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Thursday, January 23, 2014

A New Physics Theory of Life

Jeremy England
Jeremy England, a 31-year-old physicist at MIT, thinks he has found the underlying physics driving the origin and evolution of life.


Katherine Taylor for Quanta Magazine

January 22, 2014
Comments (43)
   
Why does life exist?

Popular hypotheses credit a primordial soup, a bolt of lightning and a colossal stroke of luck. But if a provocative new theory is correct, luck may have little to do with it. Instead, according to the physicist proposing the idea, the origin and subsequent evolution of life follow from the fundamental laws of nature and “should be as unsurprising as rocks rolling downhill.”

From the standpoint of physics, there is one essential difference between living things and inanimate clumps of carbon atoms: The former tend to be much better at capturing energy from their environment and dissipating that energy as heat. Jeremy England, a 31-year-old assistant professor at the Massachusetts Institute of Technology, has derived a mathematical formula that he believes explains this capacity. The formula, based on established physics, indicates that when a group of atoms is driven by an external source of energy (like the sun or chemical fuel) and surrounded by a heat bath (like the ocean or atmosphere), it will often gradually restructure itself in order to dissipate increasingly more energy. This could mean that under certain conditions, matter inexorably acquires the key physical attribute associated with life.

Plagiomnium affine
Kristian Peters

Cells from the moss Plagiomnium affine with visible chloroplasts, organelles that conduct photosynthesis by capturing sunlight.

“You start with a random clump of atoms, and if you shine light on it for long enough, it should not be so surprising that you get a plant,” England said.

England’s theory is meant to underlie, rather than replace, Darwin’s theory of evolution by natural selection, which provides a powerful description of life at the level of genes and populations. “I am certainly not saying that Darwinian ideas are wrong,” he explained. “On the contrary, I am just saying that from the perspective of the physics, you might call Darwinian evolution a special case of a more general phenomenon.”

His idea, detailed in a recent paper and further elaborated in a talk he is delivering at universities around the world, has sparked controversy among his colleagues, who see it as either tenuous or a potential breakthrough, or both.

England has taken “a very brave and very important step,” said Alexander Grosberg, a professor of physics at New York University who has followed England’s work since its early stages. The “big hope” is that he has identified the underlying physical principle driving the origin and evolution of life, Grosberg said.

“Jeremy is just about the brightest young scientist I ever came across,” said Attila Szabo, a biophysicist in the Laboratory of Chemical Physics at the National Institutes of Health who corresponded with England about his theory after meeting him at a conference. “I was struck by the originality of the ideas.”

Others, such as Eugene Shakhnovich, a professor of chemistry, chemical biology and biophysics at Harvard University, are not convinced. “Jeremy’s ideas are interesting and potentially promising, but at this point are extremely speculative, especially as applied to life phenomena,” Shakhnovich said.

England’s theoretical results are generally considered valid. It is his interpretation — that his formula represents the driving force behind a class of phenomena in nature that includes life — that remains unproven. But already, there are ideas about how to test that interpretation in the lab.

“He’s trying something radically different,” said Mara Prentiss, a professor of physics at Harvard who is contemplating such an experiment after learning about England’s work. “As an organizing lens, I think he has a fabulous idea. Right or wrong, it’s going to be very much worth the investigation.”
A computer simulation by Jeremy England and colleagues shows a system of particles confined inside a viscous fluid in which the turquoise particles are driven by an oscillating force. Over time (from top to bottom), the force triggers the formation of more bonds among the particles.
Courtesy of Jeremy England

A computer simulation by Jeremy England and colleagues shows a system of particles confined inside a viscous fluid in which the turquoise particles are driven by an oscillating force. Over time (from top to bottom), the force triggers the formation of more bonds among the particles.

At the heart of England’s idea is the second law of thermodynamics, also known as the law of increasing entropy or the “arrow of time.” Hot things cool down, gas diffuses through air, eggs scramble but never spontaneously unscramble; in short, energy tends to disperse or spread out as time progresses. Entropy is a measure of this tendency, quantifying how dispersed the energy is among the particles in a system, and how diffuse those particles are throughout space. It increases as a simple matter of probability: There are more ways for energy to be spread out than for it to be concentrated. Thus, as particles in a system move around and interact, they will, through sheer chance, tend to adopt configurations in which the energy is spread out. Eventually, the system arrives at a state of maximum entropy called “thermodynamic equilibrium,” in which energy is uniformly distributed. A cup of coffee and the room it sits in become the same temperature, for example. As long as the cup and the room are left alone, this process is irreversible. The coffee never spontaneously heats up again because the odds are overwhelmingly stacked against so much of the room’s energy randomly concentrating in its atoms.

Although entropy must increase over time in an isolated or “closed” system, an “open” system can keep its entropy low — that is, divide energy unevenly among its atoms — by greatly increasing the entropy of its surroundings. In his influential 1944 monograph “What Is Life?” the eminent quantum physicist Erwin Schrödinger argued that this is what living things must do. A plant, for example, absorbs extremely energetic sunlight, uses it to build sugars, and ejects infrared light, a much less concentrated form of energy. The overall entropy of the universe increases during photosynthesis as the sunlight dissipates, even as the plant prevents itself from decaying by maintaining an orderly internal structure.

Life does not violate the second law of thermodynamics, but until recently, physicists were unable to use thermodynamics to explain why it should arise in the first place. In Schrödinger’s day, they could solve the equations of thermodynamics only for closed systems in equilibrium. In the 1960s, the Belgian physicist Ilya Prigogine made progress on predicting the behavior of open systems weakly driven by external energy sources (for which he won the 1977 Nobel Prize in chemistry). But the behavior of systems that are far from equilibrium, which are connected to the outside environment and strongly driven by external sources of energy, could not be predicted.

This situation changed in the late 1990s, due primarily to the work of Chris Jarzynski, now at the University of Maryland, and Gavin Crooks, now at Lawrence Berkeley National Laboratory. Jarzynski and Crooks showed that the entropy produced by a thermodynamic process, such as the cooling of a cup of coffee, corresponds to a simple ratio: the probability that the atoms will undergo that process divided by their probability of undergoing the reverse process (that is, spontaneously interacting in such a way that the coffee warms up). As entropy production increases, so does this ratio: A system’s behavior becomes more and more “irreversible.” The simple yet rigorous formula could in principle be applied to any thermodynamic process, no matter how fast or far from equilibrium. “Our understanding of far-from-equilibrium statistical mechanics greatly improved,” Grosberg said. England, who is trained in both biochemistry and physics, started his own lab at MIT two years ago and decided to apply the new knowledge of statistical physics to biology.

Using Jarzynski and Crooks’ formulation, he derived a generalization of the second law of thermodynamics that holds for systems of particles with certain characteristics: The systems are strongly driven by an external energy source such as an electromagnetic wave, and they can dump heat into a surrounding bath. This class of systems includes all living things. England then determined how such systems tend to evolve over time as they increase their irreversibility. “We can show very simply from the formula that the more likely evolutionary outcomes are going to be the ones that absorbed and dissipated more energy from the environment’s external drives on the way to getting there,” he said. The finding makes intuitive sense: Particles tend to dissipate more energy when they resonate with a driving force, or move in the direction it is pushing them, and they are more likely to move in that direction than any other at any given moment.

“This means clumps of atoms surrounded by a bath at some temperature, like the atmosphere or the ocean, should tend over time to arrange themselves to resonate better and better with the sources of mechanical, electromagnetic or chemical work in their environments,” England explained.

Self Replicating Microstructures
Courtesy of Michael Brenner/Proceedings of the National Academy of Sciences

Self-Replicating Sphere Clusters: According to new research at Harvard, coating the surfaces of microspheres can cause them to spontaneously assemble into a chosen structure, such as a polytetrahedron (red), which then triggers nearby spheres into forming an identical structure.

Self-replication (or reproduction, in biological terms), the process that drives the evolution of life on Earth, is one such mechanism by which a system might dissipate an increasing amount of energy over time. As England put it, “A great way of dissipating more is to make more copies of yourself.” In a September paper in the Journal of Chemical Physics, he reported the theoretical minimum amount of dissipation that can occur during the self-replication of RNA molecules and bacterial cells, and showed that it is very close to the actual amounts these systems dissipate when replicating. He also showed that RNA, the nucleic acid that many scientists believe served as the precursor to DNA-based life, is a particularly cheap building material. Once RNA arose, he argues, its “Darwinian takeover” was perhaps not surprising.

The chemistry of the primordial soup, random mutations, geography, catastrophic events and countless other factors have contributed to the fine details of Earth’s diverse flora and fauna. But according to England’s theory, the underlying principle driving the whole process is dissipation-driven adaptation of matter.

This principle would apply to inanimate matter as well. “It is very tempting to speculate about what phenomena in nature we can now fit under this big tent of dissipation-driven adaptive organization,” England said. “Many examples could just be right under our nose, but because we haven’t been looking for them we haven’t noticed them.”

Scientists have already observed self-replication in nonliving systems. According to new research led by Philip Marcus of the University of California, Berkeley, and reported in Physical Review Letters in August, vortices in turbulent fluids spontaneously replicate themselves by drawing energy from shear in the surrounding fluid. And in a paper appearing online this week in Proceedings of the National Academy of Sciences, Michael Brenner, a professor of applied mathematics and physics at Harvard, and his collaborators present theoretical models and simulations of microstructures that self-replicate. These clusters of specially coated microspheres dissipate energy by roping nearby spheres into forming identical clusters. “This connects very much to what Jeremy is saying,” Brenner said.

Besides self-replication, greater structural organization is another means by which strongly driven systems ramp up their ability to dissipate energy. A plant, for example, is much better at capturing and routing solar energy through itself than an unstructured heap of carbon atoms. Thus, England argues that under certain conditions, matter will spontaneously self-organize. This tendency could account for the internal order of living things and of many inanimate structures as well. “Snowflakes, sand dunes and turbulent vortices all have in common that they are strikingly patterned structures that emerge in many-particle systems driven by some dissipative process,” he said. Condensation, wind and viscous drag are the relevant processes in these particular cases.

“He is making me think that the distinction between living and nonliving matter is not sharp,” said Carl Franck, a biological physicist at Cornell University, in an email. “I’m particularly impressed by this notion when one considers systems as small as chemical circuits involving a few biomolecules.”

Snowflake
Wilson Bentley

If a new theory is correct, the same physics it identifies as responsible for the origin of living things could explain the formation of many other patterned structures in nature. Snowflakes, sand dunes and self-replicating vortices in the protoplanetary disk may all be examples of dissipation-driven adaptation.

England’s bold idea will likely face close scrutiny in the coming years. He is currently running computer simulations to test his theory that systems of particles adapt their structures to become better at dissipating energy. The next step will be to run experiments on living systems.

Prentiss, who runs an experimental biophysics lab at Harvard, says England’s theory could be tested by comparing cells with different mutations and looking for a correlation between the amount of energy the cells dissipate and their replication rates. “One has to be careful because any mutation might do many things,” she said. “But if one kept doing many of these experiments on different systems and if [dissipation and replication success] are indeed correlated, that would suggest this is the correct organizing principle.”

Brenner said he hopes to connect England’s theory to his own microsphere constructions and determine whether the theory correctly predicts which self-replication and self-assembly processes can occur — “a fundamental question in science,” he said.

Having an overarching principle of life and evolution would give researchers a broader perspective on the emergence of structure and function in living things, many of the researchers said. “Natural selection doesn’t explain certain characteristics,” said Ard Louis, a biophysicist at Oxford University, in an email. These characteristics include a heritable change to gene expression called methylation, increases in complexity in the absence of natural selection, and certain molecular changes Louis has recently studied.

If England’s approach stands up to more testing, it could further liberate biologists from seeking a Darwinian explanation for every adaptation and allow them to think more generally in terms of dissipation-driven organization. They might find, for example, that “the reason that an organism shows characteristic X rather than Y may not be because X is more fit than Y, but because physical constraints make it easier for X to evolve than for Y to evolve,” Louis said.

“People often get stuck in thinking about individual problems,” Prentiss said.  Whether or not England’s ideas turn out to be exactly right, she said, “thinking more broadly is where many scientific breakthroughs are made.”

Emily Singer contributed reporting.

Correction: This article was revised on January 22, 2014, to reflect that Ilya Prigogine won the Nobel Prize in chemistry, not physics.


What Happens When Artificial Intelligence Turns On Us?

Before long, artificial intelligence will stop looking to humans for upgrades and start seeking improvements on their own. (© Warner Brothers/Courtesy of Everett Collection)
Terminator


What Happens When Artificial Intelligence Turns On Us?

In a new book, James Barrat warns that artificial intelligence will one day outsmart humans, and there is no guarantee that it will be benevolent

smithsonianmag.com
January 21, 2014

Artificial intelligence has come a long way since R2-D2. These days, most millennials would be lost without smart GPS systems. Robots are already navigating battlefields, and drones may soon be delivering Amazon packages to our doorsteps.

Siri can solve complicated equations and tell you how to cook rice. She has even proven she can even respond to questions with a sense of humor.

But all of these advances depend on a user giving the A.I. direction. What would happen if GPS units decided they didn’t want to go to the dry cleaners, or worse, Siri decided she could become smarter without you around?

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"Before we share the planet with super-intelligent machines, we must develop a science for understanding them. Otherwise, they’ll take control," author James Barrat says of his new book, Our Final Invention: Artificial Intelligence and the End of the Human Era. (Courtesy of James Barrat)

These are just the tamest of outcomes James Barrat, an author and documentary filmmaker, forecasts in his new book, Our Final Invention: Artificial Intelligence and the End of the Human Era.

Before long, Barrat says, artificial intelligence—from Siri to drones and data mining systems—will stop looking to humans for upgrades and start seeking improvements on their own. And unlike the R2-D2s and HALs of science fiction, the A.I. of our future won’t necessarily be friendly, he says: they could actually be what destroy us.

In a nutshell, can you explain your big idea?   
  
In this century, scientists will create machines with intelligence that equals and then surpasses our own. But before we share the planet with super-intelligent machines, we must develop a science for understanding them. Otherwise, they’ll take control. And no, this isn’t science fiction.

Scientists have already created machines that are better than humans at chess, Jeopardy!, navigation, data mining, search, theorem proving and countless other tasks. Eventually, machines will be created that are better than humans at A.I. research

At that point, they will be able to improve their own capabilities very quickly. These self-improving machines will pursue the goals they’re created with, whether they be space exploration, playing chess or picking stocks. To succeed they’ll seek and expend resources, be it energy or money. They’ll seek to avoid the failure modes, like being switched off or unplugged. In short, they’ll develop drives, including self-protection and resource acquisition—drives much like our own. They won’t hesitate to beg, borrow, steal and worse to get what they need.

How did you get interested in this topic?
                
I’m a documentary filmmaker. In 2000, I interviewed inventor Ray Kurzweil, roboticist Rodney Brooks and sci-fi legend Arthur C. Clarke for a TLC film about the making of the novel and film, 2001: A Space Odyssey. The interviews explored the idea of the Hal 9000, and malevolent computers. Kurzweil’s books have portrayed the A.I. future as a rapturous “singularity,” a period in which technological advances outpace humans’ ability to understand them. Yet he anticipated only good things emerging from A.I. that is strong enough to match and then surpass human intelligence. He predicts that we’ll be able to reprogram the cells of our bodies to defeat disease and aging. We’ll develop super endurance with nanobots that deliver more oxygen than red blood cells. We’ll supercharge our brains with computer implants so that we’ll become superintelligent. And we’ll port our brains to a more durable medium than our present “wetware” and live forever if we want to. Brooks was optimistic, insisting that A.I.-enhanced robots would be allies, not threats.

Scientist-turned-author Clarke, on the other hand, was pessimistic. He told me intelligence will win out, and humans would likely compete for survival with super-intelligent machines. He wasn’t specific about what would happen when we share the planet with super-intelligent machines, but he felt it’d be a struggle for mankind that we wouldn’t win.

That went against everything I had thought about A.I., so I began interviewing artificial intelligence experts.

What evidence do you have to support your idea?

Advanced artificial intelligence is a dual-use technology, like nuclear fission, capable of great good or great harm. We’re just starting to see the harm.

The NSA privacy scandal came about because the NSA developed very sophisticated data-mining tools. The agency used its power to plumb the metadata of millions of phone calls and the the entirety of the Internet—critically, all email. Seduced by the power of data-mining A.I., an agency entrusted to protect the Constitution instead abused it. They developed tools too powerful for them to use responsibly.

Today, another ethical battle is brewing about making fully autonomous killer drones and battlefield robots powered by advanced A.I.—human-killers without humans in the loop. It’s brewing between the Department of Defense and the drone and robot makers who are paid by the DOD, and people who think it’s foolhardy and immoral to create intelligent killing machines. Those in favor of autonomous drones and battlefield robots argue that they’ll be more moral—that is, less emotional, will target better and be more disciplined than human operators. Those against taking humans out of the loop are looking at drones’ miserable history of killing civilians, and involvement in extralegal assassinations. Who shoulders the moral culpability when a robot kills? The robot makers, the robot users, or no one? Nevermind the technical hurdles of telling friend from foe. 

In the longer term, as experts in my book argue, A.I. approaching human-level intelligence won’t be easily controlled; unfortunately, super-intelligence doesn’t imply benevolence. As A.I. theorist Eliezer Yudkowsky of MIRI [the Machine Intelligence Research Institute] puts it, “The A.I. does not love you, nor does it hate you, but you are made of atoms it can use for something else.” If ethics can’t be built into a machine, then we’ll be creating super-intelligent psychopaths, creatures without moral compasses, and we won’t be their masters for long.

What is new about your thinking?

Individuals and groups as diverse as American computer scientist Bill Joy and MIRI have long warned that we have much to fear from machines whose intelligence eclipses our own. In Our Final Invention, I argue that A.I. will also be misused on the development path to human-level intelligence. Between today and the day when scientists create human-level intelligence, we’ll have A.I.-related mistakes and criminal applications.

Why hasn’t more been done, or, what is being done to stop AI from turning on us?

There’s not one reason, but many. Some experts don’t believe we’re close enough to creating human-level artificial intelligence and beyond to worry about its risks. Many A.I. makers win contracts with the Defense Advanced Research Projects Agency [DARPA] and don’t want to raise issues they consider political. The normalcy bias is a cognitive bias that prevents people from reacting to disasters and disasters in the making—that’s definitely part of it. But a lot of A.I. makers are doing something. Check out the scientists who advise MIRI. And, a lot more will get involved once the dangers of advanced A.I. enter mainstream dialogue.

Can you describe a moment when you knew this was big?
          
We humans steer the future not because we’re the fastest or the strongest creatures on the planet, but because we’re the smartest. When we share the planet with creatures smarter than ourselves, they’ll steer the future. When I understood this idea, I felt I was writing about the most important question of our time.

Every big thinker has predecessors whose work was crucial to his discovery. Who gave you the foundation to build your idea?

The foundations of A.I. risk analysis were developed by mathematician I. J. Good, science fiction writer Vernor Vinge, and others including A.I. developer Steve Omohundro. Today, MIRI and Oxford’s Future of Humanity Institute are almost alone in addressing this problem. Our Final Invention has about 30 pages of endnotes acknowledging these thinkers.

In researching and developing your idea, what has been the high point? And the low point?

The high points were writing Our Final Invention, and my ongoing dialogue with A.I. makers and theorists. People who program A.I. are aware of the safety issues and want to help come up with safeguards. For instance, MIRI is working on creating “friendly” A.I.

Computer scientist and theorist Steve Omohundro has advocated a “scaffolding” approach, in which provably safe A.I. helps build the next generation of A.I. to ensure that it too is safe. Then that A.I. does the same, and so on. I think a public-private partnership has to be created to bring A.I.-makers together to share ideas about security—something like the International Atomic Energy Agency, but in partnership with corporations. The low points? Realizing that the best, most advanced A.I. technology will be used to create weapons. And those weapons eventually will turn against us.

What two or three people are most likely to try to refute your argument? Why?

Inventor Ray Kurzweil is the chief apologist for advanced technologies. In my two interviews with him, he claimed that we would meld with the A.I. technologies through cognitive enhancements. Kurzweil and people broadly called transhumanists and singularitarians think A.I. and ultimately artificial general intelligence and beyond will evolve with us. For instance, computer implants will enhance our brains’ speed and overall capabilities. Eventually, we’ll develop the technology to transport our intelligence and consciousness into computers. Then super-intelligence will be at least partly human, which in theory would ensure super-intelligence was “safe.”

For many reasons, I’m not a fan of this point of view. Trouble is, we humans aren’t reliably safe, and it seems unlikely that super-intelligent humans will be either. We have no idea what happens to a human’s ethics after their intelligence is boosted. We have a biological basis for aggression that machines lack. Super-intelligence could very well be an aggression multiplier. 

Who will be most affected by this idea?

Everyone on the planet has much to fear from the unregulated development of super-intelligent machines. An intelligence race is going on right now. Achieving A.G.I. is job number one for Google, IBM and many smaller companies like Vicarious and Deep Thought, as well as DARPA, the NSA and governments and companies abroad. Profit is the main motivation for that race. Imagine one likely goal: a virtual human brain at the price of a computer. It would be the most lucrative commodity in history. Imagine banks of thousands of PhD quality brains working 24/7 on pharmaceutical development, cancer research, weapons development and much more. Who wouldn’t want to buy that technology?

Meanwhile, 56 nations are developing battlefield robots, and the drive is to make them, and drones, autonomous. They will be machines that kill, unsupervised by humans. Impoverished nations will be hurt most by autonomous drones and battlefield robots. Initially, only rich countries will be able to afford autonomous kill bots, so rich nations will wield these weapons against human soldiers from impoverished nations.

How might it change life, as we know it?

Imagine: in as little as a decade, a half-dozen companies and nations field computers that rival or surpass human intelligence. Imagine what happens when those computers become expert at programming smart computers. Soon we’ll be sharing the planet with machines thousands or millions of times more intelligent than we are. And, all the while, each generation of this technology will be weaponized. Unregulated, it will be catastrophic.

What questions are left unanswered?

Solutions. The obvious solution would be to give the machines a moral sense that makes them value human life and property. But programming ethics into a machine turns out to be extremely hard. Moral norms differ from culture to culture, they change over time, and they’re contextual. If we humans can’t agree on when life begins, how can we tell a machine to protect life? Do we really want to be safe, or do we really want to be freeWe can debate it all day and not reach a consensus, so how can we possibly program it?

We also, as I mentioned earlier, need to get A.I. developers together. In the 1970s, recombinant DNA researchers decided to suspend research and get together for a conference at Asilomar in Pacific Grove, California. They developed basic safety protocols like “don’t track the DNA out on your shoes,” for fear of contaminating the environment with genetic works in progress. Because of the “Asilomar Guidelines,” the world benefits from genetically modified crops, and gene therapy looks promising. So far as we know, accidents were avoided. It’s time for an Asilomar Conference for A.I.

What’s standing in the way?

A huge economic wind propels the development of advanced A.I. Human-level intelligence at the price of a computer will be the hottest commodity in history. Google and IBM won’t want to share their secrets with the public or competitors. The Department of Defense won’t want to open their labs to China and Israel, and vice-versa. Public awareness has to push policy towards openness and public-private partnerships designed to ensure safety.

What is next for you?

I’m a documentary filmmaker, so of course I’m thinking about a film version of Our Final Invention



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How to Digitally Record/Video a UFO sighting:


Como registar digitalmente ou gravar um vídeo de um avistamento de um UFO:




Stabilize the camera on a tripod. If there is no tripod, then set it on top of a stable, flat surface. If that is not possible lean against a wall to stabilize your body and prevent the camera from filming in a shaky, unsteady manner.

Estabilize a camera com um tripé. Se não tiver um tripé, então coloque-a em cima de uma superfície estável. Se não for possível, então encoste-se a uma parede para estabilizar o corpo e evitar que a camera registe de maneira tremida e instável.

Provide visual reference points for comparison. This includes the horizon, treetops, lampposts, houses, and geographical landmarks (i.e., Horsetooth Reservoir, Mt. Adams, etc.) Provide this in the video whenever is appropriate and doesn’t detract from what your focus is, the UFO.

Forneça pontos visuais de referência para comparação. Isso inclui o horizonte, cimo das árvores, postes de iluminação, pontos de referência geográficos (como o Reservatório de Horsetooth, Mone Adams, etc) Forneça esses pontos no vídeo sempre que for apropriado e não se distraia do que é o seu foco, o UFO/a Nave.

Narrate your videotape. Provide details of the date, time, location, and direction (N,S,E,W) you are looking in. Provide your observations on the weather, including approximate temperature, windspeed, any visible cloud cover or noticeable weather anomalies or events. Narrate on the shape, size, color, movements, approximate altitude of the UFO, etc and what it appears to be doing. Also include any unusual physical, psychological or emotional sensations you might have. Narrate any visual reference points on camera so they correlate with what the viewer will see, and thereby will be better able to understand.

Faça a narração do vídeo. Forneça pormenores sobre a data, hora, local e direcção (Norte, Sul, Este, Oeste) que está a observar. Faça observações sobre as condições atmosféricas, incluindo a temperatura aproximada, velocidade do vento, quantidade de nuvens, anomalias ou acontecimentos meteorológicos evidentes. Descreva a forma, o tamanho, a cor, os movimentos, a altitude aproximada onde se encontra o UFO/nave, etc e o que aparenta estar a fazer. Inclua também quaisquer aspectos pouco habituais de sensações físicas, psicológicas ou emocionais que possa ter. Faça a narração de todos os pontos de referência visual que o espectador irá ver e que, deste modo, será capaz de compreender melhor.

Be persistent and consistent. Return to the scene to videotape and record at this same location. If you have been successful once, the UFO sightings may be occurring in this region regularly, perhaps for specific reasons unknown, and you may be successful again. You may also wish to return to the same location at a different time of day (daylight hours) for better orientation and reference. Film just a minute or two under “normal” circumstances for comparison. Write down what you remember immediately after. As soon as you are done recording the experience/event, immediately write down your impressions, memories, thoughts, emotions, etc. so it is on the record in writing. If there were other witnesses, have them independently record their own impressions, thoughts, etc. Include in this exercise any drawings, sketches, or diagrams. Make sure you date and sign your documentation.

Seja persistente e não contraditório. Volte ao local da cena e registe o mesmo local. Se foi bem sucedido uma vez, pode ser que nessa região ocorram avistamentos de UFOs/naves com regularidade, talvez por razões específicas desconhecidas, e talvez possa ser novamente bem sucedido. Pode também desejar voltar ao mesmo lugar a horas diferentes do dia (durante as horas de luz)para ter uma orientação e referência melhor. Filme apenas um ,inuto ou dois em circunstâncias “normais” para ter um termo de comparação. Escreva tudo o que viu imediatamente após o acontecimento. Logo após ter feito o registo da experiência/acontecimento, escreva imediatamente as impressões, memórias, pensamentos, emoções, etc para que fiquem registadas por escrito. Se houver outras testemunhas, peça-lhes para registar independentemente as suas próprias impressões, pensamentos, etc. Inclua quaisquer desenhos, esbolos, diagramas. Certifique-se que data e assina o seu documento/testemunho.

Always be prepared. Have a digital camera or better yet a video camera with you, charged and ready to go, at all times. Make sure you know how to use your camera (and your cell phone video/photo camera) quickly and properly. These events can occur suddenly, unexpectedly, and often quite randomly, so you will need to be prepared.

Esteja sempre preparado, Tenha sempre uma camera digital, melhor ainda, uma camera vídeo consigo, carregada e pronta a usar sempre que necessário. Certifique-se que sabe como lidar com a sua camera (ou com o seu celular/camera fotográfica) rápida e adequadamente. Esses acontecimentos podem acontecer súbita e inesperadamente e, por vezes, acidentalmente, por isso, necessita estar preparado.

Look up. Be prepared. Report. Share.

Olhe para cima, Esteja preparado, Relate, Partilhe.

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