Thursday, March 13, 2008

Off Topic: Ken Lee - What in the world is this girl singing

I just couldn't pass on by not blogging this one.
Hehehe.. I don't know if I'd be irritated or just purely annoyed on this freakin' girl singing "Ken Lee" a disastrous remake of Mariah Carey's "Without You" single.

Ken Lee Tuli bu dibo Doucho? heheh
I cant live anymore!! heheh

somebody shot that girl in the head! hehehe

Saturday, March 8, 2008

Telling smokers 'age' of lungs helps them quit

This article from MSNBC was too good to pass up..

LONDON - Smokers are more likely to kick the habit if they are told how “old” their lungs are, a British study found on Friday.

The concept of lung age — measured by comparing a smoker’s lungs to the age of a healthy person whose lungs function the same — has helped patients better understand how smoking damages health, researchers had already found.

But that information is also effective in convincing smokers to quit, said Gary Parkes, a family physician in Hertfordshire outside London, who led the study published in the British Medical Journal.

“Telling smokers their lung age significantly improves the likelihood of them quitting smoking,” Parkes and his colleagues wrote.

Smoking kills about four million people each year, according to the World Health Organization. Tobacco is highly addictive and the leading preventable cause of both cancer and heart disease.

The study in five general medical practices outside London involved 561 long-term smokers older than 35 and began with a simple test to record the volume and rate at which the volunteers exhaled air from the lungs.

One group received no detailed information about their results while the other people were given their lung age, shown a diagram of how smoking ages the lungs and told that quitting would slow the rate of damage.

Everyone was also strongly encouraged to quit and offered help to do so. One year later, saliva tests showed that 13 percent of the smokers told their lung age had quit while only 6 percent of people in the other group had stopped.

“Anybody who had good, understandable information seemed more inclined to give up,” Parkes said. “The reason may be people had dreaded the worst and realized it was still worthwhile giving up.

Benefits of early screening
The study counters research showing such health information does not prod them to quit and underscores the benefits of early screening because 16 percent of the people in the study had undiagnosed emphysema, Parkes said.

Giving people this kind of information could represent a cheap and easy way to get people to stop smoking and reduce smoking-related health problems that are putting pressure on health systems to treat.

“The cost, if you like, is certainly within the economic framework of a good deal,” Parkes said.

Thursday, March 6, 2008

Brain Scanner Can Tell What You're Looking At. (

I was browsing over my startpage at netvibe and found this very interesting news over at

Technically, this is not a new thing since MRI (magnetic resonance imagery) and other brain imaging techniques have been available for quite awhile now, but I guess it's some sort of breakthrough because now, through this promising technology, doctors can now see how our brains work in real-time.
Though, I'm more interested in the dream-capturing capability of this new technology.
I need to figure out why teens "wet dream". I was really puzzled before because I was dreaming of people (i guess they were models) whom I don't remember seeing in person or in mags or television.

A computer will soon be able to do it, simply by analyzing the activity of your brain.

That's the promise of a decoding system unveiled this week in Nature by neuroscientists from the University of California at Berkeley.

The scientists used a functional magnetic resonance imaging machine -- a real-time brain scanner -- to record the mental activity of a person looking at thousands of random pictures: people, animals, landscapes, objects, the stuff of everyday visual life. With those recordings the researchers built a computational model for predicting the mental patterns elicited by looking at any other photograph. When tested with neurological readouts generated by a different set of pictures, the decoder passed with flying colors, identifying the images seen with unprecedented accuracy.

You can read the full article here