1/ #LBBB generates often a classical pattern on #EchoFirst. The pattern is very distinctive in Tissue Doppler of the septum.

In physics, energy is that which is causally invariant or symmetric with respect to time. Said differently, energy is never created or destroyed, it is conserved in the universe.

Now there is a question about information. Is information causally invariant? Does information remain the same with respect to time? To understand this, let's first understand what energy is, then attempt to understand what information is.

The strange thing about energy is that it is this universal currency that seems to be interchangeable between the different forces in nature (i.e. electromagnetic, strong, weak and gravity). It is that thing that makes change possible.

Now let's assume that the universe is computational in nature. That is, anything we see in nature is a consequence of computation. That is, there is computation underneath the physics that is driving the universe to change.

What does it mean then that information is conserved in this computational universe? Also, how is energy conservation related to information conservation?

A Thread about Famous Armenian Inventors and what we have contributed to the world. So the next time someone wants to say we are unimportant, you can rest easy knowing Armenians have contributed some of the greatest inventions to mankind. Here is a handful but there's more.

Raymond Damadian: Armenian-American Physician and inventor of the first MRI machine. MRI is a medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes of the body. Raymond created the first MRI in 1977.

Artem Mikoyan: One of the most famous engineers in aviation. Mikoyan along with Gurevich created one of the most famous Jet lines in history, the MiG. MiG jets directly competed with American Lockheed Martin F Series planes and were among the first to surpass the speed of sound.

Hovannes Adamian: Most notably laid the foundations of color television with his Tri-Color Principle. His work would go on to become the framework that is used to create Color-TV that we see today. He is recognized as one of the founders of color television.

Emik Avakian: An inventor who unfortunately was disabled, but that didn't stop him from contributing work that would help people similar to his condition. Notable contributions are the automatic wheelchair which dismiss the action of hand rolling and a breath operated typewriter.

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Get a cup of coffee.

In this thread, I'll help you understand the basics of Binomial Thinking.

The future is always uncertain. There are many different ways it can unfold -- some more likely than others. Binomial thinking helps us embrace this view.

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The S&P 500 index is at ~3768 today.

Suppose we want to predict where it will be 10 years from now.

Historically, we know that this index has returned ~10% per year.

If we simply extrapolate this, we get an estimate of ~9773 for the index 10 years from now:

3/

What we just did is called a "point estimate" -- a prediction about the future that's a single number (9773).

But of course, we know the future is uncertain. It's impossible to predict it so precisely.

So, there's a sense of *false precision* in point estimates like this.

4/

To emphasize the uncertainty inherent in such predictions, a better approach is to predict a *range* of values rather than a single number.

For example, we may say the index will return somewhere in the *range* of 8% to 12% (instead of a fixed 10%) per year.

5/

10 years from now, this implies an index value in the *range* [8135, 11703]:

Announcing the 2021 Summer Institutes in Computational Social Science. #SICSS is for grad students, post-docs & beginning faculty. Free for participants. @chris_bail and I are happy to tell you about all 20 locations. https://t.co/wolhtZIMc5 [thread]

SICSS brings together social scientists & data scientists interested in computational social science for 1-2 week events with intensive study & collaborative research.

Topics covered include automated text analysis, web scraping, non-probability sampling, digital experiments, ethics & much more.

All education materials created for SICSS are available open-source so that people who are unable to participate can still learn. You can also use them in your teaching. Here are materials from previous years:

Because of COVID, all SICSS locations will be online only in 2021.