Summary of “Hair dye: now with graphene to take away the frizz”

In a quest to make a less toxic hair dye, scientists created a dye using graphene.
Most permanent hair dyes use harsh chemicals to open up the outside layer of the hair so that other chemicals can get inside and change its color, Chemical & Engineering News reports.
A team of researchers at Northwestern University decided to use a different strategy: Instead of opening up the hair, why not just coat it with tiny colored particles made out of graphene?
The dye is made of chemically modified graphene particles, a sugar from the pulverized shells of crustaceans, and vitamin C. When sprayed and brushed on hair, the dye sticks in a couple of different ways: graphene clings to uneven surfaces, plus it sticks to the crustacean sugar in the dye, which in turn binds to a protein in hair, according to C&E News.
Charged hair strands can “Stand up on end, creating an uncomfortable ‘flyaway’ effect,” the study says.
Graphene conducts electricity, which means that hair coated in it doesn’t build up a charge.
To show this, researchers rubbed different hair samples with a rubber film, to create an effect similar to rubbing a balloon over your hair.
While natural hair and hair dyed with a conventional dye stood up, graphene-dyed hair stayed sleek and smooth.

The orginal article.

Summary of “Uber, Lyft Drivers Earning A Median Profit Of $3.37 Per Hour, Study Says”

Uber, Lyft Drivers Earning A Median Profit Of $3.37 Per Hour, Study Says : The Two-Way Researchers at MIT said 30 percent of Uber and Lyft drivers are actually losing money after taking car expenses into account, while most drivers earn less than minimum wage.
The vast majority of Uber and Lyft drivers are earning less than minimum wage and almost a third of them are actually losing money by driving, according to researchers at the Massachusetts Institute of Technology.
A working paper by Stephen M. Zoepf, Stella Chen, Paa Adu and Gonzalo Pozo at MIT’s Center for Energy and Environmental Policy Research says the median pretax profit earned from driving is $3.37 per hour after taking expenses into account.
Drivers earning the median amount of revenue are getting $0.59 per mile driven, researchers say, but expenses work out to $0.30 per mile, meaning a driver makes a median profit of $0.29 for each mile.
“If drivers are fully able to capitalize on these losses for tax purposes, 73.5% of an estimated U.S. market $4.8B in annual ride-hailing driver profit is untaxed,” they add.
According to MIT researchers, 80 percent of drivers said they work less than 40 hours per week.
Recode listed the initiatives Uber rolled out in 2017 in order to appeal to drivers, including 24-hour phone support, paid wait time and paying drivers if customers cancel after a certain amount of time.
Both Uber and Lyft have been fighting legal battles for years against initiatives to classify their drivers as “Employees” instead of “Independent contractors” – meaning drivers don’t receive benefits like health care or sick leave.

The orginal article.

Summary of “Where Millennials end and post-Millennials begin”

As we enter 2018, it’s become clear to us that it’s time to determine a cutoff point between Millennials and the next generation.
In order to keep the Millennial generation analytically meaningful, and to begin looking at what might be unique about the next cohort, Pew Research Center will use 1996 as the last birth year for Millennials for our future work.
At 16 years, our working definition of Millennials will be equivalent in age span to their preceding generation, Generation X. By this definition, both are shorter than the span of the Baby Boomers – the only generation officially designated by the U.S. Census Bureau, based on the famous surge in post-WWII births in 1946 and a significant decline in birthrates after 1964.
For analytical purposes, we believe 1996 is a meaningful cutoff between Millennials and post-Millennials for a number of reasons, including key political, economic and social factors that define the Millennial generation’s formative years.
Generation X grew up as the computer revolution was taking hold, and Millennials came of age during the internet explosion.
Pew Research Center is not the first to draw an analytical line between Millennials and the generation to follow them, and many have offered well-reasoned arguments for drawing that line a few years earlier or later than where we have.
As has been the case in the past, this means that the differences within generations can be just as great as the differences across generations, and the youngest and oldest within a commonly defined cohort may feel more in common with bordering generations than the one to which they are assigned.
In the coming weeks, we will be updating demographic analyses that compare Millennials to previous generations at the same stage in their life cycle to see if the demographic, economic and household dynamics of Millennials continue to stand apart from their predecessors.

The orginal article.

Summary of “Does money buy happiness? Yes, up to a point.”

The technical term for this cutoff is the income “Satiation point.”
The researchers analyzed the relationship between this score and household income.
The incomes are converted to US dollars and adjusted for variations in spending power across countries.
These psychologists, from Purdue University and the University of Virginia, are not the first to study how income relates to life satisfaction.
Dan Sacks is an economist at Indiana University who studies the relationship between income and subjective well-being.
The surveys rely on self-reported income, and previous research shows that just because people say they make a certain amount of money, it doesn’t mean they actually do.
“It could be true that on average, people who say they have income of $150,000 are no happier than people who say they have income of $100,000,” writes Sacks.
“But I’m not convinced that people who actually have income of $150,000 are no happier than people who have income of $100,000.” Also, it’s possible that rich people have a tendency to underemphasize their happiness compared with poorer people.

The orginal article.

Summary of “How Our Beliefs Can Shape Our Waistlines”

A recent epidemiological study suggests that our beliefs about how much we exercise may substantially influence our health and longevity, even if those beliefs are objectively inaccurate – which hints that upending our thinking about exercise might help us whittle away pounds, whether we work out more or not.
Crum and her co-author studied 84 female hotel-room attendants, who told the researchers that they felt they completed little or no daily exercise, although their work consisted mostly of physical labor.
Crum and her colleague explained to half of them that they were meeting or exceeding national recommendations for 30 minutes of daily exercise; a month later, when the researchers checked back, the women said they believed they were getting more exercise than before.
For the new study, Crum and a different co-author, Octavia Zahrt, turned to two federal databases, the National Health Interview Survey and the National Health and Nutrition Examination Survey, which contain health data about representative samples of Americans.
The scientists homed in on information from 61,141 participants who answered questions about whether they felt they were getting more, less or about the same amount of exercise as most people their age.
Risk of early death was up to 71 percent higher than for the group that, correctly or not, felt confident that they exercised more than their peers.
This type of study cannot prove that exercise beliefs directly cause life spans to shorten or grow; it can show only that the two issues are related.
Self-comparisons might also dampen exercise motivation, leading to declining health.

The orginal article.

Summary of “The GANfather: The man who’s given machines the gift of imagination”

The goal of GANs is to give machines something akin to an imagination.
When future historians of technology look back, they’re likely to see GANs as a big step toward creating machines with a human-like consciousness.
Yann LeCun, Facebook’s chief AI scientist, has called GANs “The coolest idea in deep learning in the last 20 years.” Another AI luminary, Andrew Ng, the former chief scientist of China’s Baidu, says GANs represent “a significant and fundamental advance” that’s inspired a growing global community of researchers.
In one widely publicized example last year, researchers at Nvidia, a chip company heavily invested in AI, trained a GAN to generate pictures of imaginary celebrities by studying real ones.
Once it’s been trained on a lot of dog photos, a GAN can generate a convincing fake image of a dog that has, say, a different pattern of spots; but it can’t conceive of an entirely new animal.
Researchers at Yale University and Lawrence Berkeley National Laboratory have developed a GAN that, after training on existing simulation data, learns to generate pretty accurate predictions of how a particular particle will behave, and does it much faster.
Hany Farid, who studies digital forensics at Dartmouth College, is working on better ways to spot fake videos, such as detecting slight changes in the color of faces caused by inhaling and exhaling that GANs find hard to mimic precisely.
Researchers are already highlighting the risk of “Black box” attacks, in which GANs are used to figure out the machine-learning models with which plenty of security programs spot malware.

The orginal article.

Summary of “Why Self-Taught Artificial Intelligence Has Trouble With the Real World”

In 2016, Google DeepMind’s AlphaGo thrashed champion Lee Sedol at the ancient board game Go after poring over millions of positions from tens of thousands of human games.
The past year also saw otherworldly self-taught bots emerge in settings as diverse as no-limit poker and Dota 2, a hugely popular multiplayer online video game in which fantasy-themed heroes battle for control of an alien world.
One characteristic shared by many games, chess and Go included, is that players can see all the pieces on both sides at all times.
An even more daunting game involving imperfect information is StarCraft II, another multiplayer online video game with a vast following.
Before the release of AlphaGo and its progeny, the DeepMind team achieved its first big, headline-grabbing result in 2013, when they used reinforcement learning to make a bot that learned to play seven Atari 2600 games, three of them at an expert level.
Within the larger category of reinforcement learning, board games and multiplayer games allow for an even more specific approach.
In game after game, an algorithm in a self-play system faces an equally matched foe.
Since 2008, hundreds of thousands of human players have attempted Foldit, an online game where users are scored on the stability and feasibility of the protein structures they fold.

The orginal article.

Summary of “Better climate science has opened the door to lawsuits against Big Oil”

These lawsuits are also a sign that the science connecting climate change to damaging events has greatly improved.
Though scientists still warn that it’s inaccurate to speak of weather events being “Caused” by climate change – weather always has multiple causes – better climate models, more powerful computers, and refined methodologies now allow researchers to quantify how climate change has increased the likelihood or severity of heat waves, droughts, deluges, and other extreme events.
Combined with attribution science, the two fields form a sort of climate forensics, enabling communities to point to an ostensibly natural disaster, find the fingerprints of climate change, and trace them back to an Exxon or BP. If the current volley of lawsuits over adaptation costs are successful, they will likely be followed by others: Phoenix might sue over deadly heat, Boulder over its shrinking ski season, or Houston over torrential rain.
“Advances in the science of extreme weather event attribution have the potential to change the legal landscape in novel ways.” The better attribution science gets, the easier it will be to argue that governments should have foreseen climate risks and prepared for them – and to hold them liable if they fail to.
The new lawsuits from Santa Cruz, New York, and elsewhere may fare better, according to Michael Burger, the executive director of Columbia University’s Sabin Center for Climate Change Law.
If the new round of lawsuits go to trial, there will be a bitter fight over these two links in the causal chain: that these companies contributed to climate change, and that climate change is causing these particular harms.
In a petition filed last month in a Texas district court, the company accused the California communities of “Abusive law enforcement tactics” designed to stifle the company’s “First Amendment right to participate in the national dialogue about climate change and climate policy.” Seeking depositions and documents, Exxon also accused the communities of failing to tell bondholders about the climate risks cited in their lawsuits.
It’s standard practice for fossil fuel companies to push back fiercely against attempts to hold them accountable for climate change, but it’s easy to see why the current round of lawsuits would be worrisome.

The orginal article.

Summary of “Why A.I. Researchers at Google Got Desks Next to the Boss”

A growing number of tech companies are pushing research labs and other far-reaching engineering efforts closer to the boss.
A year ago, the Google Brain team of mathematicians, coders and hardware engineers sat in a small office building on the other side of the company’s campus.
“Any C.E.O. thinks a lot about where people are sitting – who they can walk around and have casual conversations with,” said Diane Greene, who oversees Google’s cloud computing team and sits on the board of Alphabet, Google’s parent company.
Google is placing big bets on the A.I. being explored by researchers like Mr. Goodfellow.
These big companies are trying to duplicate the vibe of a Silicon Valley start-up, where the boss is next to everyone.
Ms. Greene, who was the chief executive of the software company VMware, said she had always made a point of sitting beside the top engineers because they saw the company’s future.
After Facebook went public and started a big push for revenue, important members of the ad team moved next to the boss, said Antonio García Martínez, who wrote a book about his experiences inside Facebook.
The boss is also showing them how important they are to the company.

The orginal article.

Summary of “China’s great leap forward in science”

These days, Chinese scientists stand at least as good a chance of making a global impact on science from within China itself.
In January, the United States National Science Foundation reported that the number of scientific publications from China in 2016 outnumbered those from the US for the first time: 426,000 versus 409,000.
“The startup packages for researchers in good universities in China can be significantly higher than Hong Kong universities can offer,” says Che Ting Chan, a physicist at the Hong Kong University of Science & Technology in what was previously China’s affluent and westernised neighbour.
According to quantum physicist Jian-Wei Pan of the University of Science and Technology in Hefei, as a relative latecomer to the global scientific stage, China needs such incentives as a way of maintaining enthusiasm.
The pattern seems clear, and is worth heeding by other nations: despite China’s reputation for authoritarian and hierarchical rule, in science the approach seems to be to ensure that top researchers are well supported with funding and resources, and then to leave them to get on with it.
It’s with good reason Poo asserts that China has become a world leader in stem-cell science and regenerative medicine.
China is taking great strides in other areas of biological science too.
In 2016 China initiated an international project called Quantum Experiments at Space Scale and launched a satellite designed for quantum data handling, called Micius after the romanised name of the ancient Chinese philosopher Mozi.

The orginal article.