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Saturday Night Science: Apparent Diurnal Variation in Background Radiation

Aware Electronics RM-80 sensorSince October 16th, 1998, I’ve run an Aware Electronics RM-80 radiation monitor pretty much continuously, connected to a serial port on a 1992 vintage 486/50 machine. The RM-80 uses a 7313 pancake Geiger-Müller tube. The tube is halogen quenched and has a minimum dead time of 30 µS, with a mica window which allows alpha particles to pass. The computer interface generates high voltage for the tube from the Data Terminal Ready and Request to Send pins of the serial port and toggles the state of the Ring Indicator line whenever a count is detected. The serial port can be programmed to interrupt on changes in the state of this signal, making it straightforward to implement radiation monitoring in software. Tube sensitivity, calibrated with Cesium-137 (137Cs), is 3.54 µR/hour per count per minute.

The second generation HotBits generator uses an RM-80 detector illuminated by a 5 microcurie 137Cs check source. I decided to attach the HotBits spare detector to a PC and let it run as a background radiation monitor, as much as anything to let the detector run for a while to guard against “infant mortality” in any of its components, should it have to take over for the in-service detector. Aware Electronics supplies the detector with a DOS driver program called AW-SRAD, which I used to log the number of counts per minute, logging the collected data to files in CSV format.

Database Coverage

Here’s a plot that shows the extent of coverage by month over the period I monitored background radiation. The month of May, for example, has just about one year’s complete data (this doesn’t necessarily mean all of May for one year—it might be half of May in 1999 and half in 2000, for example). November has the greatest coverage, in excess of 2.5 years of data. The summer months have the least coverage due to vacations and other circumstances which caused me to shut down the machine connected to the detector. Since we’re examining only diurnal variations—change in flux within a day—the uneven coverage over the months shouldn’t be a problem. If we wanted to explore, for example, whether any diurnal variation we detected varied from month to month, it would be best to extract a subset of the data weighted equally by month, ideally with full coverage of each day of the solar year even though the days may be taken from different years.

Database Coverage

Counts per Minute Histogram

The first obvious step in reducing the data is to plot a histogram showing the distribution of counts per minute; the vertical axis is the number of minutes in the database in which the number of counts on the horizontal axis were recorded. The histogram table is plotted below.

Counts per minute histogram

At first glance, this looks like the Gaussian “bell curve” you’d expect for a random process. At second glance, however, it doesn’t…note that the “tail” on the right hand side, corresponding to larger numbers of counts per minutes appears distinctly longer and “fatter” than the tail on the left side. Still, let’s proceed for the moment on the assumption that we do have a Gaussian distribution and calculate the mean and standard deviation from the data set. Crunching the numbers, we find a mean value of 56.65 counts per minute with a standard deviation of 9.31. We can then plot this Gaussian (normal) distribution as a red line superimposed on the histogram of experimental results.

Histogram vs. normal distribution

This makes it even more apparent that there’s something happening which isn’t “perfectly normal”. Note how the excess on the high end of the histogram pulls the best-fit normal distribution to the right of the actual data distribution, with the histogram bars to the left of the mean consistently exceeding the value of the normal curve and those to the right falling below.

You might be inclined to wonder just how closely we should expect experimental results like these to approximate a normal distribution. Could the observed deviation be nothing more than a statistical fluke? No…compare the fit of the background radiation histogram above with the the plot below of a data set of comparable size collected using the same detector but, instead of monitoring background radiation in counts per minute, measuring counts per second with the detector illuminated by the HotBits Cesium-137 source. Although this data set necessarily includes background radiation as well as counts due to the radiation source, with about 2000 counts per second from the 137Cs source, the roughly one count per second from background radiation has a negligible influence on the results.

Detector illuminated by Cs-137 source

In the radiation source data set we see an essentially perfect fit of the expected normal distribution to the experimental data. This makes it quite clear that there’s something curious going on with the background radiation data. But what?

The Two Population Hypothesis

One way we might end up with the kind of asymmetrical distribution we observe for the background radiation is if the radiation flux we’re measuring is composed of two separate components, or populations, each individually normally distributed, but with different peak value, mean, and standard deviation. Suppose, for example, that the background radiation the detector measures is the sum of that due to decay of heavy elements (principally thorium and daughter nuclides) in the immediate vicinity (the earth beneath the detector and the structure of the building in which it is located) and a less intense cosmic ray flux which occurs in sporadic bursts with a greater mean value than the terrestrial flux. (At this point I’m simply suggesting these sources to illustrate how the background radiation might be composed of two (or more) separate populations with different statistics; I’m not identifying them as the actual components.)

Here’s a “toy model” which illustrates how this might work.

Two population model

Let the brown curve labeled “Population 1” represent the terrestrial component of background radiation. It has a mean value of around 58 counts per minute and exhibits a precisely Gaussian distribution with total flux equal to the area under the brown Population 1 curve. We take the red “Population 2” curve to represent the supposed cosmic ray flux. This also has a normal distribution, but with a mean value of about 70 counts per minute, a greater standard deviation (resulting in a broader distribution curve), and a total flux only about one tenth that of Population 1.

Since counts resulting from the two populations cannot be distinguished by our simple detector, what we observe is the sum of the two populations, shown as the orange “Combined Flux” curve. Note the strong resemblance between this curve and the histogram plot from the detector; while Population 1 dominates the result, the contribution of Population 2 lifts and extends the high end of the combined distribution, precisely as we observed in the experimental data set.

Radiation by Local Solar Time

Next I tried binning the results hourly by local solar time. The following chart shows the results, plotted in terms of average background radiation flux in micro-Roentgens per hour. (The average background radiation of 16.2 µR/hr—142 mR per year—may seem high, but my detector is located at an altitude of 800 metres above sea level. Both the soft and hard [primarily muon] components of cosmic rays are absorbed by the atmosphere, so at a higher altitude more they are more intense. At sea level, cosmic rays contribute about 30 mR/year, but at the 10 km altitude commercial jet aircraft fly, cosmic radiation accounts for about 2000 mR/year; more than 60 times as intense.) When I plotted the hourly local time averages, I obtained the following result.

Radiation by local solar time

I’ve read about variations in cosmic ray flux varying with latitude, in Easterly and Westerly incidence, the solar cycle, and changes in the geomagnetic field, without a mention of a diurnal cycle, yet this plot appears to show a sinusoidal variation, with a magnitude variation between the highest three-hour period and the lowest of almost 6% of the mean value and, further, the trough in the curve seems to be about 12 hours from the peak.

To explore whether this might be nothing but an artifact or statistical fluctuation, I then re-binned the same data minute by minute, resulting in the following plot, in which the blue curve is the raw minute-binned data and the red curve is the same data filtered by an exponentially smoothed moving average with a smoothing factor of 0.9.

Radiation minute-by-minute, smoothed

Randomly selected data subsetWell, it still looks credibly sinusoidal, with the maximum and minimum at about the same point. As we all know, the human eye and brain are extraordinarily adept at seeing patterns in random data. So let’s try another test frequently applied as a reality check when apparently significant results appear in a data set. The chart at the left was created by randomly selecting 25% of the points appearing in the complete data set and plotting them hour by hour. We find that the selection has little effect on the shape of the curve or the location of its maximum and minimum.

Outliers removedNext, I decided to explore whether the apparent sinusoidal variation might disappear if I discarded outlying values, which might conceivably vary differently in time than those which make up the bulk of the database. I pruned the bell curve at one standard deviation, then used the remaining data to prepare the plot at the left. As you can see, the case for a sinusoidal variation is eroded somewhat, but the general shape, magnitude, and location of extrema is conserved.

Outliers and Populations

The fact that removing the outlying values reduced the diurnal variation in the above plot suggests that we may indeed have two populations contributing to the observed flux, with the population responsible for the outlying values containing more diurnal variation than that near the mean. To investigate this further, I passed the data set through a variety of filters and prepared the following plot.

Outliers and populations

In the Stars?

Finally, I decided to plot the average radiation flux against local sidereal time. Sidereal time tracks the position of the distant stars as viewed from a given point on the Earth. At the same sidereal time, the same celestial objects (external to the solar system) will cross the celestial meridian above a given place on the Earth. Because the viewpoint of the Earth shifts as it orbits the Sun, the sidereal day (time between successive meridian crossings of a given star) is about 4 minutes shorter than the solar day (mean time between solar meridian crossings). Correlation with the sidereal period is powerful evidence for a distant source as the cause of a given effect. For example, it was correlation with the sidereal period which provided early radio astronomers evidence the centre of the galaxy and Crab Nebula were celestial sources of the noise they were monitoring. Here’s a plot of average radiation flux by sidereal time.  There is no significant evidence for a correlation of flux with sidereal time.

Background radiation by sidereal time

 

What’s Going On Here?

Darned if I know! The floor is open to inference and speculation.

First of all, I think it’s reasonable to assume that any diurnal variation, should such exist, is due to cosmic rays. The balance of background radiation is primarily due to thorium, radon, and daughter nuclides in the local environment. Where I live, in the Jura mountains of Switzerland, subterranean rocks are almost entirely limestone, which has little or no direct radioactivity (as opposed to, for example, granite), nor radon precursors. In such an environment, it’s hard to imagine a background radiation component other than cosmic rays which would vary on a daily basis. (This would not be the case, for example, in a house with a radon problem, where you would expect to see a decrease when doors and windows were opened during the day.)

If the effect is genuine, and the cause is cosmic ray flux, what are possible causes? The two which pop to mind are atmospheric density and the geomagnetic field. During the day, as the Sun heats the atmosphere, it expands. If you’re at sea level, the total absorption cross section remains the same, but the altitude at which the primary cosmic ray first interacts with an atmospheric atom may increase. Further, an increase in atmospheric temperature may change the scale height of of the atmosphere, which would perturb values measured at various altitudes above sea level. We could explore temperature dependence by comparing average background radiation in summer and winter months.

Let’s move on to the geomagnetic field. It’s well documented that the Earth’s magnetic field and its interaction with the Sun’s create measurable changes in cosmic ray incidence, since the proton and heavy ion component of primary particles is charged and follows magnetic field lines. As any radio amateur or listener to AM radio in the 1950s knows, the ionosphere changes dramatically at night, allowing “skip propagation” of medium- and high-frequency signals far beyond the horizon. Perhaps this effect also modifies the geomagnetic field, affecting the number of charged cosmic rays incident at a given location.

If there is a diurnal effect, why on Earth should it peak around 07:00 local time? Beats me.

References

  1. Clay, Roger, and Bruce Dawson. Cosmic Bullets. Reading, MA: Addison-Wesley, 1997. ISBN 978-0-7382-0139-9.
  2. Wheeler, John Archibald, and Kenneth Ford. Geons, Black Holes, and Quantum Foam: A Life in Physics. New York: W.W. Norton, 1998. ISBN 978-0-393-31991-0.

Download Raw Data and Analysis Programs

If you’d like to perform your own investigations of this data set, you can download the data and programs used in preparing this page. The 2.8 Mb Zipped archive contains the raw data in rad5.csv and a variety of Perl programs which were used to process it in various ways. There is no documentation and these programs are utterly unsupported: you’re entirely on your own.

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Che Done Me Wrong by the Blue Bellies

I know many of you know this song but I wish it would not be sung too often here. I know it was stuck at Number 503 on the charts seemingly forever but I don’t think it will get much higher. Yet i hopes it will.

I like the sound of a new group,The Rat-a-tats. They really Roxie. That producer Kelvin really knows how to get that Cowbell to Fear the Reaper. Top 10 all the way.

 

 

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We Just Hit the 1000 Comment Mark

 

55         Members (3 Pending)

122        Posts

2824    Likes

1            Party

2           Cheerleaders

41         Podcast Links

We started testing on December 10, 2017 with only three people.

In the comments, guess what the total comments will be on the morning of January 10, 2018 and you could win a prize.

 

 

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Molly’s Game: Especially Interesting if You are a Poker Player.

Molly’s Game (2017) is based on the memoir by Molly Bloom (2014). It is the true story, from her point of view. Principally photographed in Toronto, Canada, it is written and directed by Aaron Sorkin (56). He is an award-winning writer, of such things as A Few Good Men and The West Wing, and this is his directorial debut. It would appear that working with good directors has taught him a lot, as his direction of this film is competent and professional. I found his fast conversations as people were moving around, a little hard to follow at times. Perhaps if I knew more about Poker and the running of a Game, I would have found it easier.

Jessica Chastain (40) plays Molly Bloom with conviction. I wonder if the real Molly is always as serious as she is depicted. This is the story of a driven woman, highly intelligent and beautiful, but with no apparent sense of humour. She is an excellent business woman, in what could probably be called more of a man’s world. She even gets lightly beaten up by the Russian Mob, and survives. The FBI were almost too much for her, but she managed to get out of their clutches with much less damage than might have been expected. There doesn’t seem to be a lighter side to her character. This means that there is not a lighter side to the film.

Idris Elba (45) played Charlie Jaffey, Molly’s defense lawyer against the FBI, extremely well. I liked him. Kevin Coster (62), as Molly’s father, Larry Bloom, a clinical psychologist, played competently.

Knowing nothing about poker, or running a Game, I found it interesting that only licensed businesses are legal. Molly Bloom knew this, of course, and never charged an entrance fee for her Game. How she made money, lots of it, was by accepting tips as a “gift” from her “guests.”

The film is entertaining: colourful people; splendid environments; interesting story. My film group all enjoyed it, as did I. I would have enjoyed it more if I could have felt a little more sympathetic towards Molly Bloom. I admired her for doing well in what was a man’s world. She is obviously highly intelligent, beautiful, and a good businesswoman, all of which I appreciate. I just wished I liked her more! Perhaps the problem lay with the film being based too much on her book. To her, the story must be serious, but perhaps a little more objectivity might have lightened it a little. On the other hand, she didn’t give out any names, and perhaps this is what she was wanting to show in her memoir. To the “Names”, that would be very important.

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Curmudgeon before Coffee

It seems the deep state is snarling and gnashing teeth as the traps get sprung. It looks like a number of key folks in DOJ and the FBI and I expect some in CIA and NSA are to be exposed and removed.

The Clinton machine rejected the olive branch Trump held out early on and kept the Trump probes going using the politicized agencies. Now they get the return fire. It seems Bill was the smart one.

2018 will continue as a year of great surprises.

Theme of the midterm elections? “Prosperity is here , right now, for everyone who wants to work. Wages are up, jobs are out there. Or you can go on voting the same old way.”

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TOTD 2018/1/5: Favorites Games & Toys from Your Childhood

I was thinking about this topic because my kids were home over Christmas, and even though they are in their mid-20s now, they broke out board games to play on our dining room table, late into the night.  They were none of the games I remember though! They played Settlers of Cataan, Phase 10 and King Domino.  Some that I remember from growing up in the 1960s are:

Fascination Pool – a plastic maze board that looked like a pool table – the picture above. You held it in your hands, released little balls from the center and tried to tip the board to get all the balls one by one into the color-corresponding pockets – but not let them roll into the wrong-color pocket.

King of the Hill – another game with little balls, you spun a spinner to move your marble up the mountain on little paths, but sometimes you’d land on a spot with a hole, and your marble would drop down a chute and come out a lower level.  Whoever got their marble to the top of the hill dropped it into the crown and I think some action happened then, like the crown popped up or something?

Chinese Jump Rope – Do girls still play this?? All it took was a long circular elastic band. Two children stood about 5 feet apart with the band around their ankles and there was a whole set of jumping actions the third child did with the elastic – then if you completed those actions, the children on the end moved the band up to their knees & you performed the same actions, then to their hips and you tried to perform the same actions – quite a feat!

Did you play these?  What were your favorite games and toys from your childhood?

 

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Let’s get this party started

So we’re a sort of refugee camp – a happy one, to be sure. Full of grown ups.

I’d like to thank John Walker and the infamous Dime for gathering us all together. I am Irish and therefore not an optimist by nature, but I’ve never felt such hope and promise. And I am enjoying seeing so many people I’ve been missing.

My Marine Corps sons are happy (and by definition, so am I), my 401(k) is in the black, BTC is up along with ETH, I have two gorgeous grand daughters and two engaged sons.

Don’t harsh my buzz. 2018 is going to be awesome. (as long as little Rocket Man doesn’t do something stupid with his little buzzer while son #2 is in Okinawa)

Happy New Year. Ratburger never tasted so good.

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I Know, You’d Never Even Think: Ratburger’s Got the Podcast Links

Here at Ratburger, the foremost site for civil discussion on the Internet, unencumbered by  adverts, pop-ups, glacial page loading times, and censors, we don’t (yet) have our own podcasts.  But we listen to them, from time to time.  And now, you can find all of your favourite podcasts right here, without frequenting legacy sites.

There’s a new drop-down on the Activity item on the main menu, “Podcasts”.  It displays a page (or pages, depending upon how many are shown), with links to the most recent two episodes of podcasts followed by Ratburger members.  When you click on the link, you’ll be taken to the site which hosts the podcast; each site may have its own interface to play, download, or otherwise consume its content.  Once you click, it’s on them, not on the rat on a bun.

I have populated this list with podcasts to which I regularly listen.  If you have other podcasts you’d like to add to the feed, please include them in the comments.  In order to be included, the podcast must have a publicly-accessible RSS feed.  Most podcasts do, but it can be challenging to find it.

If this feature proves popular, I may make it more visible than its present state of buried in a sub-menu.

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Understanding the Intel CPU Security Bug

You may have heard about the discovery of a major security hole affecting most recent Intel microprocessors which allows a process running on a computer to exploit a side-channel attack to read privileged information from the operating system or other processes on the same machine.

Here is the technical paper describing this exploit.  This was reported by those who discovered it to the major CPU manufacturers: Intel, AMD, and ARM on 2017-06-01, but kept secret to allow time for mitigation to be put into place.

This is one of the most serious hardware problems to have discovered in mass-produced microprocessors since the notorious Intel Pentium floating point divide bug in 1994.  It is difficult to exploit this bug, but it defeats the security of systems running on these processors at a fundamental level and is costly to mitigate in software, with a performance hit of up to 30% for programs which make a large number of system calls.

The bug is due to interaction between memory protection, the processor’s cache, and a performance tweak called “speculative execution”, in which when encountering a conditional branch the CPU goes both ways and then discards the path not taken after it completes evaluation of the conditional upon which the branch depends.  Unless you’re deeply marinated in CPU architecture, all of this may sound like gibberish, but if you’re using a computer with an Intel microprocessor, it affects you.

Fortunately, Master Explainer Scott Manley has recorded this excellent twelve minute video which provides a gentle introduction to the bug and its consequences.

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TOTD 2018/1/4: Should Politicians Train for the Job? Was Plato Right?

January 4 2018

Should Politicians Train for the Job? Was Plato Right?

Doctors, dentists, lawyers, accountants, and other professionals, all expect to undertake an extensive training to do their very specific jobs. Why not politicians? There are Standardized Best Practices for many organizations, why not for Members of Parliament?

If I were designing a course, it would include economics, history and political science, just as a beginning. You can probably think of other subjects it would be good for politicians to have at least a basic knowledge. Perhaps Plato had it right in The Republic when he suggested training the Guardians of Society, almost from birth.

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#MTIFA

You are probably wondering what that means. I am too. For those who want to guess please do so in the comments. For those who want to find out quickly click here ….

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Picture alignment how to

Alignment None

I  am putting text in just to show how a picture is aligned for the various settings with a picture. It is hard to come up with something to say when you are just filling space. To be or not to be that is the question. Whether it is nobler to …. Not bad for off the cuff, right?

Alignment Left

I  am putting text in just to show how a picture is aligned for the various settings with a picture. It is hard to come up with something to say when you are just filling space. To be or not to be that is the question. Whether it is nobler to …. Not bad for off the cuff, right?

 

 

 

Alignment Center

I  am putting text in just to show how a picture is aligned for the various settings with a picture. It is hard to come up with something to say when you are just filling space. To be or not to be that is the question. Whether it is nobler to …. Not bad for off the cuff, right?

Alignment Right

I  am putting text in just to show how a picture is aligned for the various settings with a picture. It is hard to come up with something to say when you are just filling space. To be or not to be that is the question. Whether it is nobler to …. Not bad for off the cuff, right?

 

 

 

Three places to set this

  1. When you add media by selecting a picture from your picture library, you will see to the right of your screen at the bottom “Alignment” with a drop down menu.    
  2. After you put it in the post and you select the picture. You  will see this. There are six icons above the picture.
    1. Align left
    2. Align center
    3. Align right
    4. No Alignment
    5. Pencil ( When clicked you enter the picture edit mode.)
    6. “X”  (Remove)
  3. After you put it in the post and you select the picture click the Pencil Icon. You will get this screen. (Click the picture to see more clearly.)
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