Thursday, June 9, 2011
Wednesday, June 8, 2011
Roaming Rocks of Death Valley by Will Hunt
NASA/GSFC/Cynthia CheungLarge boulders like this one wander across the flat clay surface of Racetrack Playa, a dry lake bed in Death Valley National Park in California, leaving long furrows but no hint of what propelled them. Last summer, NASA’s Cynthia Cheung may have discovered their secret: The rocks, some weighing several hundred pounds, probably glide on collars of ice that form around their base. When rain or snowmelt wets the valley, the collars act as flotation devices, Cheung says. The boulders then slide so easily that high winds can send them scooting, improbably and beautifully, across the slick surface.
The Priest-Physicist Who Would Marry Science to Religion
John Polkinghorne leads a disparate group of scientists the
controversial search
for God
within
the
fractured
logic
of
quantum physics.
Image of the Carina Nebula courtesy of NASA, ESA, and the Hubble Heritage Team (STScI/AURA)When he describes his line of work, John Polkinghorne jests, he encounters “more suspicion than a vegetarian butcher.” For the particle physicist turned Anglican priest, dissonance comes with the territory. Science parses the concrete: the structure of the atom and the workings of the brain. Religion confronts the intangible: questions about ethics and the purpose of life. Taken literally, the biblical story of Genesis contradicts modern cosmology and evolutionary biology in full.
Yet 21 years ago, in a move that made many eyes roll, Polkinghorne began working to unite the two sides by seeking a mechanism that would explain how God might act in the physical world. Now that work has met its day of reckoning. At a series of meetings at Oxford University last July and September, timed to celebrate Polkinghorne’s 80th birthday, physicists and theologians presented their answers to the questions he has so relentlessly pursued. Do any physical theories allow room for God to influence human actions and events? And, more controversially, is there any concrete evidence of God’s hand at work in the physical world?
Lightning Unleashes Antimatter Storms
You don't have to go all the way to supernovas to find natural events powerful enough to generate gamma rays...
Some high-powered lightning strikes produce unusual forms of matter.iStockphoto
the powerful blasts of particles and light energy known as gamma-ray bursts come from violent cosmic events in deep space, such as stellar explosions and black hole collisions. But smaller-scale bursts called terrestrial gamma-ray flashes (TGFs) can occur much closer to home, erupting thousands of times a year in association with lightning strikes during storms in Earth’s atmosphere. Two satellites originally designed to observe gamma rays from space recently caught the atmospheric flares in action, revealing that they emit far more energy than previously thought and release streams of antimatter particles, which bear a charge opposite that of their normal counterparts.
In a study of 130 TGFs recorded by
the AGILE satellite, Italian Space Agency physicist Marco Tavani and colleagues report that the most energetic particles released carry four times as much energy as previous measurements detected, and hundreds of times as much as those produced by normal lightning strikes. In fact, Tavani describes a storm hurling photons into AGILE’s detectors as basically a giant particle accelerator in the sky. “It’s the equivalent of the Large Hadron Collider acting in the atmosphere for a fraction of a second,” he says. Next, Tavani plans to evaluate how TGFs might affect aircraft flying nearby.
Researchers working on another mission, NASA’s Fermi Gamma-ray Space Telescope, announced in January that about 10 percent of the particles fired off by TGFs consist of positrons—the positively charged antimatter twins of electrons. Because gamma rays can convert into electrons and positrons, physicists had predicted the antiparticles’ presence in the bursts, but until now they had never been directly observed. Astrophysicist Michael Briggs, a Fermi team member based at the University of Alabama in Huntsville, hopes such findings will aid in modeling how TGFs form. Currently, he says, scientists do not understand why some lightning strikes produce such mayhem while others do not.
If Modern Humans Are So Smart, Why Are Our Brains Shrinking?
John Hawks is in the middle of explaining his research on human evolution when he drops a bombshell. Running down a list of changes that have occurred in our skeleton and skull since the Stone Age, the University of Wisconsin anthropologist nonchalantly adds, “And it’s also clear the brain has been shrinking.”
“Shrinking?” I ask. “I thought it was getting larger.” The whole ascent-of-man thing.
“That was true for 2 million years of our evolution,” Hawks says. “But there has been a reversal.”
He rattles off some dismaying numbers: Over the past 20,000 years, the average volume of the human male brain has decreased from 1,500 cubic centimeters to 1,350 cc, losing a chunk the size of a tennis ball. The female brain has shrunk by about the same proportion. “I’d call that major downsizing in an evolutionary eyeblink,” he says. “This happened in China, Europe, Africa—everywhere we look.” If our brain keeps dwindling at that rate over the next 20,000 years, it will start to approach the size of that found in Homo erectus, a relative that lived half a million years ago and had a brain volume of only 1,100 cc. Possibly owing to said shrinkage, it takes me a while to catch on. “Are you saying we’re getting dumber?” I ask.
When Astronomy Met Computer Science
Contrasting views of the Lagoon nebula. Top: Infrared observations from the Paranal Observatory in Chile cut through dust and gas to reveal a crisp view of baby stars within. Bottom: A similar view in visible light appears opaque. ESO, VVV
For Kirk Borne, the information revolution began 11 years ago while he was working at NASA’s National Space Science Data Center in Greenbelt, Maryland. At a conference, another astronomer asked him if the center could archive a terabyte of data that had been collected from the MACHO sky survey, a project designed to study mysterious cosmic bodies that emit very little light or other radiation. Nowadays, plenty of desktop computers can store a terabyte on a hard drive. But when Borne ran the request up the flagpole, his boss almost choked. “That’s impossible!” he told Borne. “Don’t you realize that the entire data set NASA has collected over the past 45 years is one terabyte?”
“That’s when the lightbulb went off,” says Borne, who is now an associate professor of computational and data sciences at George Mason University. “That single experiment had produced as much data as the previous 15,000 experiments. I realized then that we needed to do something not only to make all that data available to scientists but also to enable scientific discovery from all that information.”
The tools of astronomy have changed drastically over just the past generation, and our picture of the universe has changed with them. Gone are the days of photographic plates that recorded the sky snapshot by painstaking snapshot. Today more than a dozen observatories on Earth and in space let researchers eyeball vast swaths of the universe in multiple wavelengths, from radio waves to gamma rays. And with the advent of digital detectors, computers have replaced darkrooms. These new capabilities provide a much more meaningful way to understand our place in the cosmos, but they have also unleashed a baffling torrent of data. Amazing discoveries might be in sight, yet hidden within all the information.
For the first time in history, we cannot examine all our data,” says Caltech astronomer George Djorgovski. “It’s not just the volume of data. It’s also the quality and complexity.”
A new generation of sky surveys promises to catalog literally billions and billions of astronomical objects. Trouble is, there are not enough graduate students in the known universe to classify all of them. When the Large Synoptic Survey Telescope (LSST) in Cerro Pachón, Chile, aims its 3.2-
billion-pixel digital camera (the world’s largest) at the night sky in 2019, it will capture an area 49 times as large as the moon in each 15-second exposure, 2,000 times a night. Those snapshots will be stitched together over a decade to eventually form a motion picture of half the visible sky. The LSST, producing 30 terabytes of data nightly, will become the centerpiece of what some experts have dubbed the age of petascale astronomy—that’s 1015 bits (what Borne jokingly calls “a tonabytes”).
The data deluge is already overwhelming astronomers, who in the past endured fierce competition to get just a little observing time at a major observatory. “For the first time in history, we cannot examine all our data,” saysGeorge Djorgovski, an astronomy professor and codirector of the Center for Advanced Computing Research at Caltech. “It’s not just data volume. It’s also the quality and complexity. A major sky survey might detect millions or even billions of objects, and for each object we might measure thousands of attributes in a thousand dimensions. You can get a data-mining package off the shelf, but if you want to deal with a billion data vectors in a thousand dimensions, you’re out of luck even if you own the world’s biggest supercomputer. The challenge is to develop a new scientific methodology for the 21st century.”
Why rice is so nice
The Pith: What makes rice nice in one varietal may not make it nice in another. Genetically, that is….
Rice is edible and has high yields thanks to evolution. Specifically, the artificial selection processes which lead to domestication. The “genetically modified organisms” of yore! The details of this process have long been of interest to agricultural scientists because of possible implications for the production of the major crop which feeds the world. And just as much of Charles Darwin’s original insights derived from his detailed knowledge of breeding of domesticates in Victorian England, so evolutionary biologists can learn something about the general process through the repeated instantiations which occurred during domestication during the Neolithic era.
A new paper in PLoS ONE puts the spotlight on the domestication of rice, and specifically the connection between particular traits which are the hallmark of domestication and regions of the genome on chromosome 3. These are obviously two different domains, the study and analysis of the variety of traits across rice strains, and the patterns in the genome of an organism. But they are nicely spanned by classical genetic techniques such as linkage mapping which can adduce regions of the genome of possible interesting in controlling variations in the phenotype.
In this paper the authors used the guidelines of the older techniques to fix upon regions which might warrant further investigation, and then applied the new genomic techniques. Today we can now gain a more detailed sequence level picture of the genetic substrate which was only perceived at a remove in the past through abstractions such as the ‘genetic map.’ Levels and Patterns of Nucleotide Variation in Domestication QTL Regions on Rice Chromosome 3 Suggest Lineage-Specific Selection:
Oryza sativa or Asian cultivated rice is one of the major cereal grass species domesticated for human food use during the Neolithic. Domestication of this species from the wild grass Oryza rufipogon was accompanied by changes in several traits, including seed shattering, percent seed set, tillering, grain weight, and flowering time. Quantitative trait locus (QTL) mapping has identified three genomic regions in chromosome 3 that appear to be associated with these traits. We would like to study whether these regions show signatures of selection and whether the same genetic basis underlies the domestication of different rice varieties. Fragments of 88 genes spanning these three genomic regions were sequenced from multiple accessions of two major varietal groups in O. sativa—indica and tropical japonica—as well as the ancestral wild rice species O. rufipogon. In tropical japonica, the levels of nucleotide variation in these three QTL regions are significantly lower compared to genome-wide levels, and coalescent simulations based on a complex demographic model of rice domestication indicate that these patterns are consistent with selection. In contrast, there is no significant reduction in nucleotide diversity in the homologous regions in indica rice. These results suggest that there are differences in the genetic and selective basis for domestication between these two Asian rice varietal groups.
Here’s what seems relevant for the two domestic varieties from Wikipedia:
Oryza sativa contains two major subspecies: the sticky, short grained japonicaor sinica variety, and the non-sticky, long-grained indica variety. Japonica are usually cultivated in dry fields, in temperate East Asia, upland areas of Southeast Asia and high elevations in South Asia, while indica are mainly lowland rices, grown mostly submerged, throughout tropical Asia….
There’s long been debate about the exact phylogenetic relationship between these two strains of domestic rice. More on that later. In regards to domestication there are three categories we need to focus on in terms of adaptation: 1) traits which are common to all domestic cereals and tend to crop up almost immediately, 2) traits which are extensions and improvements upon the initial domestic prototype, 3) traits which are regional diversifications, often adaptations to climate. Consider an analogy to horses. The original domestic horse was rather small, and was only fit for drawing chariots. Eventually the breeds became larger, and suitable for cavalry. Finally, there was a diversification by task (e.g., workhorses vs. race horses) and to some extent climate.
As noted above previous classical genetic techniques had narrowed down the genetic regions responsible for various domesticate traits when comparing japonica to the wild rufipogon. Since domestication usually entails a process of selection the authors naturally presumed that they might be able to detect signatures of selection within the genome. What are the genomic tells of selection?
There are many, just as there are different types of selection. In this case what we know suggests that due to #1 there’s going to be an initial bout of adaptation and rapid shift from wild diversity to fixed traits suitable for a crop which is going to be controlled by humans. Just as the riotous diversity of the wild varieties become constrained to monocultures, so the diversity of the wild type often gets swept away by a few genetic variants which are responsible for the favored traits. So what they might see in the domestic varieties is a sharp reduction of variation around the quantitative trait loci (QTLs) reported earlier, because those QTLs have presumably been the target of selection. In other words, a selective sweep.
That’s what they found. At least in one lineage.
Left to right you have indica, japonica, and rufipogon. Front to back in each chart you see the three QTLs, and the distribution of nucleotide diversities by genetic fragments within these QTLs. The extremely skewed distribution of the domestic varieties in relation to the wild type rufipogonis rather obvious. Additionally, you see a stronger skew in japonica in relation to indica. The skew in the domestic strains is toward a greater proportion of the fragments having very low nucleotide diversity.
What could cause this? You need a further piece of information here. The domestic varieties have long regions of the genome characterized by linkage disequilibrium (actually, japonica is so homogeneous that you barely have enough variation to calculate LD!). So particular genetic variants are associated with each other, resulting in long runs of similar sequences, haplotypes. It’s as if a chunk of some ancient chromosome just “blew up” and took over that segment of the genome in japonica.
Natural selection could do this. Imagine that an ancestral rufipogon has a genetic variant which confers a domestic trait. It would be selected. Even if crossed with other strains with other domestic characteristics its particular QTL would be transmitted down to the descendants in general. But not only would the specific genetic variant which conferred the favored trait be passed on, but many of the flanking genomic regions carrying other variants would also be transmitted! This explains the extremely low genetic diversity in japonica, if there’s a sweep up in frequency of a particular ancestral haplotype then what were polymorphisms in the wild type become monomorphic in the domesticate.
Another explanation though could be that demographic history produced these results. Random genetic drift due to small populations, whether via bottleneck or systematic inbreeding/selfing, can also drive up the frequency of alleles favored by lady-luck and render extinct all others. To check for this the authors constructed a model where japonica and indica went through bottlenecks enforced by the domestication (note that strong selection can drive down population size as well). Even with this model the diversity in japonica in these QTLs remained far too low (though indica’s skew did not reach statistical significance).
Since both of the domestic strains exhibit traits of domestication the lack of a selective event inindica at these QTLs does not allow us to infer that there are no genes which were selected for these traits in the past in indica. On the contrary, there certainly were and are such genes. But where are they? The authors moot the possibility that selection exists at the loci under consideration, but was simply missed because the selection was by a different dynamic which might not be picked up by their test. For various reasons they are skeptical of this on its own merits, but I think the bigger issue is that the original linkage mapping was performed with japonica vs. wild type strains, so naturally if the two domestic subspecies differed in their genetic architectures then the QTLs of interest of indica would not be discovered simultaneously.
Something which I’m rather perplexed by is how this comports or aligns with the finding by many of the same researchers that the two domestic varietals derive from the same ancestral populationwhich was domesticated from East Asian wild rice. It could be that the history of domestication is more serial than we know, and that the common QTLs to both japonica and indica have been rendered irrelevant by new adaptations subsequent to their separation. Or, one or the other may have experienced introgression at that locus and so diverged after domestication. Interestingly infigure 7 of the paper they show that phylogenetic trees which illustrates the relationship of alleles associated with each strain. It indicates that indica is not monophyletic on these regions, whilejaponica is. This means that the japonica variants share a common ancestor, from which all are descended. In contrast, indica variants do not. Such a pattern is consistent with the story of strong positive selection upon a single variant at some time in the past for japonica. From what I can tell they may actually have sent the PLoS ONE paper to the reviewers before the PNAS paper which I reviewed earlier. Because these two papers were published so close to each other they don’t cite each other, though in some ways the first paper in PNAS would have fleshed out the natural history of domestic rice somewhat. As it is, they kind of leave of us hanging in relation to indica.
Why does all of this matter? Yes, agricultural genetics is important for agriculture. But let’s get back to people. There is a hypothesis that man is a ‘self-domesticated’ organism.Whatever quibbles I have with artificial terms like domestication I do think that there may be broad analogies to be drawn between our own species and the organisms associated with us.
HANDS & FEET..
Your face might get noticed first but your hands get the maximum exposure. Besides harsh sun and chaffing winds they are in direct contact with drying elements like detergents, hot water etc. the result: hands look years older than the rest of you.
Why hands age so fast?
The fragile structure of your hands makes the skin especially vulnerable to aging, but you can slow the process. The skin on the backs of your hands has few oil glands so it shrivels and chaps easily upon exposure especially around the joints. Protect skin with gloves in winters and use moisturizer and sunscreen all year round.
Why does skin on the hands sag?
Thinning bones and shrinking fat cells cause skin to sag. Keep bones strong with calcium supplements. Also moderate exercise will pump blood and it's nutrients back into hands and feet. Production of collagen and elastin- proteins that make skin supple also slows with age. Oral vitamin C protects these component.
Top hand irritants
For lovely hands always use gloves for washing clothes and utensils
Soak hands in a bowl of warm water to which 1 tsp of corn starch has been added for 5 minutes daily after finishing the house-hold chores. Massage hands once a week with olive oil and a little table salt added to it. Remove ingrained dirt from hands with a 10 minute massage of sugar' and butter. Glycerine, rose water and lemon juice rubbed on the hands every night during winter months keeps them soft and prevents ugly cracks forming. For chapped hands in winters, wash with lukewarm water (before going to bed), apply milk-cream and put on a pair of gloves; wash hands the next morning. To remove stains from hands ' rub with a slice of lemon or a raw potato. For nicotine stains, apply lemon juice and leave for 10 minutes before washing. A drop of Witch Hazel in the palms is an effective antidose for hands that perspire a lot. To keep hands clean and soft, soak 250 grams oatmeal in 11-12 cups water and leave overnight. Strain it through a thin muslin cloth the next morning and add 1 thsp lemon juice and 1 tsp each. of olive oil, rose water, glycerine and diluted ammonia. Bottle and apply on hands 3-4 times daily.
Knees, Heel and Feet
Keep knees smooth by rubbing them occasionally wit. fresh lime juice or massage with a nourishing cream.
The winter itch that cracks the skin of the heels due to excessive dryness or the use of an alkaline soap can be treated by washing the feet at night in warm water and mild soap and applying a lanolin rich cream or mixture of glycerine and rose water. Tired feet should be soaked alternately in hot and cold water. Before applying paint on your toe-nails, cut triangular shapes of sponge and place then between toes to keel them separated, and save the hassle of cleaning the skin on the toes.
waxing
Impliments:-
Two handled vessels with lids
Plastic basket like things to keep pieces of cloths.
Spatula
Towels & Napkins
Ingradients:-
-Sugar - 2 lbs
-Lime juice - 700gms
-Hydrogen peroxide - 1/2 or 1 tsp
Method of preparing wax:-
Take a vessel put lime juice and sugar(1:6) into it. Put in on low fire for 30 to 40 minutes. Stir it gently. After 20 - 25 minutes take drop of prepared wax. Put into glass of water. If it forms beads, it means your wax is ready. If you want, you can add hydrogenperoxide into the wax.
Method of removing hair with impliments:-
Heat the wax on heater or fire. Apply talcum powder to the area hair to remove. Apply wax with knife or spatula in the same direction of hair growth. Put the cloth on it and press it with the hand. Remove it in the opposite direction of hair growth. Put the hand on the area to avoid rash.
Caution:-
If there is a rash take avil tablet to avoid rash. Always do waxing after bleaching.
Procedure for Manicure at Home
|
DARK ELBOW AND KNEES
Tip 1:
Rub with limejuice, leave for10-15 minutes. Soak a towel inhotwaterand scrub firmly.
Tip 2:
Mix 1 tspn coconut oil with ½ a tspn of limejuice. Apply and wash in the same way with a hot towel.
Rub with limejuice, leave for10-15 minutes. Soak a towel inhotwaterand scrub firmly.
Tip 2:
Mix 1 tspn coconut oil with ½ a tspn of limejuice. Apply and wash in the same way with a hot towel.
Tip 1:
Soak hands and feet in water to whichcornflourhas been added. Soak for 5-10 minutes.
Soak hands and feet in water to whichcornflourhas been added. Soak for 5-10 minutes.
Rough Hands and Feet
Tip 2:
Roast an onion,mashand make a paste. Apply on cracked heels. Wash after 20 minutes.Continue for a month till the cracks heal.
Tip 3:
After a bath massage Mustard oil well into hands and feet. Wash with water and pat with a towel to dry.
Tip 4:
Add ½ tspn Vinegar to ½ a cup of curds. Massagefeetandankleswell with this Wash after 5 minutes.
Tip 5:
For cracks in heels, mix Candle wax withMustardoil. Heat and apply. Wear socks and leave overnight.
Calluses :
Crush6 Aspirin tablets in 1cup of water with 1 tspn limejuice.Coatthe calluses with this. Cover with a warm towel. After 10 minutes scrub with a pumice stone and wash.
Weekly :
Once a week in ½ a bucket of water add 2 tblspns of Vinegar and 1 tspn of limejuice. Add a gentle shampoo and soak ands and feet for 10-15 minutes.Rubwith a pumice stone and then have a bath.
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