Can any science really be soft?

When I worked as a reporter there were two types of news: hard news and soft news.

The hard news reporters covered things that not only had immediate impact, but had numbers to back up the importance. These stories — crimes, disasters, accidents, fires, etc. — zoomed to the front page. The soft news reporters, who covered features and human interest beats, typically had their stories inserted into the inner reaches of the feature sections, or they waited patiently for the Sunday edition to get more exposure.

I won’t lie. Hard news reporters had a little more swagger in the newsroom.

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Fascinatin’ Rhythm

Mickey Hart of Grateful Dead fame is known for pushing boundaries. A prime force behind the ethnically diverse genre known as world music, Hart won a Grammy for 2007’s “Global Drum Project.” His brand-new album, “Mysterium Tremendum,” goes way beyond globetrotting to encompass the rhythms of the entire universe. And some of the most far-out sounds on the record, literally, were created by Penn State’s Mark Ballora.

 Ballora, who teaches music technology at Penn State, creates “sonifications,” aural patterns in which data sets are represented as sound. As he explains, they’re “just like visualizations, except they’re aimed at the ear instead of the eye.” His compositions are incorporated as backing tracks on Hart’s new album.

In this fascinating TED talk given in December, Ballora shares examples of his oeuvre, taking rapt listeners on a sonic tour from the surface of the sun through the solar system and beyond, arriving at last at sounds that represent the echoes of the Big Bang. Though we can’t see them, he says, these are “the rhythms of space time that underlie the pulsations of our existence.”

Unlike composers of the late-night “Hearts of Space” genre, Ballora says, he strives to be true to the actual data, to create sonifications that are “both musically compelling and scientifically informative.”

Is it music? Is it science? Does it matter?

Pythagoras and Galileo, Ballora points out to his TED listeners, never saw the two as separate.

“The distinction is a recent imposition.”

The mall is on fire!

We need a better way to help the banking industry and its regulators make decisions based on sound information and avert another near-collapse of global financial system, says John Lietchy, marketing professor in Penn State’s Smeal College of Business, in the April 12 issue of Nature.

To make his point more understandable to the non-specialist, Liechty compares the global financial system to a shopping mall that requires customers to buy tickets in order to enter and exit the mall. A statistical model can be built to track and predict door traffic – when and where and how many shoppers enter and exit the mall. But what happens if a store in the mall catches fire and shoppers rush for the exits and the ticket-takers are overwhelmed? A fire in the mall, Liechty says, is analogous to a credit-confidence crisis, when banks are unwilling to make loans or accept collateral in exchange for securing debts.

The models now in use, he says, are fine for measuring risk when financial markets act conventionally, i.e., when the mall is operating normally. But current models lack crucial data — about the interconnectivity between financial houses, for example, and the capacity of markets to execute trades — that undermines their reliability in times of crisis, i.e., when the mall catches fire.

The question is, can new scientific models be constructed that predict shopper behavior (how banks and other financiers will act) when a fire (a credit-confidence crisis) breaks out? Liechty offers some interesting thoughts.

Liechty knows his way around banks and their regulators. The Office of Financial Research, a new federal oversight agency established by the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, grew from an idea that he outlined at a February 2009 conference on financial risk.

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