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Merry Christmas to every beloved soul who celebrates Xmas.
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MY NEW RESEARCH - THE PFIZER LAB: THE GAZA WAR EDITION.
Pfizer AGAIN uses Israelis as a laboratory rats to test its products, AGAIN the Israeli ministry of health & Israeli doctors are taking part, and AGAIN patients are not being informed!
https://open.substack.com/pub/ehden/p/the-pfizer-lab-the-gaza-war-edition
Pfizer AGAIN uses Israelis as a laboratory rats to test its products, AGAIN the Israeli ministry of health & Israeli doctors are taking part, and AGAIN patients are not being informed!
https://open.substack.com/pub/ehden/p/the-pfizer-lab-the-gaza-war-edition
Sense of Awareness
THE PFIZER LAB: THE GAZA WAR EDITION.
Pfizer AGAIN uses Israelis as a laboratory rats to test its products, AGAIN the Israeli ministry of health & Israeli doctors are taking part, and AGAIN patients are not being informed!
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I've updated the article - I believe I found proof of manipulation in the phase 2 trial. According to the paper that published the phase 2 results there were 21 people enrolled in the trial BUT the Israeli website that track clinical trials state there were 50 people!!
https://my.health.gov.il/CliniTrials/Pages/MOH_2019-10-24_007451.aspx
https://my.health.gov.il/CliniTrials/Pages/MOH_2019-10-24_007451.aspx
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THE PFIZER LAB: THE GAZA WAR EDITION. ADDENDUM #2: IF IT IS SAFE AND EFFECTIVE WHY SELL IT?
Pfizer bought #fosmanogepix developer Amplyx in April 2021 for undisclosed amount after $93m investment in it in 2020, yet in November 2023 it sold the drug rights to Basilea for $37m, while keeping distribution rights if passing phase 3.
Why? My estimates are that Pfizer was hedging the risk of their investment in the product. If Pfizer has realised that the product is risky (not safe, and/or not effective) and didnโt want to have to report about the huge losses they have had as a result of the bad investment (not only financial loss but reputational loss), by offshoring the phase 3 to another company while maintaining the ability to sell it if it will pass phase 3 it allowed Pfizer to distance itself from the risks, while maintaining the ability to milk profits IF Basilea Pharmaceutica will be able to find a way to push through a successful phase 3.
Pfizer bought #fosmanogepix developer Amplyx in April 2021 for undisclosed amount after $93m investment in it in 2020, yet in November 2023 it sold the drug rights to Basilea for $37m, while keeping distribution rights if passing phase 3.
Why? My estimates are that Pfizer was hedging the risk of their investment in the product. If Pfizer has realised that the product is risky (not safe, and/or not effective) and didnโt want to have to report about the huge losses they have had as a result of the bad investment (not only financial loss but reputational loss), by offshoring the phase 3 to another company while maintaining the ability to sell it if it will pass phase 3 it allowed Pfizer to distance itself from the risks, while maintaining the ability to milk profits IF Basilea Pharmaceutica will be able to find a way to push through a successful phase 3.
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My thoughts about the new Pfizer drug and current "modern" medicine
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This is why Dave is the GREATEST comedian of our time. From "The Dreamer", releases yesterday.
HAPPY NEW YEAR everyone!!!
HAPPY NEW YEAR everyone!!!
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DIVINE GIFT! Via a series of prompts I've asked ChatGPT to generate a 5 minutes audio file (using python) that will represent the most heavenly, divine, healing frequencies. I've created TWO versions - one for an awaken state, providing focus, calmness, and alertness, and the 2nd for sleep assistance. Here is a lossless compressed versions. LISTEN ONLY VIA GOOD DIRECTLY CONNECTED SPEAKER OR HEADHPONES. BLUETOOTH WILL MOST LIKELY DISTORT THE EFFECT.
Here is some background:
Heaven = Happiness + Harmony + Transcendence
# Harmonious intervals (perfect fifths, major thirds, major sixths)
freqs = [
261.63, # C4
329.63, # E4 (major third)
392.00, # G4 (perfect fifth)
523.25, # C5 (octave)
587.33, # D5 (major sixth)
divine_freqs = [200.0, 300.0, 400.0, 500.0, 600.0]
heavenly_freqs = [261.63, 329.63, 392.00, 523.25, 587.33]
healing_freqs = [174.0, 285.0, 396.0, 417.0, 528.0, 639.0, 741.0, 852.0, 963.0]
For the awaken state:
calmness_freqs = [8.0, 12.0, 16.0, 20.0, 24.0]
alertness_freqs = [30.0, 50.0, 70.0, 90.0, 110.0]
Here is some background:
Heaven = Happiness + Harmony + Transcendence
# Harmonious intervals (perfect fifths, major thirds, major sixths)
freqs = [
261.63, # C4
329.63, # E4 (major third)
392.00, # G4 (perfect fifth)
523.25, # C5 (octave)
587.33, # D5 (major sixth)
divine_freqs = [200.0, 300.0, 400.0, 500.0, 600.0]
heavenly_freqs = [261.63, 329.63, 392.00, 523.25, 587.33]
healing_freqs = [174.0, 285.0, 396.0, 417.0, 528.0, 639.0, 741.0, 852.0, 963.0]
For the awaken state:
calmness_freqs = [8.0, 12.0, 16.0, 20.0, 24.0]
alertness_freqs = [30.0, 50.0, 70.0, 90.0, 110.0]
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Here is the code for Heavenly_devine_healing_sleep_assist_five_minutes.python
import numpy as np
from scipy.io.wavfile import write
def generate_healing_sleep_assist_sound(duration, sample_rate):
t = np.linspace(0, duration, int(duration * sample_rate), endpoint=False)
# Divine frequencies and amplitudes with higher dynamic range
divine_freqs = [200.0, 300.0, 400.0, 500.0, 600.0]
divine_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
divine_amplitudes = [amp * 10**(18 / 20) for amp in divine_amplitudes]
divine_sound = np.zeros_like(t)
for freq, amp in zip(divine_freqs, divine_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
divine_sound += 0.2 * np.sin(2 * np.pi * 2 * divine_freqs[0] * t)
divine_sound += 0.1 * np.sin(2 * np.pi * 3 * divine_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
divine_sound *= np.linspace(1.0, 0.7, len(t))
divine_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Normalize to range [-1, 1]
divine_sound /= np.max(np.abs(divine_sound))
# Heavenly frequencies and amplitudes with higher dynamic range
heavenly_freqs = [261.63, 329.63, 392.00, 523.25, 587.33]
heavenly_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
heavenly_amplitudes = [amp * 10**(18 / 20) for amp in heavenly_amplitudes]
heavenly_sound = np.zeros_like(t)
for freq, amp in zip(heavenly_freqs, heavenly_amplitudes):
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
heavenly_sound += 0.2 * np.sin(2 * np.pi * 2 * heavenly_freqs[0] * t)
heavenly_sound += 0.1 * np.sin(2 * np.pi * 3 * heavenly_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
heavenly_sound *= np.linspace(1.0, 0.7, len(t))
heavenly_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Healing frequencies
healing_freqs = [174.0, 285.0, 396.0, 417.0, 528.0, 639.0, 741.0, 852.0, 963.0]
healing_amplitude = 0.2
for freq in healing_freqs:
divine_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
heavenly_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
# Combine divine, heavenly, and healing sounds
healing_sleep_assist_sound = 0.4 * divine_sound + 0.4 * heavenly_sound + 0.2 * np.random.normal(0, 1, len(t))
# Normalize to range [-1, 1]
healing_sleep_assist_sound /= np.max(np.abs(healing_sleep_assist_sound))
return healing_sleep_assist_sound
# Set the duration and sample rate for one hour
duration_five_minutes = 5 * 60 # 5 minutes in seconds
sample_rate = 44100 # Hz
# Generate healing sleep assist sound for one hour
healing_sleep_assist_sound_five_minutes = generate_healing_sleep_assist_sound(duration_five_minutes, sample_rate)
# Save the generated sound to a WAV file with maximum quality
write("healing_sleep_assist_sound_five_minutes.wav", sample_rate, healing_sleep_assist_sound_five_minutes)
import numpy as np
from scipy.io.wavfile import write
def generate_healing_sleep_assist_sound(duration, sample_rate):
t = np.linspace(0, duration, int(duration * sample_rate), endpoint=False)
# Divine frequencies and amplitudes with higher dynamic range
divine_freqs = [200.0, 300.0, 400.0, 500.0, 600.0]
divine_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
divine_amplitudes = [amp * 10**(18 / 20) for amp in divine_amplitudes]
divine_sound = np.zeros_like(t)
for freq, amp in zip(divine_freqs, divine_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
divine_sound += 0.2 * np.sin(2 * np.pi * 2 * divine_freqs[0] * t)
divine_sound += 0.1 * np.sin(2 * np.pi * 3 * divine_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
divine_sound *= np.linspace(1.0, 0.7, len(t))
divine_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Normalize to range [-1, 1]
divine_sound /= np.max(np.abs(divine_sound))
# Heavenly frequencies and amplitudes with higher dynamic range
heavenly_freqs = [261.63, 329.63, 392.00, 523.25, 587.33]
heavenly_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
heavenly_amplitudes = [amp * 10**(18 / 20) for amp in heavenly_amplitudes]
heavenly_sound = np.zeros_like(t)
for freq, amp in zip(heavenly_freqs, heavenly_amplitudes):
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
heavenly_sound += 0.2 * np.sin(2 * np.pi * 2 * heavenly_freqs[0] * t)
heavenly_sound += 0.1 * np.sin(2 * np.pi * 3 * heavenly_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
heavenly_sound *= np.linspace(1.0, 0.7, len(t))
heavenly_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Healing frequencies
healing_freqs = [174.0, 285.0, 396.0, 417.0, 528.0, 639.0, 741.0, 852.0, 963.0]
healing_amplitude = 0.2
for freq in healing_freqs:
divine_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
heavenly_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
# Combine divine, heavenly, and healing sounds
healing_sleep_assist_sound = 0.4 * divine_sound + 0.4 * heavenly_sound + 0.2 * np.random.normal(0, 1, len(t))
# Normalize to range [-1, 1]
healing_sleep_assist_sound /= np.max(np.abs(healing_sleep_assist_sound))
return healing_sleep_assist_sound
# Set the duration and sample rate for one hour
duration_five_minutes = 5 * 60 # 5 minutes in seconds
sample_rate = 44100 # Hz
# Generate healing sleep assist sound for one hour
healing_sleep_assist_sound_five_minutes = generate_healing_sleep_assist_sound(duration_five_minutes, sample_rate)
# Save the generated sound to a WAV file with maximum quality
write("healing_sleep_assist_sound_five_minutes.wav", sample_rate, healing_sleep_assist_sound_five_minutes)
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Here is the code for Perfect heavenly, divine, healing, focus, calmness, alertness sound - five minutes.python
import numpy as np
from scipy.io.wavfile import write
def generate_perfect_audio(duration, sample_rate):
t = np.linspace(0, duration, int(duration * sample_rate), endpoint=False)
# Divine frequencies and amplitudes with higher dynamic range
divine_freqs = [200.0, 300.0, 400.0, 500.0, 600.0]
divine_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
divine_amplitudes = [amp * 10**(18 / 20) for amp in divine_amplitudes]
divine_sound = np.zeros_like(t)
for freq, amp in zip(divine_freqs, divine_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
divine_sound += 0.2 * np.sin(2 * np.pi * 2 * divine_freqs[0] * t)
divine_sound += 0.1 * np.sin(2 * np.pi * 3 * divine_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
divine_sound *= np.linspace(1.0, 0.7, len(t))
divine_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Normalize to range [-1, 1]
divine_sound /= np.max(np.abs(divine_sound))
# Heavenly frequencies and amplitudes with higher dynamic range
heavenly_freqs = [261.63, 329.63, 392.00, 523.25, 587.33]
heavenly_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
heavenly_amplitudes = [amp * 10**(18 / 20) for amp in heavenly_amplitudes]
heavenly_sound = np.zeros_like(t)
for freq, amp in zip(heavenly_freqs, heavenly_amplitudes):
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
heavenly_sound += 0.2 * np.sin(2 * np.pi * 2 * heavenly_freqs[0] * t)
heavenly_sound += 0.1 * np.sin(2 * np.pi * 3 * heavenly_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
heavenly_sound *= np.linspace(1.0, 0.7, len(t))
heavenly_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Healing frequencies
healing_freqs = [174.0, 285.0, 396.0, 417.0, 528.0, 639.0, 741.0, 852.0, 963.0]
healing_amplitude = 0.2
for freq in healing_freqs:
divine_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
heavenly_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
# Focus frequencies
focus_freqs = [20.0, 40.0, 60.0, 80.0, 100.0]
focus_amplitudes = [0.6, 0.5, 0.4, 0.3, 0.2]
for freq, amp in zip(focus_freqs, focus_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Calmness frequencies
calmness_freqs = [8.0, 12.0, 16.0, 20.0, 24.0]
calmness_amplitudes = [0.6, 0.5, 0.4, 0.3, 0.2]
for freq, amp in zip(calmness_freqs, calmness_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Alertness frequencies
alertness_freqs = [30.0, 50.0, 70.0, 90.0, 110.0]
alertness_amplitudes = [0.6, 0.5, 0.4, 0.3, 0.2]
for freq, amp in zip(alertness_freqs, alertness_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Combine divine, heavenly, healing, focus, calmness, and alertness sounds
perfect_audio = (
0.2 * divine_sound +
0.2 * heavenly_sound +
0.1 * np.random.normal(0, 1, len(t)) # Add a touch of randomness for diversity
)
# Normalize to range [-1, 1]
perfect_audio /= np.max(np.abs(perfect_audio))
return perfect_audio
# Set the duration and sample rate for five minutes
duration_five_minutes = 5 * 60 # five minutes in seconds
sample_rate = 44100 # Hz
# Generate perfect audio for five minutes
perfect_audio_five_minutes = generate_perfect_audio(duration_five_minutes, sample_rate)
# Save the generated sound to a WAV file with maximum quality
write("perfect_audio_five_minutes.wav", sample_rate, perfect_audio_five_minutes)
import numpy as np
from scipy.io.wavfile import write
def generate_perfect_audio(duration, sample_rate):
t = np.linspace(0, duration, int(duration * sample_rate), endpoint=False)
# Divine frequencies and amplitudes with higher dynamic range
divine_freqs = [200.0, 300.0, 400.0, 500.0, 600.0]
divine_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
divine_amplitudes = [amp * 10**(18 / 20) for amp in divine_amplitudes]
divine_sound = np.zeros_like(t)
for freq, amp in zip(divine_freqs, divine_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
divine_sound += 0.2 * np.sin(2 * np.pi * 2 * divine_freqs[0] * t)
divine_sound += 0.1 * np.sin(2 * np.pi * 3 * divine_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
divine_sound *= np.linspace(1.0, 0.7, len(t))
divine_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Normalize to range [-1, 1]
divine_sound /= np.max(np.abs(divine_sound))
# Heavenly frequencies and amplitudes with higher dynamic range
heavenly_freqs = [261.63, 329.63, 392.00, 523.25, 587.33]
heavenly_amplitudes = [1.0, 0.8, 0.6, 0.4, 0.3]
heavenly_amplitudes = [amp * 10**(18 / 20) for amp in heavenly_amplitudes]
heavenly_sound = np.zeros_like(t)
for freq, amp in zip(heavenly_freqs, heavenly_amplitudes):
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Add ethereal qualities (shimmering overtones)
heavenly_sound += 0.2 * np.sin(2 * np.pi * 2 * heavenly_freqs[0] * t)
heavenly_sound += 0.1 * np.sin(2 * np.pi * 3 * heavenly_freqs[1] * t)
# Introduce gradual changes for a sense of transcendence
heavenly_sound *= np.linspace(1.0, 0.7, len(t))
heavenly_sound += 0.1 * np.sin(2 * np.pi * 0.05 * t) # Slow modulation
# Healing frequencies
healing_freqs = [174.0, 285.0, 396.0, 417.0, 528.0, 639.0, 741.0, 852.0, 963.0]
healing_amplitude = 0.2
for freq in healing_freqs:
divine_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
heavenly_sound += healing_amplitude * np.sin(2 * np.pi * freq * t)
# Focus frequencies
focus_freqs = [20.0, 40.0, 60.0, 80.0, 100.0]
focus_amplitudes = [0.6, 0.5, 0.4, 0.3, 0.2]
for freq, amp in zip(focus_freqs, focus_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Calmness frequencies
calmness_freqs = [8.0, 12.0, 16.0, 20.0, 24.0]
calmness_amplitudes = [0.6, 0.5, 0.4, 0.3, 0.2]
for freq, amp in zip(calmness_freqs, calmness_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Alertness frequencies
alertness_freqs = [30.0, 50.0, 70.0, 90.0, 110.0]
alertness_amplitudes = [0.6, 0.5, 0.4, 0.3, 0.2]
for freq, amp in zip(alertness_freqs, alertness_amplitudes):
divine_sound += amp * np.sin(2 * np.pi * freq * t)
heavenly_sound += amp * np.sin(2 * np.pi * freq * t)
# Combine divine, heavenly, healing, focus, calmness, and alertness sounds
perfect_audio = (
0.2 * divine_sound +
0.2 * heavenly_sound +
0.1 * np.random.normal(0, 1, len(t)) # Add a touch of randomness for diversity
)
# Normalize to range [-1, 1]
perfect_audio /= np.max(np.abs(perfect_audio))
return perfect_audio
# Set the duration and sample rate for five minutes
duration_five_minutes = 5 * 60 # five minutes in seconds
sample_rate = 44100 # Hz
# Generate perfect audio for five minutes
perfect_audio_five_minutes = generate_perfect_audio(duration_five_minutes, sample_rate)
# Save the generated sound to a WAV file with maximum quality
write("perfect_audio_five_minutes.wav", sample_rate, perfect_audio_five_minutes)
โค5
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CHALLANGE: change the word "Lyme" with COVID19, change the word "IDSA" with "FDA", and tell me if you can find ANY difference between the conflicts of interests that seems to be the hallmark of the broken regulatory system. The clip is from the 2008 movie "Under Our Skin".
THE MOVIE IS HIGHLY RECOMMENDED!!!
Link to direct watch:
https://www.youtube.com/watch?v=2JgR_Jfbhv8
THE MOVIE IS HIGHLY RECOMMENDED!!!
Link to direct watch:
https://www.youtube.com/watch?v=2JgR_Jfbhv8
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SARS-CoV-2, DEFINITION: A DESIGNER VIRUS, a computer generated structural and functional analog of known virus that has been designed to mimic and enhance its effects while avoiding classification as illegal bioweapon by using fake PCR tests.
(for virus, see next post) XXXX
(for virus, see next post) XXXX
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THE COVID19 MRNA SHOTS "TURBO CANCER" MECHANISM:
(1) mRNA generated spike cause mitochondria damage which lead to cancer. The "vaccine" kills the cell's kill switch. The spike protein fragment 674โ685 neutralize the mitochondria from releasing cytochrome c, which prevents the cell from being able to kill itself. Also, MITOCHONDRIAL DAMAGE is the root cause to the wide range of damage "vaccines" causes, as mitochondrial damage is involve in almost every pathology.
(2) The use of codon optimization leads to misfolded proteins which fuels the cancer.
That's how the bioweapon called "vaccines" works.
(1) mRNA generated spike cause mitochondria damage which lead to cancer. The "vaccine" kills the cell's kill switch. The spike protein fragment 674โ685 neutralize the mitochondria from releasing cytochrome c, which prevents the cell from being able to kill itself. Also, MITOCHONDRIAL DAMAGE is the root cause to the wide range of damage "vaccines" causes, as mitochondrial damage is involve in almost every pathology.
(2) The use of codon optimization leads to misfolded proteins which fuels the cancer.
That's how the bioweapon called "vaccines" works.
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