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“Some of the most important theories explaining how quantum matter behaves in the universe are based on their existence, but they have eluded direct imaging since they were first theoretically conceived in the 1930s.”

“A magnetic monopole is a ‘hypothetical’ particle that is a magnet with only one single magnetic pole,” says UCD Theoretical Physicist, Professor Hans-Benjamin Braun from the UCD School of Physics, who co-led the study with Dr Laura Heyderman from the Paul Scherrer Institute in Switzerland.

Initially conceived by the British-Swiss theoretical physicist Dirac in 1931, monopoles were proposed to occur as emergent quasiparticles in so called pyrochlore spin-ice systems by Castelnovo, Moessner and Sondhi in 2008.

Instead of reading an entire news article, watching an entire television show or listening to an entire speech, growing numbers of people are happy to jump to the summary, the video clip, the sound bite — never mind if context and nuance are lost in the process; never mind if it’s our emotions, more than our sense of reason, that are engaged; never mind if statements haven’t been properly vetted and sourced.

And online research enables scholars to power-search for nuggets of information that might support their theses, saving them the time of wading through stacks of material that might prove marginal but that might have also prompted them to reconsider or refine their original thinking.

Digital insiders like Mr. Lanier and Paulina Borsook, the author of the book “Cyberselfish,” have noted the easily distracted, adolescent quality of much of cyberculture. Ms. Borsook describes tech-heads as having “an angry adolescent view of all authority as the Pig Parent,” writing that even older digerati want to think of themselves as “having an Inner Bike Messenger.”

authors “will increasingly tailor their work to a milieu that the writer Caleb Crain describes as ‘groupiness,’ where people read mainly ‘for the sake of a feeling of belonging’ rather than for personal enlightenment or amusement. As social concerns override literary ones, writers seem fated to eschew virtuosity and experimentation in favor of a bland but immediately accessible style.

However impossible it is to think of “Jon & Kate Plus Eight” or “Jersey Shore” as art, reality shows have taken over wide swaths of television,

Those include insisting on a proctored final exam and reminding students of that exam “early, often, and broadly, so students are ever-conscious that they will be responsible for the material in an unaided environment.”

watching kids work at mastering games confirms what I know from my own experience: learning is essentially hard; it happens best when one is deeply engaged in hard and challenging activities.

The preoccupation in America with "Making It Easy" is self-defeating and cause for serious worry about the deterioration of the learning environment.

I have found that when they get the support and have access to suitable software systems, children's enthusiasm for playing games easily gives rise to an enthusiasm for making them, and this in turn leads to more sophisticated thinking about all aspects of games, including those aspects that we are discussing here. Of course, the games they can make generally lack the polish and the complexity of those made by professional designers. But the idea that children should draw, write stories and play music is not contradicted by the fact that their work is not of professional quality. I would predict that within a decade, making a computer game will be as much a part of children's culture as any of these art forms.

That’s not to say there isn’t any room for humans in Demand’s process. They just aren’t worth very much. First, a crowdsourced team of freelance “title proofers” turn the algorithm’s often awkward or nonsensical phrases into something people will understand: “How to make a church-pew breakfast nook,” for example, becomes “How to make a breakfast nook out of a church pew.” Approved headlines get fed into a password-protected section of Demand’s Web site called Demand Studios, where any Demand freelancer can see what jobs are available. It’s the online equivalent of day laborers waiting in front of Home Depot. Writers can typically select 10 articles at a time; videographers can hoard 40. Nearly every freelancer scrambles to load their assignment queue with titles they can produce quickly and with the least amount of effort — because pay for individual stories is so lousy, only a high-speed, high-volume approach will work. The average writer earns $15 per article for pieces that top out at a few hundred words, and the average filmmaker about $20 per clip, paid weekly via PayPal. Demand also offers revenue sharing on some articles, though it can take months to reach even $15 in such payments. Other freelancers sign up for the chance to copyedit ($2.50 an article), fact-check ($1 an article), approve the quality of a film (25 to 50 cents a video), transcribe ($1 to $2 per video), or offer up their expertise to be quoted or filmed (free). Title proofers get 8 cents a headline. Coming soon: photographers and photo editors. So far, the company has paid out more than $17 million to Demand Studios workers; if the enterprise reaches Rosenblatt’s goal of producing 1 million pieces of content a month, the payouts could easily hit $200 million a year, less than a third of what The New York Times shells out in wages and benefits to produce its roughly 5,000 articles a month.

But once it was automated, every algorithm-generated piece of content produced 4.9 times the revenue of the human-created ideas. So Rosenblatt got rid of the editors. Suddenly, profit on each piece was 20 to 25 times what it had been. It turned out that gut instinct and experience were less effective at predicting what readers and viewers wanted — and worse for the company — than a formula.

Here is the thing that Rosenblatt has since discovered: Online content is not worth very much. This may be a truism, but Rosenblatt has the hard, mathematical proof. It’s right there in black and white, in the Demand Media database — the lifetime value of every story, algorithmically derived, and very, very small. Most media companies are trying hard to increase those numbers, to boost the value of their online content until it matches the amount of money it costs to produce. But Rosenblatt thinks they have it exactly backward. Instead of trying to raise the market value of online content to match the cost of producing it — perhaps an impossible proposition — the secret is to cut costs until they match the market value.

tackle what colleges were doing poorly: graduating students. Half the students who enroll in post-secondary education never get a degree but still accumulate debt

school spends millions to employ more than 160 “admissions counselors” who man the phones, especially on weekends, guiding prospective students into the right degree program

“College is designed in every way for that 20 percent—cost, time, scheduling, everything,” says LeBlanc. He set out to create an institution for the other 80 percent, one that was flexible and offered a seamless online experience

online courses are created centrally and then farmed out to a small army of adjuncts hired for as little as $2,200 a class. Those adjuncts have scant leeway in crafting the learning experience.

highly standardized courses, and adjuncts who act more like coaches than professors

we are cognitively blind to disconfirming data and challenging ideas.

To innovate, people have to take their normal thinking to a much higher level. Most of us have to be taught how to do that.

Fear of failure, fear of looking bad, and fear of losing our job if we make mistakes all can lead to what Chris Argyris called “defensive reasoning”: the tendency to defend what we believe. This makes it hard to get outside of ourselves in order to “think out of the box.”

most organizations exist to produce predictable, reliable, standardized results. In those environments, mistakes and failures are bad.

To innovate, you must simultaneously tolerate mistakes and insist on operational excellence.

Humility, empathy, and the devaluation of hierarchical rank were critical to making this new culture work.

That makes this field of science rather peculiar and probably explains why there hasn’t been much progress. But it’s not like we don’t have any questions that need to be answered. There are a lot of questions that have been around for decades. For example, what is dark energy? What is dark matter? What are the masses of the Standard Model particles? And what’s up with the foundation of quantum mechanics? Is a theory that's fundamentally not deterministic, where we cannot predict outcomes, the last word that we have, or is there something more to it? Is there maybe another underlying structure to reality?

but we haven't reached the fundamental level. Maybe we will never reach it. Certainly, the theories that we have right now are not all there is. The question is, of course, if we don’t have any guidance by experiment, how do we make progress? And are we doing the right thing?

We’ve reached this point where we have to carefully rethink if the criteria that we’re using to select our theories are promising at all. If one looks at the history of this field in the foundations of physics, progress has usually been made by looking at questions that, at least in hindsight, were well posed, where there was an actual mathematical contradiction. For example, special relativity is incompatible with Newtonian gravity. If you try to resolve this incompatibility, you get general relativity.

There are various similar examples where such breakthroughs have happened because there was a real problem. There was an inconsistency and people had to resolve it. It had nothing to do with beauty. Maybe beauty was, in some cases, the personal motivation of the people to work on it. There’s certainly some truth to this, but I don’t think it’s good to turn this story around and say that if we only pay attention to this motivation that comes from ideals of beauty it will lead to progress.

If we are working with the wrong theories, we are making the wrong extrapolations, we have the wrong expectations, we make the wrong experiments, and then we don’t get any new data. We have no guidance to develop these theories. So, it’s a chicken and egg problem. We have to break the cycle. I don’t have a miracle cure to these problems. These are hard problems. It’s not clear what a good theory is to develop. I’m not any wiser than all the other 20,000 people in the field.

The way that research is funded in foundations of physics and in many other fields just puts a lot of things at a disadvantage that are not pursued anymore. Typically, everything that takes longer than three years to complete, no one will start it because they can’t afford it. They can literally not afford it.

Who makes the decisions about the funding? Superficially, people say that it's a funding agency, so it’s the university who get to hire people. But that puts the blame on the wrong party. In the end it’s the community itself who makes the decisions. What do the funding agencies do if they get a proposal? They send it to reviewers. And who are the reviewers? They're people from the same community. If you look at how hiring decisions are being made, there’s some committee and they are people from the same community. They have some advisory boards or something, which contains people from the same community.

Even if that wasn’t so, what the people in these committees would be doing is looking at easy measures for scientific success. Presently, the most popular of these measures are the number of publications and the number of citations. And maybe also whether the person has published in high-impact journals. So, these are the typical measures that are presently being used. But what do they measure? They primarily measure popularity. They indicate whether somebody’s research is well received by a lot of people in the same community. And that’s why once a research area grows beyond a certain critical mass, you have sufficiently many people who tell each other that what they’re doing is the good thing to do. They review each other’s papers and say that that’s great and it's what we should continue to do. It’s a problem in all communities that grow beyond a certain size.

I later came to the United States and then Canada, and that gave me the opportunity to learn a lot about quantum gravity. I also figured out that much of what goes on in quantum gravity is very detached from reality. It’s pretty much only mathematics. Yes, the mathematics is there, but I still don’t know if it’s the mathematics that describes reality.

That’s the very reason why we don’t normally think of gravity as a weak force. It’s the only force that is left over on long distances, and the reason for this is that it adds up. It gets stronger the more mass you pile up. More precisely, we should say that the reason we find it so hard to measure quantum gravitational effects is that we either have a particle that has very pronounced quantum properties, like, say, a single electron or something like that, but then it’s so light that we cannot measure the gravitational field. Or we have some object that is so heavy that we can measure the gravitational field, but then it doesn’t have quantum properties. Okay, so that’s the actual problem.

did notreturn any recent studies investigating the effec-tiveness of a purely cognitive intervention in thetreatment of MPA; consequently, research inthis particular area is needed

Past re-search has focused on combined interventions;however, often these programs run for over 6weeks and it is unknown which aspects of theintervention are most effective (e.g., Nagel,Himle, & Papsdorf, 1989)

State–Trait Anxiety Inventory (STAI).The STAI is widely used in anxiety researchand is considered to be a valid and reliable scale(Kenny, 2006).

The PAI (Nagel, Himle, & Papsdorf, 1981) isbased on the STAI and is a music inventoryassessing the three-systems model of anxiety

heart rate at 10 min, 5

Signs of anxiety included trem-bling knees, lifting shoulders, stiff back and/orneck, trembling hands, stiff arms, face deadpan,shaking head, moistening and/or biting lips, dis-tressed facial expressions, and sweating.

Nagel et al.reported that the average preintervention scorewas 55 and the average postintervention scorewas 38, with a score of 39 or less indicating a

person has few problems with performance anx-iety

Researchers have found that MPA af-fects instrumentalists and vocalists of all agesand abilities, including students, professionals,amateurs, and children (Brotons, 1994; Kenny,2006; Liston, Frost, & Mohr, 2003)

Few studies have investigated whether a cog-nitive intervention can reduce anxiety and en-hance performance in musicians (Lehrer, 1987;Steptoe & Fidler, 1987)

Few studies have investigated whether a cog-nitive intervention can reduce anxiety and en-hance performance in musicians (Lehrer, 1987;Steptoe & Fidler, 1987

The cognitive intervention had no significanteffect on anxiety levels. Sweeney and Horan’s(1982) study indicated that a cognitive restruc-turing program may be helpful in the treatmentof MPA; their program, featuring cognitive re-structuring, significantly reduced anxiety.

d it is unknown which aspects of theintervention are most effective (e.g., Nagel,Himle, & Papsdorf, 1989)

The STAI is widely used in anxiety researchand is considered to be a valid and reliable scale

Performance Anxiety Inventory (PAI)

cognitive, behavioral, and physiological fac

and has beenwidely used in treatment outcome research

Behavioral Anxiety Index (BAI)

igns of anxiety included trem-bling knees, lifting shoulders, stiff back and/orneck, trembling hands, stiff arms, face deadpan,shaking head, moistening and/or biting lips, dis-tressed facial expressions, and sweating

Participants were then taught howthoughts, behaviors, and feelings interact andinfluence performance

practical exercise, how people waste their en-ergy trying to control uncontrollable factors,thereby impairing performance

This exercise wasdesigned to demonstrate how thoughts cansometimes be irrational and can be changed inlight of new evidence

how to use self-talk effectively and how touse cues

Participants practiced how to identify negativethoughts, stop the thoughts, and use cues to helpthem overcome the negative thoughts.

Imagery is a mentalexercise that can help athletes maintain concen-tration, decrease anxiety, and improve confi-dence; thus, it may also be helpful for somemusicians (Gregg & Clark, 2007).

Participants in the wait-list controlgroup waited 3 weeks until their second perfor-mance, which was on the same night as theirfirst worksho

MPA is a pervasive problem affecting musi-cians of all ages and abilities. As compared withthe research on mental skills training in athletes,relatively little is known about the assessment,treatment, and theoretical underpinnings ofMPA

Kenny (2006) suggested that improving perfor-mance quality will have a positive, self-reinforcing effect on the musician and enhanceconfidence in future performances.

We predicted that anxiety levels would de-crease in the treatment group from pre- to post-test. This hypothesis was partially supported.Specifically, there was a significant reductionon the PAI in the treatment group. Although theparticipants improved after the intervention,they were still not within the optimal rangeaccording to Nagel et al. (1981

Although the decrease in anxiety was notas large in our study, our participants droppedfrom the high performance anxiety category tothe moderate performance anxiety category