Scientists from US, France, Canada win Nobel for laser work
By DAVID KEYTON and JIM HEINTZ
Tuesday, October 2
STOCKHOLM (AP) — Three scientists from the United States, Canada and France won the Nobel Prize in physics Tuesday for work with lasers described as revolutionary and bringing science fiction into reality.
The American, Arthur Ashkin of Bell Laboratories in New Jersey, entered the record books of the Nobel Prizes by becoming the oldest laureate at age 96. Donna Strickland, of the University of Waterloo in Canada, became the first woman to win a Nobel in three years and is only the third to have won the prize for physics.
Frenchman Gerard Mourou of the Ecole Polytechnique and University of Michigan will share half of the 9 million kronor ($1.01 million) the prize carries with Strickland; Ashkin gets the other half.
Sweden’s Royal Academy of Sciences, which chose the winners, said Ashkin’s development of “optical tweezers” that can grab tiny particles such as viruses without damaging them realized “an old dream of science fiction — using the radiation pressure of light to move physical objects.”
The tweezers are “extremely important for measuring small forces on individual molecules, small objects, and this has been very interesting in biology, to understand how things like muscle tissue work, what are the molecule motors behind the muscle tissue,” said David Haviland of the academy’s Nobel committee.
Strickland and Mourou helped develop short and intense laser pulses that have broad industrial and medical applications, including laser eye surgery and highly precise machine cutting. The academy said their 1985 article on the technique was “revolutionary.”
“With the technique we have developed, laser power has been increased about a million times, maybe even a billion,” Mourou said in a video statement released by Ecole Polytechnique.
Strickland’s award was the first Nobel Prize in physics to go to a woman since 1963, when it was won by Maria Goeppert-Mayer; the only other woman to win for physics was Marie Curie in 1903.
“Obviously, we need to celebrate women physicists because we’re out there. And hopefully in time, it’ll start to move forward at a faster rate, maybe,” Strickland said in a phone call with the academy after the prize announcement.
Michael Moloney, CEO of the American Institute of Physics, praised all the laureates.
“It is also a personal delight to see Dr. Strickland break the 55-year hiatus since a woman has been awarded a Nobel Prize in physics, making this year’s award all the more historic,” Moloney said.
He credited the work of all three with “expanding what is possible at the extremes of time, space and forms of matter.”
Ashkin’s tweezers can be used to hold and manipulate proteins, DNA and other biomolecules to study their mechanical properties or stimulate them, said Erwin Peterman, a physicist at Vrije Universiteit Amsterdam, who called the award “a great recognition for this visionary scientist who was ahead of his time.”
On Monday, American James Allison and Japan’s Tasuku Honjo won the Nobel medicine prize for groundbreaking work in fighting cancer with the body’s own immune system.
The winner or winners of the Nobel chemistry prize will be announced Wednesday, followed by the peace prize on Friday. The economics prize, which is not technically a Nobel, will be announced Oct. 8.
Heintz reported from Moscow. Malcolm Ritter in New York, Samuel Petrequin in Paris and Frank Jordans in Berlin contributed.
Safe, efficient self-driving cars could block walkable, livable communities
October 2, 2018
Assistant Professor of Community and Regional Planning, University of Nebraska-Lincoln
Daniel Piatkowski does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
University of Nebraska-Lincoln provides funding as a member of The Conversation US.
Almost exactly a decade ago, I was cycling in a bike lane when a car hit me from behind. Luckily, I suffered only a couple bruised ribs and some road rash. But ever since, I have felt my pulse rise when I hear a car coming up behind my bike.
As self-driving cars roll out, they’re already being billed as making me – and millions of American cyclists, pedestrians and vehicle passengers – safer.
As a driver and a cyclist, I initially welcomed the idea of self-driving cars that could detect nearby people and be programmed not to hit them, making the streets safer for everyone. Autonomous vehicles also seemed to provide attractive ways to use roads more efficiently and reduce the need for parking in our communities. People are certainly talking about how self-driving cars could help build more sustainable, livable, walkable and bikable communities.
But as an urban planner and transportation scholar who, like most people in my field, has paid close attention to the discussion around driverless cars, I have come to understand that autonomous vehicles will not complement modern urban planning goals of building people-centered communities. In fact, I think they’re mutually exclusive: We can have a world of safe, efficient, driverless cars, or we can have a world where people can walk, bike and take transit in high-quality, human-scaled communities.
Changing humans’ behavior
These days, with human-driven cars all over the place, I choose my riding routes and behavior carefully: I much prefer to ride on low-speed traffic, low-traffic roads, buffered bike lanes or off-street bike paths whenever possible, even if it means going substantially out of my way. That’s because I’m scared of what a human driver – through error, ignorance, inattention or even malice – might do to me on tougher roads.
But in a hypothetical future in which all cars are autonomous, maybe I’ll make different choices? So long as I’m confident self-driving cars will at least try to avoid killing me on my bike, I’ll take the most direct route to my destination, on roads that I consider much too dangerous to ride on today. I won’t need to worry about drivers because the technology will protect me.
Driverless cars will level the playing field: I’ll finally be able to ride where I am comfortable in a lane, rather than in the gutter – and pedal at a comfortable speed for myself rather than racing to keep up with, or get out of the way of, other riders or vehicles. I can even see riding with my kids on roads, instead of driving somewhere safe to ride like a park (of course, this is all still assuming driverless cars will eventually figure out how to avoid killing cyclists).
To bikers and people interested in vibrant communities, this sounds great. I’m sure I won’t be the only cyclist who makes these choices. But that actually becomes a problem.
The tragedy of the commons
In the midsize midwestern college town I call home, estimates suggest about 4,000 people commute by bike. That might not sound like many, but consider the traffic backups that would result if even just a few hundred cyclists went out at rush hour and rode at leisurely speeds on the half-dozen arterial roads in my city.
Technology optimists might suggest that driverless cars will be able to pass cyclists more safely and efficiently. They might also be directed to use other roads that are less clogged, though that carries its own risks.
But what happens if it’s a lovely spring afternoon and all those 4,000 bike commuters are riding, in addition to a few thousand kids and teenagers running, riding or skating down my local roads? Some might even try to disrupt the flow of traffic by walking back and forth in the road or even just standing and texting, confident the cars will not hit them. It’s easy to see how good driverless cars will enable people to enjoy those previously terrifying streets, but it also demonstrates that safety for people and efficiency for cars can’t happen at the same time.
People versus cars
It’s not hard to imagine a situation where driverless cars can’t get anywhere efficiently – except late at night or early in the morning. That’s the sort of problem policy scholars enjoy working on, trying to engineer ways for people and technology to get along better.
One proposed solution would put cars and bicycles on different areas of the streets, or transform certain streets into “autonomous only” thoroughfares. But I question the logic of undertaking massive road-building projects when many cities today struggle to afford basic maintenance of their existing streets.
An alternative could be to simply make new rules governing how people should behave around autonomous vehicles. Similar rules exist already: Bikes aren’t allowed on most freeways, and jaywalking is illegal across most of the U.S.
Regulating people instead of cars would be cheaper than designing and building new streets. It would also help work around some of the technical problems of teaching driverless cars to avoid every possible danger – or even just learning to recognize bicycles in the first place.
However, telling people what they can and can’t do in the streets raises a key problem. In vibrant communities, roads are public property, which everyone can use for transportation, of course – but also for commerce, civil discourse and even civil disobedience. Most of the U.S., however, appears to have implicitly decided that streets are primarily for moving cars quickly from one place to another.
There might be an argument for driverless cars in rural areas, or for intercity travel, but in cities, if driverless cars merely replace human-driven vehicles, then communities won’t change much, or they may become even more car-dependent. If people choose to prioritize road safety over all other factors, that will shift how people use roads, sidewalks and other public ways. But then autonomous vehicles will never be particularly efficient or convenient.
Gene H. Bell-Villada
Instead of encouraging driverless cars, why not rebuild public transport instead? Just what is wrong with tramways, trolleys, buses, and trains? Their past efficiency is proven; why not build on it?
Entire American cities, once 1945, have been built around “automobilization,” with mixed results as best. A fleet of autonomous cars will only exacerbate the problems.
I reject the logic of this article; why not forbid bikes instead, or forbid all but walking and wheelbarrows (no dangerous skateboards either of course)? Or permit driverless cars and driverless bikes only? What about heavy trucks?
How are we to assign functions to our streets and roads? Is it to be for recreation (if so whose, bikers primarily?) And it it to be the same in small communities, large cities, industrial areas, residential areas, and open roads? There is a valid case to be made for healthy communities living in skyscrapers only, except for agriculture, heavy industry, long-distance travel and a few such specialities. In such communities the problem would disappear.
As for driverless cars and bikes at rush hour, I used to study in a modest-sized university/agricultural/business town in the days when not everyone had a car, especially not all the students, and no one wore a crash-helmet. The streets in the university area exploded into bikes and pedestrians for ten minutes at the end of each lecture period. (A shocking experience for uninitiated persons, drivers, pedestrians, and bikers alike.) Cars simply drifted along in the crowd. There were a few spills occasionally, but I cannot remember any fatal accidents or serious injuries at all, though I am sure there must have been some during the several decades that those conditions reigned.
Now, if driverless cars could also discuss their itinerary on the fly, then they also could link up into trains, bumper-to-bumper for part of their journeys, making their journeys both safer, more efficient and more productive, and requiring less street space and maintenance.
Community and Regional Planning is not a one-dimensional topic. I think the entire thesis needs a lot more thought out of the box than limiting the concepts to two-horse towns and zero-driver vehicles. (One-horse towns shouldn’t be too much problem, and cities should be able to provide cycle tracks and pedestrian walkways).
People with depression use language differently – here’s how to spot it
February 2, 2018
PhD Candidate in Psychology, University of Reading
Mohammed Al-Mosaiwi receives funding from Medical Research Council.
University of Reading provides funding as a member of The Conversation UK.
From the way you move and sleep, to how you interact with people around you, depression changes just about everything. It is even noticeable in the way you speak and express yourself in writing. Sometimes this “language of depression” can have a powerful effect on others. Just consider the impact of the poetry and song lyrics of Sylvia Plath and Kurt Cobain, who both killed themselves after suffering from depression.
Scientists have long tried to pin down the exact relationship between depression and language, and technology is helping us get closer to a full picture. Our new study, published in Clinical Psychological Science, has now unveiled a class of words that can help accurately predict whether someone is suffering from depression.
Traditionally, linguistic analyses in this field have been carried out by researchers reading and taking notes. Nowadays, computerised text analysis methods allow the processing of extremely large data banks in minutes. This can help spot linguistic features which humans may miss, calculating the percentage prevalence of words and classes of words, lexical diversity, average sentence length, grammatical patterns and many other metrics.
So far, personal essays and diary entries by depressed people have been useful, as has the work of well-known artists such as Cobain and Plath. For the spoken word, snippets of natural language of people with depression have also provided insight. Taken together, the findings from such research reveal clear and consistent differences in language between those with and without symptoms of depression.
Language can be separated into two components: content and style. The content relates to what we express – that is, the meaning or subject matter of statements. It will surprise no one to learn that those with symptoms of depression use an excessive amount of words conveying negative emotions, specifically negative adjectives and adverbs – such as “lonely”, “sad” or “miserable”.
More interesting is the use of pronouns. Those with symptoms of depression use significantly more first person singular pronouns – such as “me”, “myself” and “I” – and significantly fewer second and third person pronouns – such as “they”, “them” or “she”. This pattern of pronoun use suggests people with depression are more focused on themselves, and less connected with others. Researchers have reported that pronouns are actually more reliable in identifying depression than negative emotion words.
We know that rumination (dwelling on personal problems) and social isolation are common features of depression. However, we don’t know whether these findings reflect differences in attention or thinking style. Does depression cause people to focus on themselves, or do people who focus on themselves get symptoms of depression?
The style of language relates to how we express ourselves, rather than the content we express. Our lab recently conducted a big data text analysis of 64 different online mental health forums, examining over 6,400 members. “Absolutist words” – which convey absolute magnitudes or probabilities, such as “always”, “nothing” or “completely” – were found to be better markers for mental health forums than either pronouns or negative emotion words.
From the outset, we predicted that those with depression will have a more black and white view of the world, and that this would manifest in their style of language. Compared to 19 different control forums (for example, Mumsnet and StudentRoom), the prevalence of absolutist words is approximately 50% greater in anxiety and depression forums, and approximately 80% greater for suicidal ideation forums.
Pronouns produced a similar distributional pattern as absolutist words across the forums, but the effect was smaller. By contrast, negative emotion words were paradoxically less prevalent in suicidal ideation forums than in anxiety and depression forums.
Our research also included recovery forums, where members who feel they have recovered from a depressive episode write positive and encouraging posts about their recovery. Here we found that negative emotion words were used at comparable levels to control forums, while positive emotion words were elevated by approximately 70%. Nevertheless, the prevalence of absolutist words remained significantly greater than that of controls, but slightly lower than in anxiety and depression forums.
Crucially, those who have previously had depressive symptoms are more likely to have them again. Therefore, their greater tendency for absolutist thinking, even when there are currently no symptoms of depression, is a sign that it may play a role in causing depressive episodes. The same effect is seen in use of pronouns, but not for negative emotion words.
Understanding the language of depression can help us understand the way those with symptoms of depression think, but it also has practical implications. Researchers are combining automated text analysis with machine learning (computers that can learn from experience without being programmed) to classify a variety of mental health conditions from natural language text samples such as blog posts.
Such classification is already outperforming that made by trained therapists. Importantly, machine learning classification will only improve as more data is provided and more sophisticated algorithms are developed. This goes beyond looking at the broad patterns of absolutism, negativity and pronouns already discussed. Work has begun on using computers to accurately identify increasingly specific subcategories of mental health problems – such as perfectionism, self-esteem problems and social anxiety.
That said, it is of course possible to use a language associated with depression without actually being depressed. Ultimately, it is how you feel over time that determines whether you are suffering. But as the World Health Organisation estimates that more than 300m people worldwide are now living with depression, an increase of more than 18% since 2005, having more tools available to spot the condition is certainly important to improve health and prevent tragic suicides such as those of Plath and Cobain.
The most dangerous celebrity online is revealed
By MARK KENNEDY
AP Entertainment Writer
Tuesday, October 2
NEW YORK (AP) — Ruby Rose has played some dangerous characters, like an inmate in “Orange Is the New Black” and a scientist battling a prehistoric shark in “The Meg.” But the actress herself is now officially dangerous.
Cybersecurity firm McAfee on Tuesday crowned Rose the most dangerous celebrity on the internet. No other celebrity was more likely to land users on websites that carry viruses or malware.
Reality TV star, Kristin Cavallari finished behind Rose at No. 2, followed by actress Marion Cotillard (No. 3), the original “Wonder Woman” Lynda Carter (No. 4), actress Rose Byrne (No. 5), Debra Messing (No. 6), reality TV star Kourtney Kardashian (No. 7), actress Amber Heard (No. 8), morning TV show host Kelly Ripa (No. 9), and actor Brad William Henke as No 10.
Rose is a model and MTV VJ who may have gotten a burst of online interest when she was named to play Batwoman on an upcoming CW series.
The survey is meant to highlight the danger of clicking on suspicious links. McAfee urges internet users to consider risks associated with searching for downloadable content and always apply updated security fixes. The company used its own site ratings to compile the celebrity list and used searches on Google, Bing and Yahoo.
“In our hyper-connected world, it’s important for consumers to think before they click to be sure that they are landing on safe digital content and protecting themselves from cybersecurity threats that may be used to infect their devices or steal their identity,” writes Gary Davis, chief consumer security evangelist at McAfee. “So whether you’re looking up what Ruby did on the latest ‘Orange is the New Black’ episode, or what Kristin Cavallari wore the latest awards show, make sure you’re searching the internet safely.”
Rose deposes last year’s most dangerous celeb, Avril Lavigne. That top 10 also included Bruno Mars, Carly Rae Jepsen, Zayn Malik, Celine Dion, Calvin Harris, Justin Bieber, Sean “Diddy” Combs, Katy Perry and Beyonce.
Musicians on the latest list took a hit. Adele was the highest ranked musician at No. 21 followed by Shakira at No. 27. Diddy, who finished at No. 9 in 2017, fell to No. 76.
Mark Kennedy is at http://twitter.com/KennedyTwits