[Article] Ukraine: We Should Talk Now

Hiroshima, 1945, 15-20 Kilotons

The first atomic bomb used in war — dropped on Hiroshima, Japan on August 6, 1945 killed about 140,000 people. The second atomic bomb used in war — dropped on Nagasaki on August 9, 1945 — killed a similar number. The bomb dropped on Hiroshima had an explosive yield equivalent to about 15-20,000 tons of TNT.

Castle Bravo H-Bomb Test, 15 Megatons, March 1, 1954

Castle Bravo, shown above, was the first test of a deliverable hydrogen or thermonuclear bomb — a bomb small enough to be launched on an intercontinental ballistic missile (ICBM) over the poles to strike Russia or any other target. The Castle Bravo bomb had an explosive yield about one-thousand times more powerful than the atomic bomb dropped on Hiroshima, with a yield of about 15 million tons of TNT (15 Megatons).

As this article is written, the United States and Russia, the two major nuclear powers in the world, are engaged in their most direct, extensive military confrontation in Ukraine ever. Tens of thousands — probably hundred of thousands — have already died. In the Cuban Missile Crisis in 1962, generally considered the closest approach to global thermonuclear war previously, only one person — U2 pilot Major Rudolph Anderson — died.

Major Rudolph Anderson, Jr. was shot down and killed over Cuba during the October 1962 crisis. (U.S. Air Force photo)

Cuba was about one thousand miles from Washington D.C. and separated from the mainland United States by an ocean. Ukraine is about five-hundred miles from Moscow and shares a harder to defend land border with Russia.

The United States and Russia are probably the closest to global thermonuclear war ever. The Bulletin of Atomic Scientists, founded by Albert Einstein and colleagues in the 1940’s agrees. They have placed their so-called Doomsday Clock at 90 seconds to midnight, where midnight represents global thermonuclear war, the closest ever — even closer than during the Cuban Missile Crisis of 1962.

The Doomsday Clock Set to 90 Seconds on January 23, 2023
1980’s Era SS-18 Soviet ICBM

The Soviet SS-18 ICBM that terrified people during the 1980’s at the peak of the Cold War could carry one giant 10-25 Megaton bomb, similar to the Castle Bravo weapon. Usually the SS-18 carried ten 550 Kiloton hydrogen bomb warheads.

Zone of Total Death and Destruction of 10 Megaton Bomb Dropped on Moffett Field

A single 10 Megaton thermonuclear bomb detonated on Moffett Field in Northern California would completely destroy all building and kill everyone within a ten mile radius shown above. This would kill about 1.75 million immediately just in the zone of total destruction. Radiation and blast effects would cause injuries, deaths, and incomplete damage well beyond the red circle total destruction region shown above. Detonation of the bomb during the California dry season (late spring — early fall) would likely cause massive fires in the mountains circling the San Francisco Bay.

A global thermonuclear war between the United States and Russia would probably involve thousands of thermonuclear bombs on both sides. Hundreds of millions would probably die immediately. The war could exterminate the human race due to nuclear winter, large scale radioactive fallout, or unknown effects from detonating thousands of thermonuclear bombs nearly simultaneously — within hours or at most days.

New Russian ICBM’s and warheads are probably more powerful than SS-18

Russia has been upgrading its nuclear force, both ICBM’s and probably warheads, over the last few decades. The modern force is almost certainly more powerful, faster, and more destructive than the SS-18 arsenal of the 1980’s. All or most of the post-Cold War nuclear disarmament agreements between the US and Russia have expired or been suspended.

What is the United States Doing in Ukraine?

What is the goal of confronting Russia in the Ukraine? What is the exit strategy? What is the benefit to the United States or the World of risking global thermonuclear war in a direct military confrontation half way around the world?

The strategy seems to be to bleed, weaken, Russia, perhaps in analogy to the Afghan war in the 1980’s, using the theory that the Soviet defeat in Afghanistan in the 1980’s caused the end of the Cold War.

6/12/1987 President Reagan making his Berlin Wall speech at Brandenburg Gate West Berlin
The Soviet Union lost about 15,000 soldiers in Afghanistan during the 1980’s.

The end of the Cold War was an exceptional event, unprecedented or almost unprecedented in world history. Everyone was caught off guard by the end. Almost no one anticipated the destruction of the Berlin Wall, the withdrawal of Soviet troops from Eastern Europe, let alone the dissolution of the Soviet Union, with many republics like Ukraine becoming separate nations.

It is probable that the Afghan war contributed to some degree, but it is quite unlikely it was the primary cause. The old Soviet Union was not defeated in battle. There was no hot war like Ukraine. Rather the Soviet Union was seemingly “defeated” in the realm of ideas. The Soviet Union decided to implement a range of reforms, with mixed results, and abandon hard core communist ideology.

Afghanistan is about 2,000 miles from Moscow, separated by mountain ranges and several non-Russian speaking regions. Ukraine is only 500 miles from Moscow.

Gambling with global nuclear war with a military confrontation in Ukraine based on a single flukish event, the end of the Cold War, is insane.

Time to Talk

Castle Bravo, 15 Megatons, March 1, 1954 — Just One Hydrogen Bomb
Good Fences Make Good Neighbors (The Great Wall of China)

We should talk now. Every day that the conflict in Ukraine continues, the United States, Russia and indeed the world are gambling with global thermonuclear war which would almost certainly kill hundreds of millions of people immediately and could cause the extinction of the human race.

Good fences make good neighbors. We’ve faced this before. In 1953, newly elected President Eisenhower went to Korea, talked with the Koreans, Chinese, and Russians and ended the disastrous Korean War which cost hundreds of thousands of lives, settling down into a bloody stalemate. The agreement established a wall, the Korean DMZ, between the North and South Korea. Certainly not an ideal solution, but it has kept the peace for seventy years.

If we can spend $100 billion on offensive weapons to kill Russians in Ukraine, we can spend $100 billion or more if needed to establish defensive fortifications and other methods to prevent either side, Russia or the Ukraine, NATO, and the United States from cheating on the peace agreement, as Hitler infamously did in Czeckoslovakia in March of 1939 after occupying the Sudetenland.

Most likely Russia will end up in control of the Crimea and other predominantly Russian speaking regions — a national divorce not unlike the breakup of Czeckoslovakia into the Czech Republic and Slovakia after the end of the Cold War.

We should talk now and eliminate the risk of global thermonuclear war as soon as possible. Such a war would likely destroy the United States and Russia — and possibly mankind.

Think about it. Contact your President, Senators, and Congress-persons: email, phone, in-person if possible.

(C) 2023 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Success Through Failure] Blame Someone Else

(C) 2023 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] Is the “conspiracy theory” label stopping your from reaching your desired audience?

Is the “conspiracy theory” label stopping you from reaching your desired audience?

Has the thought-stopping pejorative phrase “conspiracy theory” ever caused serious problems discussing certain ideas or even objective facts with your audience, friends, family, or colleagues? Today even the simple word “conspiracy” is increasingly used this way. How can you overcome the thought stopping effect of “conspiracy theory” and expand your audience?

“Conspiracy theory” labelers frequently use superficially plausible arguments backed up by no data or a single or few examples. For example: “conspiracies will always or almost always fail because someone would have talked,” citing for example the exposure of the Watergate burglary failure and the downfall of Richard Nixon. This would for example suggest unsolved murders by conspiracies, such as “gang,” “Mafia” or “organized crime” killings are exceptionally rare or nonexistent.

What does the data actually tell us about the frequency and success rate of conspiracies?

For data and more details see:

Text Article URL: http://wordpress.jmcgowan.com/wp/conspiracies-what-does-the-data-show/

Video URL: https://www.bitchute.com/video/8rcV38ElvdDp/

(C) 2023 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video/Tech Jobs] The Problem with Interviews

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Short video on the problem with job interviews.

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(C) 2022 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] Massive TECH Layoffs Amidst Alleged TECH Worker Shortage

Uncensored Video Links: BitChute Odysee Rumble

Video about the contradictions between the current (Nov 2022) massive TECH layoffs and the alleged TECH worker shortage. What does this mean for you?

Article: http://wordpress.jmcgowan.com/wp/article-massive-stem-layoffs-amidst-alleged-stem-worker-shortage/

About Us:

Main Web Site: https://mathematical-software.com/
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A search engine for censored Internet content. Find the answers to your problems censored by advertisers and other powerful interests!

Subscribe to our free Weekly Newsletter for articles and videos on practical mathematics, Internet Censorship, ways to fight back against censorship, and other topics by sending an email to: subscribe [at] mathematical-software.com

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(C) 2022 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video/Article] How to Get Standard Normal Function in Python

https://www.youtube.com/shorts/V-yssaFYwvY

Short video on how to get the standard Normal/Gaussian/Bell Curve function in Python without writing your own implementation which is complex and error prone.

# Example of Standard Bell Curve Function in Python
from matplotlib import pyplot as plt
import numpy as np
import math  # no Gaussian function

# Get scipy add on module from scipy.org
from scipy.stats import norm  # Gaussian function in scipy.stats


# Custom Gaussian/Normal/Bell Curve custom function
def gaussian(x, mean, sigma):
    return 1./(math.sqrt(2.0*math.pi)*sigma)\
        * np.exp(-0.5*np.power((x - mean)/sigma, 2.))


x = np.linspace(-3, 3, 100)
# plt.plot(gaussian(x, 0.0, 1.0))
plt.plot(norm.pdf(x, loc=0.0, scale=1.0))
plt.grid(True)
plt.show()

(C) 2022 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Python] How to compute future date with millisecond precision and timezone displayed

Use the Python datetime module as follows:

# [Python] How to compute future date with millisecond precision and timezone displayed
import datetime
wait_duration_dt = datetime.timedelta(days=400, hours=2, minutes=30)  # expected wait
today_dt = datetime.datetime.now()  # current date/time in local time zone
future_date_time = today_dt + wait_duration_dt  # compute future date
# get human readable local time zone
LOCAL_TIMEZONE = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo
print(future_date_time, LOCAL_TIMEZONE)

(C) 2022 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Python] How to get function signature

How to get function signature in Python

Use:

import inspect
function_signature = inspect.signature(function_reference)

Full Example

#
# [Python] How to get function signature
#
import inspect

def myfunc(a, b, multiplier=1.0):
    return multiplier*(a + b)

print("myfunc(1,2) is:", myfunc(1,2))

sig = inspect.signature(myfunc)

msg = "function signature is: " + str(sig)
print(msg)

Note that the signature sig above is not a string (a Python str object). Must be cast to a Python str to concatenate with a string as shown in computing msg.

Python demonstration code output

(C) 2022 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Python] How to plot text in normalized coordinates in matplotlib

Normalized coordinates refers to plot coordinates where the horizontal and vertical axes run from 0.0 to 1.0 or zero percent to 100 percent of the plot dimensions. One often wants to position text labels or annotations in this way. This is NOT the default for the plt.text(…) function in matplotlib, the plotting add on module for Python that emulates MATLAB style plotting.

The key functions in matplotlib for normalized coordinates are:

ax = plt.gca()  # get the current axes of the plot
plt.text(x, y, "my text", transform=ax.transAxes, fontsize)

This is a short program showing the full use of these two function in context.

# How to plot text in normalized coordinates (0, 1) in matplotlib
# ax = plt.gca()  # get current plot axes object
# plt.text(x, y, string_message, transform = ax.transAxes, fontsize)

import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.0, 10.0, 100)
y = 10*x**2
fig = plt.figure()
plt.title("How to plot text in normalized coordinates in matplotlib", fontsize=8)
plt.plot(x, y, 'g-', label='parabola')
# Plot text in normalized (0.0, 1.0) coordinates in matplotlib
ax = plt.gca()  # get current plot axes object
# NOTE: lowercase first letter of transAxes below
Y_POS = 0.91  # in range 0.0 to 1.0 (100%)
this_text = f"plt.text(0.01, {Y_POS}, \"this text\", transform=ax.transAxes"
plt.text(0.01, 0.95, "ax = plt.gca()", transform=ax.transAxes)
plt.text(0.01, Y_POS, this_text, transform=ax.transAxes)
#
plt.minorticks_on()
plt.grid(True, which='major', color='k')
plt.grid(True, which='minor')
plt.xlabel('X')
plt.ylabel('Y')
plt.show()
fig.savefig('matplotlib_normalized_coordinates.jpg', dpi=72)
Output Plot with key function text positioned in normalized coordinates

(C) 2022 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Python] How to combine two column vectors into a single column vector

How to combine two column vectors into a single column vector in Python and NumPy

Use the NumPy vstack(…) function as show below:

import numpy as np
one = np.array([[1], [2]])
two = np.array([[3], [4]])
blatz = np.vstack((one, two))
print(blatz)
[[1]
[2]
[3]
[4]] 
How to combine two column vectors into a single column vector in Python and NumPy using vstack

(C) 2022 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).