The root cause of fear, and how to treat it, has been one of modern psychology’s central questions. In the early twentieth century, Sigmund Freud argued phobias were “protective structures” springing from a patient’s “repressed longing” for his mother. In 1920, however, the American psychologist John B. Watson put forward a simpler theory: People develop fears through negative experiences. To test his hypothesis, he sought to condition an infant, whom he called “Little Albert,” to fear a white rat by presenting the rat to the child and simultaneously striking a steel bar. ... Different types of memories consolidate in different parts of the brain. Explicit memories of life events, for instance, consolidate in the hippocampus, the long, podlike structures near the center of the brain. Emotional memories, including fear, consolidate nearby in the amygdala, which activates the fight-or-flight response when it senses danger. The subjective experience of fear often involves both of these memory systems—a person will consciously remember past experiences while also undergoing several automatic physiological responses, such as increased heart rate—but they operate independently of each other.
Samumed is finding it easy to raise huge amounts of cash because it believes it has invented medicines that can reverse aging. Its first drugs are targeted at specific organ systems. One aims to regrow hair in bald men. The same drug may also turn gray hair back to its original color, and a cosmetic version could erase wrinkles. A second drug seeks to regenerate cartilage in arthritic knees. Additional medicines in early human studies aim to repair degenerated discs in the spine, remove scarring in the lungs and treat cancer. After that Samumed will attempt to cure a leading cause of blindness and go after Alzheimer’s. The firm’s focus, disease by disease, symptom by symptom, is to make the cells of aging people regenerate as powerfully as those of a developing fetus. ... Hood, 49, had invented a cancer drug that got his previous company, Targegen, bought by Sanofi for $635 million. He has a distinct take on drug development: He thinks everybody takes too many shortcuts and insists on doing work himself that other companies outsource, including formulating drug chemistry, testing drugs in laboratory animals and running clinical trials. ... The target Hood and Kibar went after was obvious: a gene called Wnt, which stands for “wingless integration site,” because when you knock it out in fruit flies, they never grow wings. It’s a linchpin in a group of genes that control the growth of a developing fetus–whether you’re a fly or a person. Together these genes are known as the Wnt pathway. Trigger the right ones and you might revive old flesh. Some cancers do their dirty work by hijacking Wnt, and blocking it might stop tumors.
Finance may be the most powerful weapon of war. It moves armadas, armies, and squadrons. It funds troops and artillery. It endows suicide bombs and improvised explosive devices. It pays for special forces and mercenaries. It underwrites cease-fires and purchases surrenders. Finance is the weapon that makes all other weapons of war possible. ... This Article is about the financial weapons of war, their growing importance in national affairs, and their wide-ranging effects on law, finance, and society. This Article offers an early, broad examination of the realities of modern financial warfare. This Article descriptively and normatively explores the new financial theater of war, analyzes the modern arsenal of financial weapons, highlights emerging legal and policy concerns, and proposes key recommendations for current and future financial warfare. ... While policymakers, analysts, and scholars have long been studying the respective, evolving fields of modern finance and modern warfare, there has been surprisingly little meaningful legal scholarship on the crosscutting realities of modern financial warfare. Drawing on a rich legal literature that spans the laws of war, finance, and cyberspace, this Article seeks to fill this understudied, underappreciated—yet critically important—legal intersection of war and finance. ... Part I provides a general layout of the modern financial theater of war. It describes the modern financial infrastructure as a globalized, high-tech, American-centric system. ... Part II highlights particular armaments of financial warfare. Rather than provide an exhaustive catalog of financial weapons, it offers a broad inventory of the financial weapons of war. It classifies the financial weapons of war as analog weapons and cyber weapons. ... Part III contends with new concerns. It asserts that the financial weapons of war present critical challenges for traditional laws and norms relating to financial hostilities, cyberattacks, and non-state actors. ... Part IV offers new pathways. It proposes three pragmatic policy recommendations that should be undertaken in the near term response to modern financial warfare while larger issues remain unresolved by global policymakers.
Scholze’s key innovation — a class of fractal structures he calls perfectoid spaces — is only a few years old, but it already has far-reaching ramifications in the field of arithmetic geometry, where number theory and geometry come together. ... his unnerving ability to see deep into the nature of mathematical phenomena. Unlike many mathematicians, he often starts not with a particular problem he wants to solve, but with some elusive concept that he wants to understand for its own sake. ... “I understood nothing, but it was really fascinating,” ... Scholze worked backward, figuring out what he needed to learn to make sense of the proof. ... Despite the complexity of perfectoid spaces, Scholze is known for the clarity of his talks and papers. ... Scholze makes a point of trying to explain his ideas at a level that even beginning graduate students can follow
Avian vision works spectacularly well (enabling eagles, for instance, to spot mice from a mile high), and his lab studies the evolutionary adaptations that make this so. Many of these attributes are believed to have been passed down to birds from a lizardlike creature that, 300 million years ago, gave rise to both dinosaurs and proto-mammals. While birds’ ancestors, the dinos, ruled the planetary roost, our mammalian kin scurried around in the dark, fearfully nocturnal and gradually losing color discrimination. Mammals’ cone types dropped to two — a nadir from which we are still clambering back. About 30 million years ago, one of our primate ancestors’ cones split into two — red- and green-detecting — which, together with the existing blue-detecting cone, give us trichromatic vision. But our cones, particularly the newer red and green ones, have a clumpy, scattershot distribution and sample light unevenly. ... Bird eyes have had eons longer to optimize. Along with their higher cone count, they achieve a far more regular spacing of the cells. But why, Corbo and colleagues wondered, had evolution not opted for the perfect regularity of a grid or “lattice” distribution of cones? The strange, uncategorizable pattern they observed in the retinas was, in all likelihood, optimizing some unknown set of constraints. What these were, what the pattern was, and how the avian visual system achieved it remained unclear. ... Determining whether a system is hyperuniform requires algorithms that work rather like a game of ring toss. ... Hyperuniformity is clearly a state to which diverse systems converge, but the explanation for its universality is a work in progress.
Risk scores, generated by algorithms, are an increasingly common factor in sentencing. Computers crunch data—arrests, type of crime committed, and demographic information—and a risk rating is generated. The idea is to create a guide that’s less likely to be subject to unconscious biases, the mood of a judge, or other human shortcomings. Similar tools are used to decide which blocks police officers should patrol, where to put inmates in prison, and who to let out on parole. Supporters of these tools claim they’ll help solve historical inequities, but their critics say they have the potential to aggravate them, by hiding old prejudices under the veneer of computerized precision. ... Computer scientists have a maxim, “Garbage in, garbage out.” In this case, the garbage would be decades of racial and socioeconomic disparities in the criminal justice system. Predictions about future crimes based on data about historical crime statistics have the potential to equate past patterns of policing with the predisposition of people in certain groups—mostly poor and nonwhite—to commit crimes.
In 1978, the United States Geological Survey (USGS) allocated over half its research budget ($15.76 million) to earthquake prediction, a level of spending that continued for much of the next decade. Scientists deployed hundreds of seismometers and other sensors, hoping to observe telltale signals heralding the arrival of the next big one. They looked for these signs in subterranean fluids, crustal deformations, radon gas emissions, electric currents, even animal behavior. But every avenue they explored led to a dead end. ... Since the early 20th century, scientists have known that large quakes often cluster in time and space: 99 percent of them occur along well-mapped boundaries between plates in Earth’s crust and, in geological time, repeat almost like clockwork. But after decades of failed experiments, most seismologists came to believe that forecasting earthquakes in human time—on the scale of dropping the kids off at school or planning a vacation—was about as scientific as astrology. By the early 1990s, prediction research had disappeared as a line item in the USGS’s budget. ... Defying the skeptics, however, a small cadre of researchers have held onto the faith that, with the right detectors and computational tools, it will be possible to predict earthquakes with the same precision and confidence we do just about any other extreme natural event, including floods, hurricanes, and tornadoes. The USGS may have simply given up too soon. After all, the believers point out, advances in sensor design and data analysis could allow for the detection of subtle precursors that seismologists working a few decades ago might have missed. ... At a time when American companies and institutions are bankrolling “moonshot” projects like self-driving cars, space tourism, and genomics, few problems may be as important—and as neglected—as earthquake prediction.
Around the world, nearly 80 research groups in 25 countries are honing their technologies for the €5-million (US$5.5-million) event. They range from small, ad hoc teams to the world's largest manufacturers of advanced prostheses, and comprise about 300 scientists, engineers, support staff and competitors: disabled people who will each compete in one of six events that will challenge their ability to tackle the chores of daily life. A race for prosthetic-arm users will be won by the first cyborg to complete tasks including preparing a meal and hanging clothes on a line. A powered-wheelchair race will test how well participants can navigate everyday obstacles such as bumps and stairs. ... The venue — Zurich's 7,600-spectator ice-hockey stadium — should combine with the presence of television cameras and team jerseys to give the Cybathlon a sporting vibe similar to that of the Paralympics, in which disabled athletes compete using wheelchairs, running blades and other assistive technologies. The difference is that the Paralympics celebrates exclusively human performance: athletes must use commercially available devices that run on muscle power alone. But the Cybathlon honours technology and innovation. Its champions will use powered prostheses, often straight out of the lab, and are called pilots rather than athletes. The hope is that devices trialled in the games will accelerate technology development and eventually be used by people around the world.
Consider the most familiar random shape, the random walk, which shows up everywhere from the movement of financial asset prices to the path of particles in quantum physics. These walks are described as random because no knowledge of the path up to a given point can allow you to predict where it will go next. ... Beyond the one-dimensional random walk, there are many other kinds of random shapes. There are varieties of random paths, random two-dimensional surfaces, random growth models that approximate, for example, the way a lichen spreads on a rock. All of these shapes emerge naturally in the physical world, yet until recently they’ve existed beyond the boundaries of rigorous mathematical thought. Given a large collection of random paths or random two-dimensional shapes, mathematicians would have been at a loss to say much about what these random objects shared in common. ... have shown that these random shapes can be categorized into various classes, that these classes have distinct properties of their own, and that some kinds of random objects have surprisingly clear connections with other kinds of random objects. Their work forms the beginning of a unified theory of geometric randomness. ... “You take the most natural objects — trees, paths, surfaces — and you show they’re all related to each other,” Sheffield said. “And once you have these relationships, you can prove all sorts of new theorems you couldn’t prove before.” ... incoherent is not the same as incomprehensible. ... In practical terms, the results by Sheffield and Miller can be used to describe the random growth of real phenomena like snowflakes, mineral deposits, and dendrites in caves, but only when that growth takes place in the imagined world of random surfaces.
It starts with a single gene, out of some 20 to 25,000, coding for the more than 30 trillion cells in a human body. Take the length of the DNA in those cells, unravel it, and you have a distance of more than 400 lengths from the sun to the Earth. The human genome has 6 billion data points of information. Six billion ways for something to go incredibly right — or incredibly wrong. ... Sorting through these possibilities is the job of Stanford University scientist Euan Ashley. The 45-year-old Scotsman is a cardiologist, a systems biologist, and one of the leaders of a new, integrated approach to the science of genetics. He led the first team to clinically interpret a full human genome; he’s involved in attempts to sequence cancer genomes for personalized treatment and to analyze the genomes of individuals who have rare and unknown diseases. But for the last several years, his work has focused on a specific mystery. He is looking for superhero genes ... “We’re interested in truly the fittest people on the planet,” he explained. Though there are many factors that may make someone elite, his team made the decision to select athletes on the basis of a single, objective physiological variable: the maximum amount of oxygen a body can use, or VO2max. VO2max is considered one of the most important markers not only for athletic success, but for overall health: It’s such a crucial indicator of cardiovascular function that it is used to determine whether someone requires a heart transplant. VO2max has also been measured in the same way for half a century, which means it can be a useful comparative point. ... To be a part of the study, men need to test at a VO2max that exceeds 75 milliliters of oxygen per minute; for women, the cutoff is 63. Fewer than .00172 percent of the population qualify.
Financial crises pose challenges for macroeconomists. Schularick and Taylor (2012) show that credit booms precede crises. Mendoza and Terrones (2008) claim that not all credit booms end in crises. Herrera et al. (2014) argue that crises are not necessarily the result of large negative shocks, but also of political considerations. There is a need for models displaying financial crises that are preceded by credit booms and that are not necessarily the result of large negative shocks. ... In a recent paper (Gorton and Ordonez 2016), we show that credit booms are indeed not rare, that some end in crises (bad booms) but others do not (good booms). Are these two types of booms intrinsically different in their evolution, or do they just differ in how they end? We show that all credit booms start with a positive shock to productivity on average ten years before the end of the boom, but that in bad booms this increase dies off rather quickly while this is not the case for good booms. This suggests that a crisis is the result of an exhausted credit boom. We then develop a simple framework that rationalises these empirical findings and highlight several shortcomings of standard macroeconomic models that tend to neglect the interplay between macroeconomic and financial variables.
The DNDi is an unlikely success story in the expensive, challenging field of drug development. In just over a decade, the group has earned approval for six treatments, tackling sleeping sickness, malaria, Chagas' disease and a form of leishmaniasis called kala-azar. And it has put another 26 drugs into development. It has done this with US$290 million — about one-quarter of what a typical pharmaceutical company would spend to develop just one drug. The model for its success is the product development partnership (PDP), a style of non-profit organization that became popular in the early 2000s. PDPs keep costs down through collaboration — with universities, governments and the pharmaceutical industry. And because the diseases they target typically affect the world's poorest people, and so are neglected by for-profit companies, the DNDi and groups like it face little competitive pressure. They also have lower hurdles to prove that their drugs vastly improve lives. ... Now, policymakers are beginning to wonder whether their methods might work more broadly. ... If successful, the work could challenge standard assumptions about drug development, and potentially rein in the runaway price of medications.
Under a microscope, a varroa mite is a monster: armored and hairy, with eight legs and one piercing, sucking mouthpart, primordial in its horror. Since the parasite arrived in the United States from Asia in 1987, the practice of tending bees has grown immeasurably harder. Beekeepers must use harsh chemicals in their hives to kill the mites or risk losing most of their bees within two to three years. About a third of the nation’s honeybees have died each winter over the past decade, and Hayes, an apiary scientist, believes the varroa mite is a major factor in this catastrophe. ... the Internet was abuzz with theories about CCD. It offered a litany of dystopian ecological conspiracies: cell phones interfering with bee navigation, or genetically modified corn syrup, or neonicotinoid pesticides. But no one really knew. ... Traditional pesticides act like chemical backhoes, killing their targets (beetles, weeds, viruses) but harming good things along the way (beneficial insects, birds, fish, humans). RNAi, in theory, works instead like a set of tweezers, plucking its victims with exquisite specificity by clicking into sequences of genetic code unique to that organism.
Scientists are beginning to understand why these ‘mini Wall Streets’ work so well at forecasting election results — and how they sometimes fail. ... Experiments such as this are a testament to the power of prediction markets to turn individuals’ guesses into forecasts of sometimes startling accuracy. That uncanny ability ensures that during every US presidential election, voters avidly follow the standings for their favoured candidates on exchanges such as Betfair and the Iowa Electronic Markets (IEM). But prediction markets are increasingly being used to make forecasts of all kinds, on everything from the outcomes of sporting events to the results of business decisions. Advocates maintain that they allow people to aggregate information without the biases that plague traditional forecasting methods, such as polls or expert analysis. ... sceptics point out that prediction markets are far from infallible. ... prediction-market supporters argue that even imperfect forecasts can be helpful. ... People have been betting on future events for as long as they have played sports and raced horses. But in the latter half of the nineteenth century, US efforts to set betting odds through marketplace supply and demand became centralized on Wall Street, where wealthy New York City businessmen and entertainers were using informal markets to bet on US elections as far back as 1868. ... Friedrich Hayek. He argued that markets in general could be viewed as mechanisms for collecting vast amounts of information held by individuals and synthesizing it into a useful data point — namely the price that people are willing to pay for goods or services.
Americans are bad at saving. In an annual survey by the Fed, almost half said they couldn’t come up with $400 in an emergency. The savings rate of the bottom 90 percent of American households hovers just above 1 percent. ... There are many theories for why Americans don’t save, from poverty to debt to conspicuous consumption. But the most enticing comes from behavioral economics: It’s easier not to. Inertia is strong, and putting money away requires overcoming what economists call present bias. ... The good news, according to behavioral economists, is that we can just as easily be tricked into overcoming that psychology with “nudges” that reframe incentives. Just post calorie counts next to unhealthy food, and people won’t order cheeseburgers. Or, make 401(k) plans opt-out, and more people will save money for retirement. Suddenly, with one oh-so-simple tweak, making bad decisions becomes the harder option. ... At every step of the way, the study ran into a web of competing incentives and pesky human flaws that hurt its goal of getting poor people to save money. ... The problem goes beyond a sheer lack of funds. The psychology of poverty is hard to overcome with a dainty nudge. ... the study’s preliminary results were muddy. They suggested that the nudge method did get some people to save more: Deposits increased when people got some kind of reminder. But they didn’t show whether one type of nudge worked better than any other (possibly because of teller error), and they provided no evidence that the savings accounts helped people build up money over time.
The rise of immunotherapy hasn’t shifted that reality overnight, but it has sent a new jolt of energy into an age-old dream: that maybe, just maybe, medical science can turn terminal cancers into survivable conditions. ... In the past two years alone, the FDA has approved three second-generation checkpoint inhibitors, and two other arms of immunotherapy—cancer vaccines and a therapeutic approach known as adoptive T cell transfer, in which a patient’s own T cells are engineered outside the body and reinjected into the bloodstream—are showing ever-more-promising results. ... If immunotherapy leads the way to cancer cures in the coming decade, it’ll be tempting to look back on its development as inevitable, a breakthrough that was merely waiting for technology and biological research to make it possible. This would be true to some extent—scientists have hypothesized for over a century about the potential for the immune system to beat back tumors—but such a view would overlook the human choices and biases that shape the course of science. It would also overlook the power of small groups of individuals to spark major advances by bucking conventional wisdom and seeking out new frontiers. In other words, it would ignore the life of Jim Allison—a shaggy-haired, patchily bearded son of small-town South Texas whose creativity, diligence, and zest for pursuing a seemingly quixotic path far from the front lines of cancer research have added up to a revolution.
- Also: The New York Times - The Improvisational Oncologist 5-15min
- Also: The New York Times - Learning From The Lazarus Effect 5-15min
- Also: The New York Times - An Old Idea, Revived: Starve Cancer to Death 5-15min
- Also: The New York Times - The Sisters Who Treat The Untreatable 5-15min
- Also: Fortune - Can Sean Parker Hack Cancer? 5-15min
JPL, home to three thousand engineers and five hundred scientists, is very old—2016 is its eightieth anniversary—but it's only in the last few years that the close of the space shuttle program has left enough of an excitement gap for the center's singular brilliance to shine through. In contrast to NASA's other outposts, where you'll find a lot of unflappable pilot types with high-and tight haircuts, JPL is full of strange, excitable, idea people. Climate scientists who work side gigs as comedians and engineers who shave star shapes into their Mohawks before landings. ... Just off California Interstate 210, there are two signs on the side of the road. The bottom one shows an outline of the California mule deer that tend to meander out of the sagebrush and into passing traffic. The top one just says "Space," with an arrow pointing forward. The second sign is not an official JPL sign. No one really knows where it came from. People around here presume it was put there as a joke and no one ever bothered to take it down. ... Even though JPL is currently beholden to its parent organization's budgets and approvals, it is actually the reason NASA exists. ... The best way to understand what JPL does is to consider the center's "directorates," which is space-agency-speak for departments. Among these are four organized by planet. Taken together, they sound like a particularly difficult round of Jeopardy: Earth Science, Astrophysics, Mars, and Planets That Are Not Mars.
I’m sure some of the criticism of people who claim to be using data to find knowledge, and to exploit inefficiencies in their industries, has some truth to it. But whatever it is in the human psyche that the Oakland A’s exploited for profit—this hunger for an expert who knows things with certainty, even when certainty is not possible—has a talent for hanging around. ... How did this pair of Israeli psychologists come to have so much to say about these matters of the human mind that they more or less anticipated a book about American baseball written decades in the future? What possessed two guys in the Middle East to sit down and figure out what the mind was doing when it tried to judge a baseball player, or an investment, or a presidential candidate? And how on earth does a psychologist win a Nobel Prize in economics? ... Amos was now what people referred to, a bit confusingly, as a “mathematical psychologist.” Non-mathematical psychologists, like Danny, quietly viewed much of mathematical psychology as a series of pointless exercises conducted by people who were using their ability to do math as camouflage for how little of psychological interest they had to say. ... students who once wondered why the two brightest stars of Hebrew University kept their distance from each other now wondered how two so radically different personalities could find common ground, much less become soulmates. ... Danny was always sure he was wrong. Amos was always sure he was right. Amos was the life of every party; Danny didn’t go to the parties. ... Both were grandsons of Eastern European rabbis, for a start. Both were explicitly interested in how people functioned when they were in a “normal” unemotional state. Both wanted to do science. Both wanted to search for simple, powerful truths.
Intrigued by the promise of an easier way to make money, he enrolled as a guinea pig in a four-week study testing the effects of alcohol on a painkiller drug. ... For studies looking for healthy subjects, the screening process generally comes in two steps. The first is over the phone, when guinea pigs call to express their interest. ... The second step is in person, where clinic staff will check blood, urine, and vital signs to determine whether subjects’ claims are true. Some studies, the well-paying ones, are competitive, and clinics will often admit more people than they need from the phone screen, expecting to cull the herd after the round of physicals. Pros know to avoid alcohol and drugs in the days leading up to the screening. Some of the more cautious ones will also abstain from exercise, out of worry that an increased creatinine level will make it appear as though they’ve been drinking. ... In chronological order, the phases of drug testing work like this: Phase 1 studies, which test for safety, typically use between 20 and 80 healthy subjects to determine a drug’s side effects and how it’s metabolized in the body. Assuming the drug proves safe, it then advances into Phase 2, which measures its effectiveness against another treatment or a placebo; this time, the study participants are patients with whatever condition the drug was developed to treat, usually somewhere between a few dozen and a few hundred. Phase 3, the last phase before the drug is submitted to the FDA for approval, can include hundreds or thousands of patients and measures both safety and efficacy, as well as how the drug behaves in different types of patients or in conjunction with another therapy.
Like many astrophysicists, Sara Seager sometimes has a problem with her perception of scale. Knowing that there are hundreds of billions of galaxies, and that each might contain hundreds of billions of stars, can make the lives of astrophysicists and even those closest to them seem insignificant. Their work can also, paradoxically, bolster their sense of themselves. Believing that you alone might answer the question “Are we alone?” requires considerable ego. Astrophysicists are forever toggling between feelings of bigness and smallness, of hubris and humility, depending on whether they’re looking out or within. ... Her area of expertise is the relatively new field of exoplanets: planets that orbit stars other than our sun. More particular, she wants to find an Earthlike exoplanet — a rocky planet of reasonable mass that orbits its star within a temperate “Goldilocks zone” that is not too hot or too cold, which would allow water to remain liquid — and determine that there is life on it. That is as simple as her math gets. ... The vastness of space almost defies conventional measures of distance. Driving the speed limit to Alpha Centauri, the nearest star grouping to the sun, would take 50 million years or so; our fastest current spacecraft would make the trip in a relatively brisk 73,000 years. The next-nearest star is six light-years away. To rocket across our galaxy would take about 23,000 times as long as a trip to Alpha Centauri, or 1.7 billion years, and the Milky Way is just one of hundreds of billions of galaxies. ... Light or its absence is also the root of something called the transit technique, a newer, more efficient way than radial velocity of finding exoplanets by looking at their stars.
When I returned to addiction, it was as a scientist studying the addicted brain. The data were indisputable: brains change with addiction. I wanted to understand how – and why. I wanted to understand addiction with fastidious objectivity, but I didn’t want to lose touch with its subjectivity – how it feels, how hard it is – in the process. ... One explanation is that addiction is a brain disease. The United States National Institute on Drug Abuse, the American Society of Addiction Medicine, and the American Medical Association ubiquitously define addiction as a ‘chronic disease of brain reward, motivation, memory and related circuitry’ ... If only the disease model worked. Yet, more and more, we find that it doesn’t. First of all, brain change alone isn’t evidence for brain disease. Brains are designed to change. ... we now know that drugs don’t cause addiction. ... One idea is that addicts voluntarily choose to remain addicted: if they don’t quit, it’s because they don’t want to. ... The view that addiction arises through learning, in the context of environmental forces, appears to be gathering momentum.
Bringing people back from death’s door is Catena’s moonlight gig – she is on shift from 6pm to 2am six to eight times a month. By day, she is the managing director of Catena Zapata, the flagship brand of a family-owned company that sells bottles worth over $140m a year, making it Argentina’s second-biggest wine exporter. The firm was founded in 1902 by her great-grandfather Nicola Catena, and she assumed the reins from her father Nicolás in 2009. She spends four months a year in Argentina overseeing the winery’s operations, and two more as the olive-skinned, pony-tailed “face of Argentine wine”, promoting her products at tastings and dinners across the globe. She manages her staff of 120 via Skype and WhatsApp. ... Catena insists she sees her role as that of a detective, not an inventor. And she has modelled the CIW not after the development arm of a pharmaceutical firm, synthesising precious new compounds from scratch, but rather the upstream division of an oil company, searching for natural treasures the Earth has hidden away. ... how can destroying wine help Catena Zapata make its tipples taste better rather than worse? The answer is that the CIW is using baking as a kind of stress test: all wines subjected to this treatment will suffer, but some will suffer more and others less.
Why do people like what they like? It is one of the oldest questions of philosophy and aesthetics. Ancient thinkers inclined to mysticism proposed that a “golden ratio”—about 1.62 to 1, as in, for instance, the dimensions of a rectangle—could explain the visual perfection of objects like sunflowers and Greek temples. Other thinkers were deeply skeptical: David Hume, the 18th-century philosopher, considered the search for formulas to be absurd, because the perception of beauty was purely subjective, residing in individuals, not in the fabric of the universe. “To seek the real beauty, or real deformity,” he said, “is as fruitless an enquiry, as to pretend to ascertain the real sweet or real bitter.” ... Over time, science took up the mystery. In the 1960s, the psychologist Robert Zajonc conducted a series of experiments where he showed subjects nonsense words, random shapes, and Chinese-like characters and asked them which they preferred. In study after study, people reliably gravitated toward the words and shapes they’d seen the most. Their preference was for familiarity. ... This discovery was known as the “mere-exposure effect,” and it is one of the sturdiest findings in modern psychology. ... People get tired of even their favorite songs and movies. They develop deep skepticism about overfamiliar buzzwords. ... A surprise seems to work best when it contains some element of familiarity. ... On the one hand, Hekkert told me, humans seek familiarity, because it makes them feel safe. On the other hand, people are charged by the thrill of a challenge, powered by a pioneer lust. This battle between familiarity and discovery affects us “on every level,” Hekkert says—not just our preferences for pictures and songs, but also our preferences for ideas and even people. ... The power of these eureka moments isn’t bound to arts and culture. It’s a force in the academic world as well. Scientists and philosophers are exquisitely sensitive to the advantage of ideas that already enjoy broad familiarity.
Now, with The Case Against Sugar, Taubes launches his toughest crusade yet: to prove that we've been bamboozled into thinking that cookies and soda are simply "empty" calories and not uniquely toxic ones. That's the result, he argues, of a long history of deception from the sugar industry and its support of shoddy science. ... With his new book, Taubes will likely have his largest platform, and an audience poised to listen. By now, nearly everyone believes that Americans eat too much sugar. Most experts agree that it's a major contributor to our nation's grim health: More than a third of adults are obese, and one in 11 has diabetes. This understanding has spurred campaigns for soda taxes nationwide — five measures were approved by voters in November — and moves by big companies to ban sugary drinks from workplace cafeterias. ... Even these new anti-sugar crusaders, he says, are motivated by a naive, and ultimately dangerous, "less is better" view of sugar. To Taubes, the answer to our obesity crisis isn't more expensive soda and less sweetened cereals. It's to stop poisoning ourselves altogether. ... By rooting through archives and obscure textbooks, he has uncovered, he says, evidence that sugar is not just the harmless, empty calories we indulge in, but that it may well be toxic, dangerous even in small amounts.
But after stopping on a desolate gravel road next to a sign for a gas station, Santillan got the feeling that the voice might be steering him wrong. He’d already been driving for nearly an hour, yet the ETA on the GPS put his arrival time at around 5:20 P.M., eight hours later. He reentered his destination and got the same result. Though he sensed that something was off, he made a conscious choice to trust the machine. He had come here for an adventure, after all, and maybe it knew where he was really supposed to go. ... It’s comforting to know where you are, to see yourself distilled into a steady blue icon gliding smoothly along a screen. With a finger tap or a short request to Siri or Google Now—which, like other smartphone tools, rely heavily on data from cell towers and Wi-Fi hot spots as well as satellites—a wonderful little trail appears on your device, beckoning you to follow. ... The convenience comes at a price, however. There’s the creepy Orwellian fact of Them always knowing where We are (or We always knowing where They are). More concerning are the navigation-fail horror stories that have become legend. ... Enough people have been led astray by their GPS in Death Valley that the area’s former wilderness coordinator called the phenomenon “death by GPS.” ... By turning on a GPS every time we head somewhere new, we’re also cutting something fundamental out of the experience of traveling: the adventures and surprises that come with finding—and losing—our way. ... Individuals who frequently navigate complex environments the old-fashioned way, by identifying landmarks, literally grow their brains.