishing Project Debater may seem, the tradition that began with Socrates and Confucius will not end with artificial intelligence.

"What would the world be if there were no hunger?" It's a question that Professor Crystal would ask her students. They found it hard to answer, she wrote later, because imagining something that isn't part of real life—and learning how to make it real—is a rare skill. It is taught to artists and engineers, but much less often to scientists. Crystal set out to change that, and helped to create a global movement. The result一an approach known as systems thinking—is now seen as essential in meeting global challenges.

Systems thinking is crucial to achieving targets such as zero hunger and better nutrition because it requires considering the way in which food is produced, processed, delivered and consumed, and looking at how those things intersect (交叉) with human health, the environment, economics and society. According to systems thinking, changing the food system—or any other network- requires three things to happen. First, researchers need to identify all the players in that system, second, they must work out how they relate to each other, and third, they need to understand and quantify the impact of those relationships on each other and on those outside the system.

Take nutrition. In the latest UN report on global food security, the number of undernourished (营养不良) people in the world has been rising, despite great advances in nutrition science. Tracking of 150 biochemicals in food has been important in revealing the relationships between calories, sugar, fat and the occurrence of common diseases. But using machine learning and artificial intelligence, some scientists propose that human diets consist of at least 26,000 biochemicals—and that the vast majority are not known. This shows that we have some way to travel before achieving the first objective of systems t hinking - which,in this example, is to identify more constituent parts of the nutrition system.

A systems approach to creating change is also built on the assumption that everyone in the system has equal power. But as some researchers find, the food system is not an equal one. A good way to redress (修正) such power imbalance is for more universities to do what Crystal did and teach students how to think using a systems approach.

More researchers, policymakers and representatives from the food industry must learn to look beyond their direct lines of responsibility and adopt a systems approach. Crystal knew that visions alone don't produce results, but concluded that "we'll never produce results that we can't envision".