, 14 min read
Science and Technology links (March 30, 2017)
A famous and highly-funded researcher from Cornel, Brian Wansink, has published many studies regarding how we eat. His work has guided public policy all over the word. According to his Wikipedia entry, Barak Obama named him “Executive Director of the USDA’s Center for Nutrition Policy and Promotion, where he oversaw the development of the 2010 Dietary Guidelines”. He got cited 21,000 times in the scientific literature. It now seems that it was pure junk. Here is what was found…
On a ï¬rst glance at these articles, we immediately noticed a number of apparent inconsistencies in the summary statistics. A thorough reading of the articles and careful reanalysis of the results revealed additional problems. The sample sizes for the number of diners in each condition are incongruous both within and between the four articles. In some cases, the degrees of freedom of between-participant test statistics are larger than the sample size, which is impossible. Many of the computed F and t statistics are inconsistent with the reported means and standard deviations.
This story is interesting. How can you tell that a published paper is junk? Here is a nice trick: suppose I tell you that I have three integers and their average is 4.131. You know that it is simply not possible. I could have 4.000, 4.333, 4.667, but I could never get 4.131. If you see 4.131, you know the person made up the average. It tells us more: not only did the researcher not bother to actual gather integer values, he did not even bother making them up… he just made up the averages. This bears a name: Granularity-Related Inconsistency of Means (GRIM). That a scientific paper should avoid GRIM is putting the bar on science quite low… Yet half of well regarding psychology papers have made up aggregated numbers:
Using GRIM, they examined 260 psychology papers that appeared in well-regarded journals and found that, of the ones that provided enough necessary data to check, half contained at least one mathematical inconsistency. One in five had multiple inconsistencies.
So what about our famous and highly funded researcher, Wansink? Researchers found…
150 or so GRIM inconsistencies in those four Italian-restaurant papers that Wansink co-authored. They found discrepancies between the papers, even though they’re obviously drawn from the same dataset and discrepancies within the individual papers
Yes. Over a hundred made up numbers in only four papers (published in the Journal of Sensory Studies, in the Journal of Product & Brand Management, in Evolutionary Psychological Science and in BMC Nutrition). This is a man that receives millions of dollars in funding. You’d think that with this kind of budget, they could generate credible sounding made-up numbers, right? But wait… let us think about this for a minute. How come it took a silly statistical analysis to reveal the work as being junk? If the numbers are made up… certainly, someone among the authors of the 21,000 papers citing Wansink would have realized that something was odd and reported it. What about the referees recommending the papers for acceptance? What about the journal editors? Wansink is hardly a newcomer. The fact that it took people from outside his field to draw attention to the fraud is quite telling. Wansink himself is dismissive of our concerns, and this has lead Andrew Gelman, a statistician, to comment…
The whole thing just baffles me. On one hand, Wansink seems so naive about statistics and research methods. But on the other hand, who could be so clueless as to not suspect a problem when hundreds of errors have been found in these papers? (…) Paradoxically, this motivates me to examine at certain individual cases, like this one, in detail, to look at how people at different stages of their careers react to the realization that they’ve been doing junk science.
The bar in science is very low but especially low in psychology and related fields. Wansink can receive millions of dollars while not having to, I don’t know, publish the data he collects along his paper. That way, at least, he would have to make up the data behind the averages he reports. But, of course, that would be a lot of work. Oh! And what about all the proud parents who pay the Cornell tuition fees, certain that their kids are educated by the best scientists that money can buy. They would surely expect that professors who make up data on a routine basis would get fired. But, no, Cornell won’t fire Wansink. And, yes, they are getting scammed too. At this point in time, I no longer recognize psychology and behavior studies as a viable scientific discipline… it seems to be no better than astrology. More on this: Over half of psychology studies fail reproducibility test.
Fasting is often considered healthy. Scientists report that fasting for three consecutive days regenerate the entire immune system. If true, this might help, for example, cancer patients who often have damaged immune systems. It seems that fasting could cure Type 1 diabetes, the type that affects young and old people. This makes sense since type 1 diabetes is an autoimmune disease (the body attacks its own pancreas). The result is intriguing because many of us suffer from autoimmune diseases, like allergies. (Speaking for myself, I do not ever dare to fast as I am concerned about losing weight: I am quite small as it is.)
Men who have prostate cancer often receive hormone therapy (androgen deprivation) to reduce their level of testosterone. But we know that men have more muscles than women… and that this is related to testosterone levels. So can you still build large muscles, even if you have artificially low levels of testosterone? It seems that you might, given the right protein supplementation:
Testosterone appears to play a role in maintaining muscle mass but is not necessary to initiate a robust response in muscle protein synthesis following resistance exercise when combined with protein ingestion (…)
It is an intriguing result given that it is widely reported that women only ever “bulk up” when they take hormones. What this paper suggests to me is that women who take enough protein and who train a lot could build up large muscles, without hormonal tricks. A Quantum Computing start-up, Rigetti Computing, received 64 million dollars in funding. I am not entirely sure what quantum computing is good for, but some people must have practical plans.
Doctors printed a titanium vertebra to repair a women’s spine. It seems that the woman will be able to walk again.
Moore’s law is the idea that every two years or so, the number of transistors on processors doubles. There are many questions about whether Moore’s law still holds. Certainly, it seems that Intel, the company, has given up of using Moore’s law as part of its business plan. Part of the issue is that there are limits as to how small a transistor can be (clearly, you can’t make transistors with less an atom.) Klien offers a more optimistic take on our near-time future:
- Though components cannot get infinitely smaller, many memory chips are going 3D. Even if the components cannot get smaller, by piling them up, we can build ever more powerful chips.- Though Intel’s chips are not getting much faster year after year, Nvidia has seen the performance of its chips multiplied year after year.
A Japanese man received reprogrammed stem cells to help restore some of his vision.
Elon Musk, of Tesla fame, has launched a new company Neurolink, who’s goal is to develop technology to connect our brains directly to computers. Currently, we interact without computers through screens and keyboards, but Musk wants to have practical brain-to-computer interaction.
Sickle cell disease is a chronic illness that limits the lifespan of affected people. It is often considered as incurable. It affects 1 out of 500 African American. Apparently, the first ever woman was cured from the disease using radiation therapy and stem cells.
Last year, we got good and affordable virtual reality hardware: the HTC Vive, the Oculus Rift, and the PlayStation VR. Samsung sold 5 million Gear VR headset, its VR headset for smartphones. Sadly, the software is not here yet. Still, I should point out that one of the highest rated PlayStation 4 game is a VR game. Next month, Samsung is releasing a new version of Gear VR with a controller. Early versions of the Oculus Rift and of the Gear VR lacked a controller, but I think the industry learned that VR requires its own controllers, for the experience to make sense.
Retinitis pigmentosa is a terrible disease that leads to blindness. We are literally giving back (some) vision to affected individuals using bionic eyes:
Another retinal implant, the Alpha IMS from the German company Retina Implant AG, became, in 2013, the second wireless retinal implant to receive the CE mark in Europe. The device is a tiny microchip measuring 3 mm2 with 1,500 microphotodiode-amplifier pixels that replace photoreceptor function in the eye.
Of course, 1,500 pixels is not a whole lot, but let us bet that the pixel count will go up quickly at some point in the near future.
Larry Summers, a reputed economist, tell us that technology is more important for jobs than international trade:
Artificial intelligence is behind autonomous vehicles that will affect millions of jobs driving and dealing with cars within the next 15 years, even on conservative projections. Artificial intelligence is transforming everything from retailing to banking to the provision of medical care. Almost every economist who has studied the question believes that technology has had a greater impact on the wage structure and on employment than international trade and certainly a far greater impact than whatever increment to trade is the result of much-debated trade agreements.
Not all fat in our bodies is the same. A particularly interesting type of fat is called “brown fat”. This type of fat burns calories to warm you up. It seems that we can activate this fat, maybe as a way to fight obesity. Scientists have found a safe way to activate brown fat (in mice):
The researchers began with a cohort of nine healthy human volunteers, taking blood samples first at normal room temperatures and then at temperatures cold enough to activate brown fat. Levels of 12,13-diHOME rose significantly among all the volunteers in the cold. “After we identified this lipid in the human cohort, we used it to treat mice,” says Lynes. “We showed that it indeed can activate fuel uptake into brown fat, and improve brown fat performance.”
As a bonus, we could imagine saving on heating costs by turning our own fat as radiators.
The latest trend in AI is deep learning, and deep learning is strongly tied to both Montreal and Toronto. It has Canadian roots, at least in part. The Canadian government is investing massively in deep learning. They are creating a new research institute in Toronto, the Vector Institute. It will be backed by AI star Geoffrey Hinton. Recall that Geoffrey Hinton predicted, in 2015, that within a decade computers would have developed “common sense”.
David Sinclair is a medical researcher famous for promoting the idea that resveratrol, an ingredient found in grapes (and in health stores near you) can slow down aging. An initiative to develop a more potent synthetic resveratrol that he lead and sold to a large pharmaceutical company for millions ended up in a major failure. Trouble is, resveratrol was never shown to prolong the life of normal mice (only obese mice). In recent work, Ramos-Gomez at al. show that “resveratrol supplementation decreases chronological lifespan as a result of mitochondrial dysfunction” (in yeast). I don’t what it means exactly, but it does not sound good. This same David Sinclair has a new anti-aging compound that can “reverse DNA ageing”:
The cells of the old mice were indistinguishable from the young mice, after just one week of treatment, This is the closest we are to a safe and effective anti-ageing drug that’s perhaps only three to five years away from being on the market if the trials go well.
I wish Sinclair would wait for confirmation before going to the media with his speculations.
Your joints, nose, and ear are made of cartilage. We can print cartilage using 3D printers. In theory, if you lose an ear, we could print you a new one. In practice, though we could print it out, but no doctor would put it in. Scientists implanted cartilage in mice, and it worked. It is yet another stop on a long road that should see us, one day, print bones, skin, and muscles, to reconstruct damaged bodies.
I remember being told convincingly, just a few short years ago, that we would soon run out of cheap oil. We are in the middle long-running oversupply of oil that has seen us reach record stockpiles, driving prices down month after month:
Oil prices extended their streak of losses on Thursday, as traders focused on the persistent oversupply of crude in the global market that has weighed on prices in recent years. The record in U.S. stockpiles of crude oil reported Wednesday fed concerns over a global glut of supplies, despite expectations that U.S. demand for gasoline is set to grow in the run-up to the summer driving season.
What happened? Unexpected technological progress.
If you put cameras on sheep, you get a cheap way to photograph the landscape and the street views.
Last year was the first year in decades that saw a decline in food prices in the US. This would be due, in part, to lower transportation costs due to cheap oil prices.
To keep its population level constant, a country needs 2.1 births per woman. China is nowhere close:
The one-child policy, implemented in 1980, had comparatively less impact on fertility, which fluctuated between 2.5 and 2.6 births per woman in the following decade. Then, from 1990 to 2000, despite no major further tightening of family planning laws, fertility fell again, slipping to 1.45 in 2000. Fertility fluctuated between 1.5 and 1.6 for most of the 2000s, well below the replacement level of 2.1 births.
Relaxed family planning laws have prompted some to speculate that China’s fertility rate will continue to rise.
We’re more circumspect. Surveys of Chinese couples’ childbearing intentions suggest economic considerations, not legal restrictions, largely explain China’s low fertility rate today. China would not be unusual in this regard. Rising incomes are associated with falling fertility globally. This is a consequence of a variety of factors. For example, female workforce participation and college education facilitate income growth but also tend to depress fertility by delaying marriage and births. Urbanization and industrialization are also linked with income growth and falling birth rates. For agricultural households, larger families can be advantageous, since children can be put to work on the family’s plot.
By the way, in Japan and Germany, women have, on average, 1.5 children. Their populations are falling fast. In effect, it seems that technology drives down fertility which leads to smaller and older populations. Logically, people who want to see fewer human beings on Earth should promote technological progress and urbanization.
U.S. electricity power producers have reduced carbon dioxide emissions by 24 percent since 2005, according to a new report from Carnegie Mellon University’s Scott Institute for Energy Innovation. How? Better technology.
Professor Judith A. Curry, a highly cited climate researcher, on climate change research:
Scientific progress is driven by the creative tension spurred by disagreement, uncertainty, and ignorance. Progress in understanding the climate system is being hampered by an institutionalized effort to stifle this creative tension, in the name of a ‘consensus’ that humans have caused recent climate change. Motivated by the mandate from the UN Framework Convention on Climate Change (UNFCCC), the climate community has prematurely elevated a scientific hypothesis on human-caused climate change to a ruling theory through claims of a consensus. Premature theories enforced by an explicit consensus building process harm scientific progress
because of the questions that don’t get asked and the investigations that aren’t undertaken. As a result, we lack the kinds of information to more broadly understand climate variability and societal vulnerabilities.
The average scientist in the US is fifty years old. And this number of rising fast. This is caused, in part by the relative glut in the number of young scientists… which increases competition for full-time positions, and means that people compete longer for them. It is also caused in part by the fact that scientists retire older, probably because they are healthier than scientists from earlier generations. People talk a lot about the effect of technology on employment, but I think that the great untold story is the effect of increased longevity on employment.