Ultra high energy cosmic rays create a shower of particles when they encounter the Earth's atmosphere. The shower is large enough that distributed detector arrays are used to detect them. You need very large arrays and/or a lot of time to obtain a meaningful sample of events.
Greg noted an interesting approach that would use smartphones. The camera sensor can detect some types of shower particles if they happen to hit it. Of course the probability is small and you couldn't tell much from single events, but smartphones know where they are and what time it is and have a link to the Internet. There are also a lot of them. The scheme is to use them when they're idle, but plugged into a power source (so they don't drain the battery). When they detect energy being deposited in the camera sensor they send a report with the type of phone, time, place and rough amount of energy. The individual points are mapped by the experimentors who look for time and space correlated shower footprints.
A neat idea, but it would take a lot of cooperation to build a meaningful array. The problem is more social than technical in nature at this point.
Observing Ultra-High Energy Cosmic Rays with Smartphones
Daniel Whiteson,1 Michael Mulhearn,2 Chase Shimmin,1 Kyle Brodie,1 and Dustin Burns2
1Department of Physics and Astronomy, University of California, Irvine, CA 92697
2Department of Physics, University of California, Davis, CA
We propose a novel approach for observing cosmic rays at ultra-high energy (> 1018 eV) by re- purposing the existing network of smartphones as a ground detector array. Extensive air showers generated by cosmic rays produce muons and high-energy photons, which can be detected by the CMOS sensors of smartphone cameras. The small size and low efficiency of each sensor is compen- sated by the large number of active phones. We show that if user adoption targets are met, such a network will have significant observing power at the highest energies.
The source of ultra-high energy cosmic rays (UHECR), those with energy above 1018 eV, remains a puzzle even many decades after their discovery, as does the mecha- nism behind their acceleration. Their high energy leaves them less susceptible to bending by magnetic fields be- tween their source and the Earth, making them excel- lent probes of the cosmic accelerators which produce them [1, 2]. But the mechanism and location of this enor- mous acceleration is still not understood, despite many theoretical conjectures [3–6].
When incident on the Earth’s atmosphere, UHECRs produce extensive air showers, which can be detected via the particle flux on the ground, the flourescence in the air, or the radio and acoustic signatures. A series of dedicated detectors [7–9] have detected cosmic rays at successively higher energies, culminating in observation up to 3 · 1020 eV. The flux of particles drops precipitously above 1018 GeV, due to the suppression via interaction with the cosmic microwave background [10, 11], making observation of these particles challenging.
To accumulate a sufficient number of observed showers requires either a very long run or a very large area. Con- structing and maintaining a new detector array with a large effective area presents significant obstacles. Current arrays with large, highly-efficient devices (Auger , AGASA ) cannot grow dramatically larger without becoming much more expensive. Distributed detector ar- rays with small, cheaper devices (ERGO , etc) have the potential to grow very large, but have not achieved the size and density required to probe air showers, poten- tially due to the organizational obstacles of production, distribution and maintenance of their custom-built de- vices.
It has been previously shown that smartphones can de- tect ionizing radiation [15, 16]. In this paper, we demon- strate that a dense network of such devices has power sufficient to detect air showers from the highest energy cosmic rays. We measure the particle-detection efficiency of several popular smartphone models, which is necessary for the reconstruction of the energy and direction of the particle initiating the shower. With sufficient user adop- tion, such a distributed network of devices can observe UHECRs at rates at least comparable to conventional cosmic ray observatories. Finally, we describe the oper- ating principles, technical design and expected sensitivity of the CRAYFIS (Cosmic RAYs Found In Smartphones) detector array. Preliminary applications for Android and iOS platforms are available for testing .
"Our findings, for the first time, suggest that males and females respond to high-fat diets differently," said Deborah Clegg of the Cedar-Sinai Diabetes And Obesity Research Institute in Los Angeles. "The data would suggest that is probably 'ok' for females to occasionally have a high-fat meal, where it is not recommended for males.
"The way we treat patients and provide dietary and nutritional advice should be altered. We might be less concerned about an occasional hamburger for women, but for men, we might more strongly encourage avoidance, especially if they have pre-existing diseases such as heart disease or type 2 diabetes."
Earlier data from Clegg's team and others had suggested that inflammation in the brain is tied to overeating, blood sugar imbalances, and increased inflammation in other parts of the body, including fat tissue. Those effects can be triggered, in males in particular, by short-term exposure to a high-fat diet.
The researchers say they were initially shocked to discover that male and female brains differ in their fatty acid composition. When they manipulated male mouse brains to have the fatty acid profile of females, they found that those animals were protected from the ill effects of a diet high in fat.
When males with average male brains entered an inflammatory state after eating diets high in fat, they also suffered from reduced cardiac function in a way that female animals in the study did not. Those sex differences in the brain's response to fat are related to differences between females and males in estrogen and estrogen receptor status.
Now, a team of biologists at Ruhr University Bochum in Germany has found that our skin is bristling with olfactory receptors. “More than 15 of the olfactory receptors that exist in the nose are also found in human skin cells,” said the lead researcher, Dr. Hanns Hatt. Not only that, but exposing one of these receptors (colorfully named OR2AT4) to a synthetic sandalwood odor known as Sandalore sets off a cascade of molecular signals that appears to induce healing in injured tissue.
In a series of human tests, skin abrasions healed 30 percent faster in the presence of Sandalore, a finding the scientists think could lead to cosmetic products for aging skin and to new treatments to promote recovery after physical trauma.
The presence of scent receptors outside the nose may seem odd at first, but as Dr. Hatt and others have observed, odor receptors are among the most evolutionarily ancient chemical sensors in the body, capable of detecting a multitude of compounds, not solely those drifting through the air.
“If you think of olfactory receptors as specialized chemical detectors, instead of as receptors in your nose that detect smell, then it makes a lot of sense for them to be in other places,” said Jennifer Pluznick, an assistant professor of physiology at Johns Hopkins University
the paper appears in Nature for those with access..
High winter ozone pollution from carbonyl photolysis in an oil and gas basin
Peter M. Edwards, Steven S. Brown, James M. Roberts, Ravan Ahmadov, Robert M. Banta, Joost A. deGouw, William P. Dubé, Robert A. Field, James H. Flynn, Jessica B. Gilman, Martin Graus, Detlev Helmig, Abigail Koss, Andrew O. Langford, Barry L. Lefer, Brian M. Lerner, Rui Li, Shao-Meng Li, Stuart A. McKeen, Shane M. Murphy, David D. Parrish, Christoph J. Senff, Jeffrey Soltis, Jochen Stutz, Colm Sweeney et al.
The United States is now experiencing the most rapid expansion in oil and gas production in four decades, owing in large part to implementation of new extraction technologies such as horizontal drilling combined with hydraulic fracturing. The environmental impacts of this development, from its effect on water quality1 to the influence of increased methane leakage on climate2, have been a matter of intense debate. Air quality impacts are associated with emissions of nitrogen oxides3, 4(NOx = NO + NO2) and volatile organic compounds5, 6, 7 (VOCs), whose photochemistry leads to production of ozone, a secondary pollutant with negative health effects8. Recent observations in oil- and gas-producing basins in the western United States have identified ozone mixing ratios well in excess of present air quality standards, but only during winter9, 10, 11, 12, 13. Understanding winter ozone production in these regions is scientifically challenging. It occurs during cold periods of snow cover when meteorological inversions concentrate air pollutants from oil and gas activities, but when solar irradiance and absolute humidity, which are both required to initiate conventional photochemistry essential for ozone production, are at a minimum. Here, using data from a remote location in the oil and gas basin of northeastern Utah and a box model, we provide a quantitative assessment of the photochemistry that leads to these extreme winter ozone pollution events, and identify key factors that control ozone production in this unique environment. We find that ozone production occurs at lower NOx and much larger VOC concentrations than does its summertime urban counterpart, leading to carbonyl (oxygenated VOCs with a C = O moiety) photolysis as a dominant oxidant source. Extreme VOC concentrations optimize the ozone production efficiency of NOx. There is considerable potential for global growth in oil and gas extraction from shale. This analysis could help inform strategies to monitor and mitigate air quality impacts and provide broader insight into the response of winter ozone to primary pollutants.
Recently Nature published a comment by Victor and Kennel on getting rid of the 2°C goal. Their argument is poorly thought out, but it has inspired some debate and, of course, the denialist community has been piling on about unsettled science and is suggesting tabling action.
“The need for sameness is one of the most uniform characteristics of autism,” Sinha says. “It’s a short step away from that description to think that the need for sameness is another way of saying that the child with autism needs a very predictable setting.”
Most people can routinely estimate the probabilities of certain events, such as other people’s likely behavior, or the trajectory of a ball in flight. The MIT team began to think that autistic children may not have the same computational abilities when it comes to prediction.
This hypothesized deficit could produce several of the most common autism symptoms. For example, repetitive behaviors and insistence on rigid structure have been shown to soothe anxiety produced by unpredictability, even in individuals without autism.
“These may be proactive attempts on the part of the person to try to impose some structure on an environment that otherwise seems chaotic,” Sinha says.
Impaired prediction skills would also help to explain why autistic children are often hypersensitive to sensory stimuli. Most people are able to become used to ongoing sensory stimuli such as background noises, because they can predict that the noise or other stimulus will probably continue, but autistic children have much more trouble habituating.
“If we were unable to habituate to stimuli, then the world would become overwhelming very quickly. It’s like you can’t escape this cacophony that’s falling on your ears or that you’re observing,” Sinha says.
Pawan Sinhaa,1, Margaret M. Kjelgaarda,b, Tapan K. Gandhia,c, Kleovoulos Tsouridesa, Annie L. Cardinauxa, Dimitrios Pantazisa, Sidney P. Diamonda, and Richard M. Helda,1
aDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139; bDepartment of Communication Sciences and Disorders, Massachusetts General Hospital Institute of Health Professions, Boston, MA 02129; and cDepartment of Biomedical Engineering, Defense Institute of Physiology and Allied Sciences, New Delhi, India DL 110054
A rich collection of empirical findings accumulated over the past three decades attests to the diversity of traits that constitute the autism phenotypes. It is unclear whether subsets of these traits share any underlying causality. This lack of a cohesive conceptualization of the disorder has complicated the search for broadly effective therapies, diagnostic markers, and neural/genetic correlates. In this paper, we describe how theoretical considerations and a review of empirical data lead to the hypothesis that some salient aspects of the autism phenotype may be manifestations of an underlying impairment in predictive abilities. With compro- mised prediction skills, an individual with autism inhabits a seemingly “magical” world wherein events occur unexpectedly and without cause. Immersion in such a capricious environment can prove overwhelming and compromise one’s ability to effectively interact with it. If validated, this hypothesis has the potential of providing unifying insights into multiple aspects of autism, with attendant ben- efits for improving diagnosis and therapy.