The Great Alaska Earthquake & Tsunami, March 28, 1964

NOAAPMEL

U.S. Geological Survey (USGS)

'Smoking Gun' Reveals How the Inflationary Big Bang Happened

VideoFromSpace

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Metodologia para el analisis del riesgo petrolero [Sector Guanabo-Seboruco/ Cuba]

JULIO ERNESTO GÓMEZ HERRERA y OSVALDO RODRÍGUEZ MORÁN

Revista Cubana de Ingeniería, 2014

RESUMEN

Por más de 10 años, en la organización petrolera CEINPET se han realizado evaluaciones de riesgo y de reservas para la exploración; sin embargo, no han estado a la altura de la compleja problemática de la geología del país. En el presente trabajo se estudiaron diversos procedimientos de evaluación, más antiguos y recientes, y se confeccionó una nueva metodología para evaluar los sistemas petroleros, plays, prospectos y leads, mediante novedosas formalizaciones de los factores de control geológico (roca madre, migración, reservorio, trampa, sincronía, sello, preservación y recuperación). Se elaboraron conceptos para medir el grado del riesgo

geológico en la exploración petrolera y cuantifi car el potencial gasopetrolífero de los recursos recuperables utilizando la simulación de Monte Carlo. Se creó una estrategia de trabajo que utiliza herramientas de análisis de decisión multicriterio, componentes de lógica difusa, algoritmos de sistemas de expertos y simulación probabilística. Se instrumentó un sistema automatizado de cálculo para ayudar al experto a procesar la información y proporcionarle elementos para la toma de decisiones, con mayor rigor científico en los criterios geológicos y económicos. Con la utilización de algoritmos de incertidumbre se logró combinar más de 20

atributos, lo que facilitó evaluar factores de control geológico, imposibles de calcular anteriormente. La representación espacial y georeferenciada de los mapas de play y bases de datos asociadas fueron implementadas en Sistemas de Información Geográficos

(SIG). Esta metodología se validó en el Sistema Petrolero Grupo Veloz, en el play de carbonatos de aguas profundas, UTE Placetas y

Camajuaní, en el prospecto Guanabo. 

Informe completo aqui >>

Giant Virus Resurrected From Siberian Permafrost After 30,000 Years

NBC News.com

 

 Julia Bartoli, Chantal Abergel / IGS / CNRS-AMU

An enhanced transmission electron microscope image shows an ultra-thin section of a Pithovirus particle in an infected Acanthamoeba castellanii cell. Researchers say the virus particle is 1.5 micrometers in length.

A mysterious giant virus buried for 30,000 years in Siberian permafrost has been resurrected.

The virus only infects single-celled organisms and doesn't closely resemble any known pathogens that harm humans.

Even so, the new discovery raises the possibility that as the climate warms and exploration expands in long-untouched regions of Siberia, humans could release ancient or eradicated viruses. These could include Neanderthal viruses or even smallpox viruses that have lain dormant in the ice for thousands of years.

"If they have been extinct for a long time, then our immune system is no longer prepared to respond to them." study co-author Jean-Michel Claverie, a bioinformatics researcher at Aix-Marseille University in France, wrote in an email.

In recent years, Claverie and his colleagues have discovered a host of giant viruses, which are as big as bacteria but lack characteristic cellular machinery and metabolism of those microorganisms. [Tiny Grandeur: Stunning Images of the Very Small]

In the researchers' hunt for more unknown pathogens, they took a second look at permafrost samples collected from Kolyma in the Russian Far East in 2000. Because the permafrost was layered along steep cliffs, drillers could extract samples from 30,000 years ago by drilling horizontally into the ice, thereby avoiding contamination from newer samples.

The team then took samples of this permafrost and put them in contact with amoebas (blob-like single-celled organisms) in Petri dishes. The researchers then waited to see what happened.

Some of the amoebas burst open and died. When the scientists investigated further, they found a virus had killed the amoebas. This pathogen belongs to a previously unknown family of viruses, now dubbed Pithovirus. It infects only amoebas, not humans or other animals.

The findings were published Monday in the Proceedings of the National Academy of Sciences.

— Tia Ghose, LiveScience

Bodily maps of emotions

Bodily topography of basic (Upper) and nonbasic (Lower) emotions associated with words. The body maps show regions whose activation increased (warm colors) or decreased (cool colors) when feeling each emotion. (Credit: Lauri Nummenmaa et al./PNAS)

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Este gráfico te dice a qué velocidad te estás moviendo debido a la rotación de la Tierra

microsiervos

Vizual Statistix / Seth Kadish.

Dependiendo de en qué parte del planeta se encuentre uno el movimiento circular debido a la rotación de la Tierra sobre su eje es mayor o menor. En el ecuador esta velocidad es de unos 1600 km/h y en cambio cerca de en los polos la velocidad del movimiento circular se reduce y llega a ser cero, ninguno. Aquí en España estamos girando a unos 1300 km/h según este gráfico de Vizual Statistix.

Lo anterior sin contar la velocidad con la que la Tierra se mueve alrededor del Sol ni la velocidad con la que el Sol se desplaza por el espacio.

# Enlace Permanente

The Great Escape: Health, Wealth, and the Origins of Inequality

catoinstitutevideo

Why we find things beautiful

The Economist

Growing human brain tissue: The organoid without a face

The Economist

How Supercomputers Will Yield a Golden Age of Materials Science

By Gerbrand Ceder and Kristin Persson

In 1878 Thomas Edison set out to reinvent electric lighting. To develop small bulbs suitable for indoor use, he had to find a long-lasting, low-heat, low-power lighting element. Guided largely by intuition, he set about testing thousands of carbonaceous materials—boxwood, coconut shell, hairs cut from his laboratory assistant's beard. After 14 months, he patented a bulb using a filament made of carbonized cotton thread. The press heralded it as the “Great Inventor's Triumph in Electric Illumination.” Yet there were better filament materials. At the turn of the century, another American inventor perfected the tungsten filament, which we still use in incandescent lightbulbs today. Edison's cotton thread became history.

Materials science, the process of engineering matter into new and useful forms, has come a long way since the days of Edison. Quantum mechanics has given scientists a deep understanding of the behavior of matter and, consequently, a greater ability to guide investigation with theory rather than guesswork. Materials development remains a painstakingly long and costly process, however. Companies invest billions designing novel materials, but successes are few and far between. Researchers think of new ideas based on intuition and experience; synthesizing and testing those ideas involve a tremendous amount of trial and error. It can take months to evaluate a single new material, and most often the outcome is negative. As our Massachusetts Institute of Technology colleague Thomas Eagar has found, it takes an average of 15 to 20 years for even a successful material to move from lab testing to commercial application. When Sony announced the commercialization of the lithium-ion battery in 1991, for example, it seemed like a sudden, huge advance—but in fact, it took hundreds or thousands of battery researchers nearly two decades of stumbling, halting progress to get to that point.

More at Scientific American >>

Evolution of an Individual's Cancer Can Be Tracked Cell by Cell

Quanta (Find original story here).

Tumor Cells: Cells from the same tumor have different genetic profiles: green are normal, red cells have copies of two other cancer genes and yellow have three copies of a cancer-linked gene. Image: Navin et al. Genome Research 2010

From Quanta (Find original story here).

In August, when a group of physicians writing in the Journal of the American Medical Association proposed that some precancerous conditions should no longer be labeled as cancer, the recommendation was supported by studies showing that advances in the detection of these conditions haven’t reduced the incidence of invasive cancers. Indeed, precancerous conditions such as ductal carcinoma in situ — abnormal cells in part of the breast that have not spread — can progress to cancer but often don’t, raising questions about how aggressively to treat them. The larger issue is that physicians don’t yet have a reliable way to distinguish precancerous cases that will remain harmless from those that will become invasive.

Keep reading on Scientific American >>

How Climate Change and Plate Tectonics Shaped Human Evolution

By Mark Maslin and The Conversation

It should not be a surprise that East Africa was a hotbed of evolution, because over the last five million years everything about the landscape has changed.

The extraordinary forces of plate tectonics and a changing climate have transformed East Africa from a relatively flat, forested region to a mountainous fragmented landscape dominated by the rapid appearance and disappearance of huge, deep-water lakes. And from this highly variable landscape emerged an ape smart enough to question its own existence.

A cradle rocked by tectonics
Twenty million years ago the Indian and Asian continental plates clashed and pushed up the massive Tibetan plateau. In summer this plateau acts as a huge heat engine, absorbing solar energy which it transfers to the atmosphere, causing immense convection currents. With all this hot air rising, air is sucked in from all round, including moist air from the Indian Ocean that produces intense South East Asian monsoons.

This has a knock on affect of drawing moisture away from the African continent, and it was this that began the progressive drying out of East Africa. In terms of human evolution, this distinct split between the climate of Asia and Africa coincides with the split between Asian and African apes, the latter eventually evolving into us.

At the same time as the peaks of Tibet were thrusting upwards, the rifting process began in Ethiopia and gradually moved south finishing in Mozambique about one million years ago. This rifting was caused by a hotspot of magma under northern East Africa heating the crust causing it to split down the middle like an overdone apple pie.

The rifting process produced a deep, wide, hanging valley half a mile above sea level with uplifted shoulders or mountain ranges on either side rising up to two miles high. The affects of the Rift Valley formation on the local climate was dramatic.

Keep reading on scientificamerican >>

Scientists Confirm World's Oldest Creature...But Kill it Determining Its Age

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What is Optimal Health? Complexity Science, Chaos Theory and Ancestral - Grayson Wheatley

AncestryFoundation

 

Understanding Society: Structural realism and social realities?

Understanding Society

Daniel Little

understandingsociety.blogspot.com

The topic of realism has come up frequently here -- causal realism, critical realism, scientific realism. Each of these realisms comes out of somewhat different fields of questions and assumptions. Within mainstream philosophy of science there is another realism that has been debated in the past twenty years, referred to as structural realism. The view has been developed by philosopher John Worrall, and his 1989 article "Structural Realism: The Best of Both Worlds?", sets the stage (link). So what is this view, and does it have any relevance to the social sciences?

First, what is the view? It is a refinement to the theory of scientific realism advocated by philosophers like Hilary Putnam and Dick Boyd -- the view that we have reason to believe that the world has approximately the features attributed to it by the best available scientific theories. As Boyd put the view quite a few years ago, what else could explain the success of those theories if not their approximate truth and successful reference to the entities and properties of the world?

The problem that gives rise to structural realism is what Worrall calls the "pessimistic meta-induction" (109): in the history of science, most scientific theories have eventually been proven to be false. So how can scientific realists claim, after all, that there is a rational basis for believing that the world has the characteristics asserted by the current generation of scientific theories?  The answer to this question, Worrall argues, comes down to a judgment call about the history of science: "just how radical theory-change has standardly been in science" (105). If successor theories have nothing in common with their antecedents except a broader but overlapping range of empirical consequences, then it is hard to say that there is an approximate truth that is captured by both stages of the theory. "If, on the contrary, the realist is forced to concede that there has been radical change at the theoretical level in the history of even the mature sciences then he surely is in deep trouble" (107). Realism, then, depends on some degree of approximate continuity across successor theories. Here Worrall turns to Richard Boyd:

"The historical progress of the mature sciences is largely a matter of successively more accurate approximations to the truth about both observable and unobservable phenomena. Later theories typically build upon the (observational and theoretical) knowledge embodied in previous theories." (Boyd, 1984, "The Current Status of Scientific Realism" in Leplin, ed., Scientific Realism)

But many philosophers and historians of science have disputed the degree of continuity that Boyd postulates here. They emphasize the discontinuities that often occur across the process of theory change in physics. However, Worrall argues that there is a more abstract way in which physical theories show substantial continuity. This continuity isn't found at the level of entities and causal powers, but rather a set of more abstract characteristics that are attributed to the features of the world under study.

Structural realism gets going, then, if we concede that the history of physics shows radical change at the level of the properties attributed to natural objects but we maintain that it also shows a strong degree of continuity when it comes to the basic structural properties that are postulated by theories of physics.

In application to the series of theories offered to explain the behavior of light, the continuity was abstract:

There was continuity or accumulation in the shift [from Fresnel to Maxwell], but the continuity is one of form or structure, not of content. (117)

Worrall attributes this idea about a specific but abstract kind of continuity in physics to Henri Poincare, and he argues that it lays the basis for a weaker form of realism that might be described as syntactic or structural realism(117).

Roughly speaking, it seems right to say that Fresnel completely misidentified the nature of light, but nonetheless it is no miracle that his theory enjoyed the empirical predictive success that it did; it is no miracle because Fresnel's theory, as science later saw it, attributed to light the right structure.... There is no elastic solid ether. There is, however, from the later point of view, a (disembodied) electromagnetic field. The field in no clear sense approximates the ether, but disturbances in it do obey formally similar laws to those obeyed by elastic disturbances in a mechanical medium.  (117-118)

So structural realism when applied to the history of the theory of light says two things: successor theories had radically different and inconsistent hypotheses about the mechanics and substance of light; but they agreed approximately about the mathematical properties of light. And it is the latter that is preserved across the progress of this area of science.

This is a very weak form of realism, as Worrall acknowledges:

[The structural realist] insists that it is a mistake to think that we can ever "understand" the nature of the basic furniture of the universe.... On the structural realist view what Newton really discovered are the relationships between phenomena expressed in the mathematical equations of his theory, the theoretical terms of which should be understood as genuine primitives. (122)

So the commonsensical questions we might want to ask of contemporary physics -- are there electrons, is space curved, is the speed of light constant -- do not have defensible answers, according to structural realism. What the success of modern physics allows us to conclude is something much weaker: whatever the fundamental components of matter, space, time, light, and gravity are, the world conforms to the mathematical transformations that are specified by our best confirmed contemporary physical theories. It is the transformations, equations, and constants that we can be realistic about, not the concrete theories of the mechanics of the things that embody these equations.

My real interest in opening this topic was to consider whether it has any relevance to the social sciences. And the short answer seems to be -- not much. Theories in the social sciences rarely have the mathematical specificity that is crucial to the structural realist argument. So it is difficult to make the argument that Ricardo, Marx, Pareto, and Keynes were describing the same structural reality when they wrote about capitalism. Their substantive assumptions are quite different; but further, the expected "mathematical" behavior of the capitalist market system is also substantially different across the theories. Perhaps a more plausible case is the transition from Marx's classic theory of exploitation, based on the labor theory of value, to John Roemer's theory of exploitation in A General Theory of Exploitation and Class, based on neoclassical and game-theoretic economic assumptions. The two theories arrive at similar "structural" features of a capitalist economy, in spite of the fact that the underlying substantive assumptions are quite different.

(Katherine Brading and Elise Crull offer a very nice treatment of Worrall's interpretation of Poincare in "Epistemic Structural Realism and Poincare's Philosophy of Science (link).)

Babbage: What is Google up to?

The Economist

Tendencias emergentes. Economía Long Tail

Jose Monzo Marco
La popularización del término estadístico “long tail distribution” [distribuciones de “larga cola”] se debe principalmente a Chris Anderson, editor jefe de la revista Wired, que escribió un artículo sobre este interesante fenómeno asociado a Internet allá por el mes de octubre de 2004 y del que en 2006 se publicó el libro en inglés [el libro está publicado en castellano con el título “La Economía Long Tail” por la editorial Tendencias] convirtiéndose rápidamente en un éxito de ventas mundial.

El fenómeno de la “larga cola” se puede interpretar como una tendencia emergente por la que gracias a la tecnología de Internet el mercado de masas [donde la distribución de Pareto del 80/20 –el 80% de las ventas lo produce el 20% de las referencias- se cumple casi siempre: sólo unos pocos productos producen la mayor parte de los resultados] se está convirtiendo en un mercado de nichos: por primera vez en la sociedad de consumo, la venta de pequeñas cantidades es rentable.

La explicación del autor es bastante convincente: en un mercado marcado por la escasez de medios para exponer los productos [la metáfora del espacio de exposición de una tienda física es perfecta] es lógico que unos pocos productos alcancen el éxito [la limitación física de los escaparates en las tiendas o en los grandes almacenes actúa de filtro, al igual que el espacio publicitario destinado en los medios de comunicación] pero cuando el espacio de exposición es virtualmente infinito [tiendas virtuales en Internet] entonces la “larga cola” de productos que se extiende detrás de los éxitos es virtualmente infinita, como podemos observar en el gráfico.

Este fenómeno del Long Tail no implica necesariamente que con las tiendas virtuales desaparezca totalmente la típica distribución de Pareto, pero sí ejemplifica que la curva puede llegar a tener una distribución algo más parecida a una proporción 50/20 –el 50% de las ventas los produce el 20% de las referencias, lo que significa que el restante 80% de referencias produce el otro 50% de resultados-, o algo más plana en ambos lados, del orden de una proporción 20/20 –el 20% de las ventas lo produce el 20% de las referencias- lo que en la práctica algunos interpretan como el fin de la distribución continua de Pareto [1] [o de su equivalente discreto en la distribución de Zipf [2] o regla del rango-tamaño], lo que no es totalmente cierto porque en el mundo real o en el virtual siempre se venderán mucho más unas cosas que otras, pero, eso sí, “La Economía Long Tail” viene a recordarnos que ese 80% de referencias que aparentemente podríamos desechar en un entorno económico pre-Internet, en la economía virtual van a tener una importancia estratégica por la emergencia de mercados de nicho que van a nutrir y alargar la cola de productos, es decir con la tienda virtual seguirán habiendo productos “best-sellers”, sin duda, pero es muy posible que su cifra de ventas sea prácticamente igual al resto de productos que dejan tras de sí. Esa es la “La Economía Long Tail” que nos espera.

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¿Cuánto tiempo dura algo?. De la inecuación de Gott al efecto Lindy

Jose Monzo Marco

El III Reich decía de sí mismo que iba a gobernar Alemania durante 1.000 años... apenas duró 12 años (1933-1945). El partido de la UCD en España decía de sí mismo que iba a gobernar durante 100 años... apenas duró 5 años (1977-1982). Al parecer los humanos somos muy buenos calculando la esperanza de vida de una persona en base a su sexo y edad mediante las tablas actuariales, pero un poco torpes para estimar la duración de otras cosas. ¿O no?.

Inecuación de Gott

Cuando el matemático y astrofísico John Richard Gott se encontraba ante el Muro de Berlín en 1969, intentó estimar la duración probable del Muro basándose en un solo dato, el tiempo transcurrido hasta ese momento, 8 años (1961-1969) y en base al principio atribuido a Copérnico (los humanos no somos observadores privilegiados del universo), re-elaborado posteriormente como “principio de mediocridad” que viene a decir que cualquier cosa seleccionada al azar que observemos en un momento determinado no estará ni al comienzo ni al final de su vida: lo más probable es que esté en algún punto alrededor de la mitad de su vida. Armado con esta presunción y un mínimo aparataje matemático, Gott se atrevió a calcular que con una fiabilidad del 50%, al Muro de Berlín le quedasen (en 1969) menos de 24 años de existencia (exactamente entre 2,67 y 24 años adicionales). Como ustedes saben, el Muro de Berlín fue derribado en 1989, es decir, veinte años después de la profecía matemática de Gott.

No obstante y tras este éxito, su argumento fue tildado de incompleto, así que lo volvió a someter a contraste empírico. En concreto, Gott elaboró una lista de los 44 espectáculos que había en la cartelera de Broadway un día determinado, el 17 de Mayo de 1993, y predijo que los que llevaban más tiempo en representándose serían los que durarían más tiempo en cartel, y viceversa. Su predicción se demostró correcta en un 95% de los casos.

El problema al que se enfrenta este tipo de predicciones, como la propuesta por Richard Gott o como la que veremos después con el llamado efecto Lindy, desafía el sentido común, pues al común de los mortales nos podría parecer insuficiente o temerario que con apenas el conocimiento de una variable (el tiempo transcurrido) y un coeficiente nos atrevamos a realizar la estimación de la duración de casi cualquier cosa. Ni que decir tiene que el problema tiene su enjundia a un nivel fundamental, pues no pasaría de ser un divertimento matemático si no fuera porque, a mi entender, el enfoque abordado por Gott revela algo profundo sobre nuestra manera de comprender la función de probabilidad en la duración de las creaciones humanas para entrar de lleno en el campo de la metamatemática.

Gráficamente el problema de la estimación de casi cualquier cosa se podría representar de este modo:

En donde partiendo de un único dato, el tiempo transcurrido desde el inicio de algo y el tiempo presente podemos estimar el tiempo adicional o restante de ese algo.

Un cálculo ciertamente atrevido.

El enfoque de Richard Gott está basado en la aplicación de la presunción copernicana antes comentada: el momento presente de la vida de ese algo no es excepcional, es decir, no está situado ni al inicio ni al final de la vida de ese algo, un principio que proviene del ámbito de la astronomía, pero que Gott se atrevió a aplicar al ámbito de lo cotidiano. Conociendo por tanto el tiempo transcurrido sólo nos resta aplicar un coeficiente, que en el caso de la inecuación Gott se conoce como factor de fiabilidad, que podríamos entender como probabilidad de la estimación, entendiendo que a menor probabilidad más error aunque menor variabilidad (mayor precisión) y a mayor probabilidad menor error aunque mayor variabilidad (menor precisión), entendiendo por variabilidad la diferencia entre la estimación mínima y la máxima. Nota: 100 - fiabilidad = probabilidad de error.

Otra manera de entenderlo sería que cuanta menos fiabilidad correspondería un rango de solución más estrecho (F < 50%), es decir, más precisión pero más probabilidad de error y cuanta más fiabilidad correspondería un rango de solución más amplio (F > 50%), es decir menos precisión aunque menos probabilidad de error. Una recomendación al operar con la fórmula propuesta por Richard Gott es comenzar usando una probabilidad del 50% que es justo la que solía utilizar su autor.

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Douglas Hofstadter: qué es pensar

microsiervos

Hay muy poca gente interesada en cómo funciona la inteligencia humana. Por eso es en lo que yo estoy interesado: en qué es pensar.

– Douglas Hofstadter

En The Atlantic han publicado un largo perfil sobre uno de nuestros autores favoritos: Douglas Hofstadter, titulado The Man Who Would Teach Machines to Think. Hofstadter es el autor de esa mítica obra titulada Gödel, Escher, Bach: un Eterno y Grácil Bucle con la que ganó el premio Pulitzer. Es un tío con dos bemoles capaz de debatir con Ray Kurzweil acusándole de ser un magufo. Y por si fuera poco el apellido de Leonard Hofstadter el de The Big Bang Theory es un homenaje a él. ¿Puede haber algo más honorablemente geek?

{Foto: Doug Hofstadter presentation (CC) Null0 @ Flickr}

Companies rush to build ‘biofactories’ for medicines, flavorings and fuels

By Ariana Eunjung Cha

For scientist Jack Newman, creating a new life-form has become as simple as this: He types out a DNA sequence on his laptop. Clicks “send.” And a few yards away in the laboratory, robotic arms mix together some compounds to produce the desired cells.
Newman’s biotech company is creating new organisms, most forms of genetically modified yeast, at the dizzying rate of more than 1,500 a day. Some convert sugar into medicines. Others create moisturizers that can be used in cosmetics. And still others make biofuel, a renewable energy source usually made from corn.

Keep reading on The Washington Post >>