Presented at the Society for Scientific Exploration 2016 summer conference here in Boulder, Colorado.

A few weeks ago, I did an interview with the lovely Kanyakumari Ayurveda school.

A student read the interview and asked a very good question of her own:

Funny that you mention in the interview that as a teenager, astrology seemed embarrassing. I wonder when such sentiment started building? This reminded me of my classmate's comment. He is an Ivy league graduate who's not doing very well in life. He said "Astrology is too unscientific to me." My inside caption answer to that was "That's why you missed out on 3 big startup exit opportunities." My personal suspicion is that 1) on the surface, industrialization called for humans who just do what they are told, so the ruling class assigned prestige on things that push people further away from success like institutionalized education 2) or, more importantly, there was a cosmic change at some point (perhaps French revolution? End of feudalism?) that somehow pushed certain souls into higher state of consciousness and certain others into "employee" state of mind, to make the industrialization possible to begin with. I think something like this happened again when startup bubble started (division of super smart who use every wisdom passed down to mankind and super dumb thinking institutionalized "knowledge" enlighten them - like myself getting an MBA for a high price). What do you think cause that embarrssement in your young self?

Here is my answer:

Ah, that is a really cool question. I would say it is a bit of both. (Note the rise of the industrialist illuminati with the "Age of Reason".) The best politicians, religionists, industrialists, and businesspeople always​ have used astrology.

The separation of the "everyday people" from astrology probably did occur around the end of feudalism with the rise of industrialism and "Reason".

​My recent ancestors came from a time/space that was still somewhat feudal (early 1900's rural Slovakia, the last place in Europe to get Christianity fully and still not a "Reasonable" place), and the occult was and continues to be quite active in these communities.

​Even in the USA, where far-Eastern Europeans formed very strong communities, such as the pocket of Western PA in which I grew up, there is a deep abiding respect for and use of herbs, organic/biodynamic farming, astrology, and magic.

Remember that the library of the Vatican is covered with a beautiful astrology mural. It and others like it are all dated to 16th Century, an apex of astrological influence from right before the Age of Reason. Perhaps the installation of the separation of the everyday people from astrology  is a result of this apex of astrology, a kind of great peaking awareness of the ​power​ of astrology and a development of a long game of maximizing its power by the most resourced people. Industrialism also took everyday people away from the lessons of wild land and Nature, including the hidden lessons.

​I kind of consider myself one of the first Millennials, so to speak, where, 20 years ahead of the curve, I dropped academia for something much more cool, difficult, and truly worthwhile. As such, I have done things for reasons that I consider ancient: is it true? is it beautiful? is it eternal?  As a teenager, I shied away from astrology simply with a teenager's keen sense of the social: my friends were all science geeks like myself and I wanted to join the whole lot of them in conversation and not stick out.

It is only when we grew up, literally and metaphorically, did their and my respect for, and language and understanding of, these hidden spaces such as astrology grow and develop too. 

Also, how my parents did astrology seemed more about the immediate, the material. The truth, beauty, and eternity of Vedic astrology was not yet shown  to me. And theoretical science as a  field did show those traits to me. I am grateful for that knowledge now for their practical aspects and am only sad for the years of yearning, for the chasm in my life when science was all I had before Vedic astrology appeared, but as a friend points out, without that time, I would not be where I am today.

In a similar way, I am not angry at the Illuminati and the industrialists, et al. ​When astrology has a full comeback, it will be all the sweeter for having been tested.

Offered through Ayurved Sadhana Vidyalaya for a group that is both online and in-person.

We are only a week into each. (They are separate courses.)

There are full past recordings of each.

See http://ayurvedsadhana.com/sanskrit-and-jyotish/ for more.

1.08 by 1.08 inches square as per instructions, with baille;
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Sanskrit numerals form the magic square associated with the holy planet Jupiter and the holy number three.

There are yantras for the Sun, Moon, and Venus as well. All other grahas ("planets" in Jyotish or Vedic astrology) are also available by request.
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These are available in many varieties of silver and gold, including very inexpensive plated versions.

For more information, see the book Numerology by Harish Johari.  Here, here, and here are some more sites worth reading.

A Let's Wing It Production.

Organic Oats
Organic Soy Flour
Organic Coconut Flour
Organic Yogurt
Organic Sugar
Baking Yeast
Ghee or Oil
Organic Vanilla and/or Almond Extract (optional)
Organic Raisins (optional)
Organic Almond Slices (optional)
Egg (optional)

Mix about 1 cup each of the flours. Then include about 2 1/2 tbsp of yeast (if you are at altitude - less, I think, if you are not). Add about 1 cup of yogurt, 1 - 2 tbsp ghee or oil, and the 1 egg if you are doing that, along with about 1 tbsp of the extract(s). Mix in about 1/4 cup of the sugar and raisins and/or almond slices each. Knead using your favorite method, by hand or in a bread maker.

Add water if it is too dry and extra flour of your favorite type if it is too wet. Making some previous loaves is probably the best way to know if either of those are happening.

Bake at least 1 hour and 15 minutes on light setting in the bread maker if that is what you are using. If you are using an oven, use the equivalent temperature. Godspeed in trying to find out what that is. (I think it might be around 350-375 Fahrenheit.) If you are going this route, keep an eye out for done-ness as soon as 45 minutes in.

Let substantially cool before slicing.

I did this quick project for a friend who wanted to know the best place to put her dollars to get the most protein.

The raw USDA source data can be found here.

Some immediate surprises:

• how proteinaceous native Inuit foods are (it's ok to make up words here, isn't it?),
• restaurant cole slaw is below fruit pie by ratio,
• fish and meat rank higher than I knew, but not as high as soy. (What do you think of soy? And its various and manifold controversies? I, for one, have eaten meat more recently than soy, sadly enough in some ways),
• scary to think that this is the US diet option set,
• rock on, pumpkin seeds!
• rock on, spirulina!
• what is "raw cisco" anyway?
• I don't even want to think about "raw, turtle, green".

Download the spreadsheet here:

1.                  Introduction

“Mercury retrograde” is, in my culture, a time of great concern.
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It is believed by many that the apparent astronomical retrogression affects human communication, travel, use of electronics, and thinking, among other broadly related things.

To test the general thesis of an effect on communications during Mercury retrograde, I looked at a randomized 5% of a collection of 69,242,585 Amazon reviews posted between Jan 1, 2009 and July 23, 2014. (Amazon.com: Online Shopping for Electronics, Apparel, Computers, Books, DVDs & more n.d.)

I counted the number of words per entry that are not in a computerized dictionary, while discounting digits, internet links, emoji, words with three or fewer characters. Non-English entries were also discarded.

As well, not considered were context mistakes (such as there/their/they’re), grammar, punctuation, or capitalization errors. I wanted to simply approach comparing occurrences of larger non-dictionary words in Mercury retrograde seasons versus non-Mercury retrograde seasons. 

2.                   Materials

The source of the millions of Amazon reviews is a big data repository held by Stanford University. (Jure Leskovec and Andrej Krevl 2014) The Amazon data in particular is managed by Julian McAuley who kindly made it available to me for research purposes. (J. McAuley 2015)

I chose an “aggressively deduplicated” version of the dataset that has no duplicated entries whatsoever. This data represents all 82.84 million Amazon product reviews with metadata to the date of July 23, 2014.

3.                   Methods

The software Mathematica was used to implement standard data science and signal processing techniques. (Wolfram Research, Inc. 2015) The algorithms are publicly available. (Oshop, Zenodo 2015)

First, the data was scrubbed of 16.04% of its 82,469,759 entries, as these proved to be nonstandard JSON (the main format of the database) and could not be evaluated by Mathematica itself. Since automating analysis of such a large dataset would be a primary key to any success, I was comfortable with the percentage lost. However, whether there is some important unifying theme to the lost entries, such as Amazon product department, time of submission, etc. is not known by me. Using such large datasets (here, 57 GB uncompressed) is still something of an art form, especially for an older dataset, even by the best operators of the best technologies.
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Thus, a table of 69,242,585 lines was built with two entries per line: the time of the original entry in Unix format and the review text, including edits. No record exists in this database of the timing of the edits to the review.

Next, I programmed an evaluation that used a random number generator and the built-in dictionary to analyze a randomized choice of 5% of all entries. (DictionaryLookup Source Information—Wolfram Language Documentation n.d.)  

Each entry’s review was split into textual word substrings. To find emojis and links, the word strings had to be analyzed character by character.

After that, if the dictionary found no match to the word string, it was counted as a “misspelling” in that entry.  A sum of these entry misspellings was divided by the number of total textual words in the entry and the result was recorded along with the day of the original submission.

Even with a randomized sampling of only 5%, running this program took about 31 hours on my desktop computer, at a rate of analysis on the order of 1,000 entries per second.

Note that this technique would consider an unusual brand name of a product, for example, as a misspelling which would be introduced as a kind of noise to any more general trend.

The resulting entries were grouped by date. A day’s group mean was recorded with that date and retained. These values for all dates in between January 1, 2009 and July 23, 2014, GMT, were built into a time series.  

A mean filter was applied to the time series, and the results were plotted along with it.

The difference between the actual mean value for the day and the trend from the filter was found though subtraction and plotted.

A variety of periodicities emerged. That variety was analyzed through a discrete Fourier transform. The main structure, coming from the contribution of the highest two values, was graphed and found to correspond well to the regular periodicity of Mercury retrograde.

In the following pictures, the thin vertical bands mark the actual demarcations of Mercury retrograde, GMT, in that time frame.

4.                  Results

A.                 Movement of Daily Averages

The blue line describes the up and down movement of actual daily averages. The lighter gold line depicts the general trend. This general trend was obtained by a mean filter on the blue data.

​5.                   Discussion

Looking much like software’s graph of an audio clip of the human voice, Figure 2 might at first seem fascinating but opaque to easy interpretation.

In the case of the audio’s graph, the sound it represents is all in there, but how do you get from the visual picture back to the sound again? After all, recording, compressing, transmitting, and recreation of audio all happen from such software.

There has to be a mathematical way, and there is. One of the major tools of science of the last one hundred years is the Fourier transform.

Think of someone playing a pure middle C note on a perfect piano. The Fourier transform would break down that note to a graph much like Figure 3, only there would just be a single line on the left (with its mirror on the right), also called the fundamental: the one matching the frequency of middle C.

In Nature, things tend to be more complicated. An actual piano would likely have rough, very minor sub-harmonics that build on and modify the major one.  The major one would still have the exact shape of the sinusoidal wave of perfect middle C, but these rough minor frequencies would adjust that first dominant curve into a final wave form  that is more complicated than, but resembling, a pure C note.

This set of more minor notes would also appear on the Fourier transform plot, but as shorter lines and at placements along the horizontal axis that correspond to each of their frequencies. The heights give their order of modification of the first, fundamental note. Typically, the whole wave can be summarized in just a few lines. That is how compression and removal of noise in sound happens.

Returning to the sound of the human voice, the complex stacking of a rich variety of sub-harmonics could still be teased apart by the wonder of the Fourier transform, but into dozens of lines.

Similarly, looking at the wave form of Figure 3, there are dominant  “notes” that can be pulled out, and the most fundamental, dominant one of all, the one that all others modify, is at a frequency band of occurring approximately once every 142 to 162 days, with a phase shift for the time window of -2.90338. This is the highest band at position 9. The major, first harmonic appears next in height (and strength of effect) at the 13 position which represents a frequency band of occurring  approximately once every 111 to 115 days, with a phase shift for the time window of 1.05873, the very frequency and phase shift of Mercury retrograde itself in the time period being considered.

Adding the fundamental and first harmonic together, we obtain a wave, and as seen in its graph in Figure 4, the lowest troughs of the wave all happen in between the periods of time also known as Mercury retrograde with the highest peaks all in Mercury Retrograde. 

6.               Conclusions

The results of this study  are still a ways away from proving that Mercury retrograde causes spelling errors, although, with this study, an important first step has been established. Herein is just proof that the period also known as Mercury retrograde is a uniform time of maximum periodic contribution to non-dictionary word use in the dataset, an increase that can be as high as 2.19%.

If this small, but significant, error rate boost in a single act would hold across a series of them, then compounded across the thousands of small things that we do each each day, it would make one virtually sure to make a big mistake (one that is built from the small steps) during the 21 - 23 days of a Mercury retrograde period.

A remarkable side note is that the two percent, statistically significant increase was the same found during Mercury retrograde for a completely unrelated database’s non-dictionary use rate during a completely different period. (Oshop, Across Millions of Entries, Reddit is More Likely to Show Misspellings During Mercury Retrograde in May 2015, 2015)

There may still be some unknown market or cultural factor that has exactly the same periodicity and starting point as Mercury retrograde. If so, that would still suggest a tendency, actually an absolute correlation, to increased use of non-dictionary words during Mercury retrograde seasons. People who believe in some increased danger of error during that time would still be right.

The poetic turn of phrase of the harmonics of the spheres may be no mere metaphor.

​Works Cited

Amazon.com: Online Shopping for Electronics, Apparel, Computers, Books, DVDs & more. n.d. http://www.amazon.com (accessed 10 24, 2015).

"DictionaryLookup Source Information—Wolfram Language Documentation." Wolfram Language & System Documentation Center. n.d. http://reference.wolfram.com/language/note/DictionaryLookupSourceInformation.html(accessed 10 24, 2015).

Discrete Fourier Transforms—Wolfram Language Documentation. n.d. http://reference.wolfram.com/language/tutorial/FourierTransforms.html (accessed 10 25, 2015).

J. McAuley, R. Pandey, J. Leskovec. "Inferring networks of substitutable and complementary products." Knowledge Discovery and Data Mining, 2015.
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Jure Leskovec and Andrej Krevl. {SNAP Datasets}: {Stanford} Large Network Dataset Collection. June 2014. http://snap.stanford.edu/data (accessed 10 24, 2015).

Oshop, Renay: 
- Across Millions of Entries, Reddit is More Likely to Show Misspellings During Mercury Retrograde in May 2015. 10 10, 2015. http://www.ayurastro.com/articles/across-millions-of-entries-reddit-is-more-likely-to-show-misspellings-during-mercury-retrograde-in-may-2015 (accessed 11 2, 2015).
— (2015). Non-Dictionary Words Occur More Often in Amazon Reviews During Mercury Retrograde. Zenodo. DOI: 10.5281/zenodo.32847

Wolfram Research, Inc. Mathematica. Version 10.2. Champaign, IL: Wolfram Research, Inc., 2015.

I want to talk about something for which there is unfortunately only a picture in my mind's eye.

While going to sleep, whether before or after that murky demarcation, I do not know, I saw a beautiful woman on the other side of a window, something like a friend's living room window to be exact.

The woman was smiling. I acknowledged her, and then I realized I actually loved her very much, and drew my fascination directly at/toward her.

She was me!

She smiled at me, and with an explosion of recognition of my self, I awoke sharply, heavily breathing, eyes straight toward the wall, wanting so very much more than anything else to see her again, to know her more, to learn more from her.

Who is she/me?

That is all I want to know anymore, and this dream/vision gave me my clearest information to date of the essential question, who am I?

Also, the peace of knowing a bit of the answer, even of a partial detail, cannot be overstated. Being in the mere memory of it has brought me bliss, contentment, and completion all morning, bliss for which there are not words, and so I bring forward the idea of svastha both to you and to me: the importance of being “situated in the Self”. Smrtr labdhaa. Memory regained.

Know thyself. It is all you really have to do.