Program for Reproducing Janet LSPT


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We have written a short computer program that accurately reproduces Janet Left-Step Periodic Table ordering of chemical elements, solving the elusive Mendeleev’s Periodic Law “dream”.

The program is based on Tsimmerman’s Mathematical Expression of Mendeleev’s Periodic Law, detailed at

We are now working on turning it into a handy tool for chemical mining elements.

On Tsimmerman’s Adomah Periodic Table


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Because our Electron Configurations Tool was inspired by Tsimmerman and Janet versions of the periodic table, we felt necessary to add content to the tool’s page to briefly explain some features of Tsimmerman’s table, formally branded as ADOMAH PT.

Essentially, he discovered a rich connection between geometry and quantum information by packing the s,p,d, and f blocks into a regular tetrahedron.

To learn more about this 3-dimensional version of the periodic table, you may want to visit the above link and click on the section that reads Featuring Note: Tsimmerman’s ADOMAH PT.

Valery (“Larry”) Tsimmerman kindly shared with us some revealing comments about the underlying nature of the table.

To learn more about the novelties uncovered by Tsimmerman with ADOMAH PT as recognized by others, you may want to read these peer reviews.

On Sloppy University Sites


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While designing the Electron Configuration Tool, we researched several chemistry sites. Unfortunately many of these have directory browsing/listing enabled, effectively leaving files, technology, and even student resources wide open for the public to see. This is not unique to chemistry sites. On the contrary, it appears to be systemic across university sites and sites across the Web. Actually, we have exposed this before, many times.

For instance, in 4s & 3d, 3d & 4s, Cu & Cr, sloppy aufbau & Eric Scerri! Adrian Dingles shows the PES plot for Sc, obtained from

If you paste in your browser the short version of that url, like this

or like this

the entire content of those directories can be accessed and grabbed by any one. If a directory lists equally browsable subdirectories, then the problem is compounded.

From time to time, one can do a similar exercise across university sites and find entire school resources and student records wide open and accessible, only because directory browsing/listing was not blocked at the server or directory levels. Why expose sensitive information to the public? How smart is that?

Using VIN Number Validators to Prevent Scams


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During the last few days Sugey Lamela, from the local Telemundo tv station in PR, presented an investigative report on the risks of buying used cars through online classified ad portals wherein the ads placed by third parties do not disclose the vehicle identification number (VIN).

The report suggested that scammers frequently do that to avoid others from tracking down the history of the vehicle (if the unit is legit or previously involved in accidents, infractions, crimes, etc).

Well, buyers beware. Even if a VIN is shown in an ad, it can be a fake one. So how could customers be protected if they still want to use those online services?

One easy way: run the VIN through a VIN Numbers Validator tool.

It is always a good idea to check the same number through similar tools from different online sources (preferably from one provided by your local police/MV department or a reputed car insurance company), just in case the scammers have online their own faked validators. How could this be done? Keep reading.

Buyers Beware. A valid VIN can be constructed from an invalid one by simply replacing a check digit with the expected check value.

This is easy to demonstrate with our tool: 1G4AH59H75G118341 must be an invalid VIN as its check digit is 7 when it should be 4. So changing the check digit to 4 produces the valid VIN 1G4AH59H45G118341.

In general, one can change any character from a VIN, try to validate the new VIN, and if it does not pass the validation, replace its check digit with the predicted check value. This exercise simply demonstrates that one cannot just trust online ads displaying VINs. That a VIN is valid does not mean that it belongs to a legit vehicle. Once a VIN passes a validation test, the prospective buyer should research the records associated to the vehicle he is interested in.

Electron Configurations Tool


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We have developed the Electron Configurations tool, available at, as a handy tool for data miners, computational chemists, teachers and their students to easily compute electron configurations.

The tool uses Tsimmerman’s Adomah and Janet’s Left-Step versions of the periodic table which closely follow quantum mechanics and the order of electron-shell filling. It computes configurations of elements with atomic numbers ranging from 1 to 120.

The tool predicts electron configurations by reconstructing, parsing, and then reducing the configuration of the possible heaviest element predicted by Janet (Z = 120), temporarily known today as Unbinilium, Ubn. This approach selectively computes all current electron configurations (from Z = 1 to Z = 120) and can be easily modified to account for heavier elements (Z > 120) in the event that these are discovered.

Anomalous configurations, i.e. those that deviate from the predicted ones are also identified. This is done by comparing the computed configurations against those excellently documented by Eric Scerri.

PS: I spotted an error in this WikiHow article. They stated and quote:

“An electron configuration for an atom with every orbital completely filled would be written: 1s2 2s2 2p6 3s2 3p6 4s2 3d10 4p6 5s2 4d10 5p6 6s2 4f14 5d10 6p6 7s2 5f14 6d107p68s2”

“Note that the above list, if all the shells were filled, would be the electron configuration for Uuo (Ununoctium), 118, the highest-numbered atom on the periodic table – so this electron configuration contains every currently known electron shell for a neutrally charged atom.”

End of the quote.

That is totally wrong. The above is the electron configuration of Z=120, not of Z=118. I wrote a comment at WikiHow pointing this out.

Dictionaries – A New Minerazzi Miner


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Dictionaries is a new miner available at This one allows you to find all kind of definition/word reference resources like dictionaries, glossaries, thesauri, acronym lists, etc.

Need hard-to-find specialty dictionaries? Know of one that you would like to see indexed? Find or submit it at this miner.

Increasing Productivity with Miners


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Our Minerazzi miners ( can help improve productivity in many different scenarios. Just a few to think about:

Scenario 1

Those behind an enterprise intranet or shopping cart often need to catalog items, articles, short pieces of data (like customer and client records). Once in a web template format, each of these can be turned into data mining records and automatically classified. This is simpler than doing the classification by hand, one item at a time.

Scenario 2

Librarians, teachers, students, and researchers often spend large amount of time curating collections, discovering relevant web documents and classifying these. Our platform helps then to do this straight from the search result pages.

Scenario 3

Employees or client records in a format compatible with the miners can be easily classified and pieces of data extracted and mined. Example of such pieces: phone numbers, email addresses, keywords.

Scenario 4

Internet marketers, web designers, coders, and developers in general can build curated collections of phone/email addresses, scripts, CSS rules, color palettes, etc to suit their needs (e.g. launching of marketing campaigns, design of creatives, building of apps, etc).

Scenario 5

Government administrators or webmasters with many resources dispersed over dissimilar databases can have a centralized collection from which these can be linked and mined.

There are more scenarios to think about.

Each miner comes with dozen of extraction tools. Each one also comes with a News center powered by SPP, our tool for mining the pulse of RSS news across social networks. So far we have RSS focusing on technology, but soon we will be adding miner-specific RSS news as we have done with the CRAN and R-Blogs miners as well as with miislita ( miner.

The platform section at also features dozen of multidisciplinary tools for students, teachers, and researchers (eg. The Hydrocarbons Parser, The Data Set Editor, etc) that improves productivity.

PS. I forget to mention that the problem of maintenance (i.e., removing broken links from curated collections) can be a productivity-draining problem.

Our tool automatically removes broken links on a session-based manner; i.e. if a link goes broken and a user finds it, it will be removed in the next user session or when he/she refreshes the results page. Similarly, once a user does a crawl, the crawled link is either indexed or reindexed, allowing collections to be self-indexable!

Unicoder: New User Interface


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The Unicoder Tool, available at now features a new user interface. This one is more user-friendly and faster.

The tool generates Unicode entities in decimal and hexadecimal notations by extracting in real time a range of unicode entities as listed at the site. Cached results are returned if the site is down or something goes wrong.

Who can use it?

Developers that want to test character encoded vulnerabilities; e.g., ascii/unicode injections.

Content creators that need to use specialized, international, or art-like characters or language-specific symbols.

On IR Tutorials, Google, and SEOs


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In a Google patent article on user similarities ( my old tutorial on cosine similarity is cited. If you try to follow that link, you won’t be able to access it as I removed it long ago, along with all of my IR tutorials. These changes were part of the relaunching of as a miner.

I have seen many web pages citing that tutorial, or reproducing that one and many more from the early 2000s. Those attempts are convincing me that I should restore them, perhaps in the tutorials section of Minerazzi?

Perhaps. In the meantime, check this little one where the connection between cosine similarity and Pearson’s Correlation Coefficient (r) is demonstrated.

Essentially, Pearson’s r is a cosine; i.e., the cosine between mean-centered paired variables. As a cosine, Pearson’s r is not additive, nor it can be arithmetically averaged, as many SEOs still wrongly think.