Cognitive Bias in Forensic Pathology Decisions was published today by Journal of Forensic Sciences

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

The classical pattern arises from the time lapse of the activation and relaxation of the two walls, creating a pattern of interaction due to a sequence temporal imbalances of the tension between the two walls.

2/ As the septum is activated first, it contracts (shortening - septal flash) without activation of the lateral wall, which stretches. This generates slower pressure build up than a normal IVC, which then is prolonged.

3/ During ejection, the LV volume decreases, so both walls shorten. Tension, however, declines first in the septum, as this was activated first. This leads to a tension imbalance, so the lateral wall continues to shorten, the more relaxed septum stretches.

4/ The stretching of the septum builds up an elastic tension in the septum, which is released as recoil, when tension declines in the lateral wall, showing a post systolic shortening in the septum which is due to elasticity.

Let's talk about Avi Loeb and his theory about alien

First, I should disclose that I work at the fame research facility as Dr. Loeb, though I work in a different department and to my recollection we've never met.

He's a scientist; I'm in computer support.

With that out of the way...
The interview above is worth a read, and a lot of serious thought, because there's an idea there that's really critical to science, and it isn't whether or not aliens have visited (exactly).

It's about how fashion and culture and taboo have an unfortunately strong effect on science.

In particular he compares his theory on alien visitation with the multiverse theory.

Which of these is more deserving of ridicule?

Science is fundamentally a structure for forming hypotheses and then (critically) testing these hypotheses to see if they should be kept, rejected, or modified.

Some 1300 years ago in Karnataka there lived a genius who wrote "Gaṇitasārasan̄graha" (which is earliest text devoted entirely to mathematics)

The man who's work later borrowed by Arabs & Europeans

Thread on "Mahāvīracharya" astounding but forgotten legacy

Mahāvirachārya was patronised by rashtrakuta king amoghavarasha

His book"Gaṇita-sāra-saṅgraha"is earliest text devoted entirely to Mathematics

He has described the currently used method of calculating(LCM)of given numbers.The same method was used in Europe later in1500CE

Mahavira wrote "Gaṇita-sāra-saṅgraha" (GSS) in 8th century CE which contains some 1100 slokās & contains elementary topics in arithmetic , algebra , geometry , measurements , logic , number theory , dynamical systems etc

A sheer mathematical genius

He was devout jain
His magnum opus "Ganit sara sangraha " start with a sloka bowing to the glory of the jinas

"संख्याज्ञानप्रदिपेन जैनेंद्रन महत्वेशा,
प्रकाशितम जगतसर्व येन तम प्रणमाम्यहम"

He also praised his predecessor aryabhata , brahmagupta & other greats in his works

The importance & popularity of "Gaṇita-sāra-saṅgraha"was so huge that it enjoyed statues of most important textbook of mathematics in South Indian for over 3 centuries

A large no of manuscript copies of
"Gaṇita-sāra-saṅgraha"whr discovered in Kerala shows it's popularity

1/

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.

2/

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]: