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New Hubble images of Comet 3I Atlas.
speaker_0
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And in Space Bites plus, staring right down the jet of an actively feeding supermassive black hole.
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All this and more, in this week's Space Bites.
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[digital screen click] All right, this is it, this is the moment we've all been waiting for.
speaker_0
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en
Uh, Webb has been looking at the planets, one by one, in the TRAPPIST-1 system.
speaker_0
angry
en
And finally, when Webb arrived, it was the right machine, capable of being able to observe atmospheres on exoplanets.
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en
What do we find?
speaker_0
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And so far, nothing.
speaker_0
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So the closest two planets to the TRAPPIST-1 star, these are TRAPPIST-1b and TRAPPIST-1c.
speaker_0
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en
And it was always assumed that this was a very long-shot chance to be able to detect anything, but the hope was that you would get something like a Venus, where you've got these Earth-sized worlds orbiting close to the star, they're superheated, thick atmospheres of carbon dioxide.
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But they pretty conclusively have been found to have no atmosphere.
speaker_0
angry
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And that's not very surprising because TRAPPIST-1 is a super flare star, which means that it generates a tremendous amount of flare activity that would scour the atmospheres off of any planets that are too close.
speaker_0
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Now, the first planet that is just barely within the habitable zone is TRAPPIST-1d.
speaker_0
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We've been anticipating this day for a very long time, and the results are no atmosphere detected.
speaker_0
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Now, this doesn't mean there's no atmosphere.
speaker_0
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It just means that there was no atmosphere detected, and there's a couple of possibilities that could explain that.
speaker_0
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It's just not enough atmosphere to be able to make this detection.
speaker_0
happy
en
But the other possibility is that it's actually a very thick atmosphere, like Venus, but just such a thick layer of clouds at the top that it's obscuring any of the elements underneath.
speaker_0
angry
en
And we didn't get any detection of carbon dioxide or methane or water vapor in the atmosphere.
speaker_0
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It's at best inconclusive, and at worst, there's just no atmosphere there at all.
speaker_0
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But it's still early days and astronomers are still developing their techniques on how to be able to make these kinds of observations.
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And I had a fantastic interview with Megan Giacaluca earlier this year, where she went through each of the planets in order and gave us sort of a sneak peek of what we might expect with TRAPPIST-1d.
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Stay tuned.
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But if you want more information, we've got a story about this by Evan Goff.
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[Digital screen click] Now, speaking of TRAPPIST-1, we've got more information about the star itself, and this is probably the biggest challenge that astronomers are dealing with, is that because TRAPPIST-1 is a flare star, in other words, it puts out a lot of very powerful flares, very active, it's really difficult to distinguish what is the signal of the light that's coming from the planets around
speaker_0
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Once you get a sense of just how active the star is, then you can set that as a baseline to then tease out the atmospheric information of the planets in orbit around it.
speaker_0
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And we know that the star is covered by various magnetic features.
speaker_0
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You've got sunspots, you've got faculae, you've got w- areas of convection and that magnetic fields that are twisting and turning, and this is all contributing to the changes in brightness of the star.
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When are we seeing a flare or some kind of magnetic event on the surface of the star?
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[static] All right, let's move on to Comet 3I Atlas, which is the third interstellar object to pass through the solar system.
speaker_0
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And unlike the previous two, 'Oumuamua and Borisov, 3I Atlas, we are seeing it inbound into the inner solar system, but it is moving faster than any interstellar object that we've seen so far today.
speaker_0
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And its coma, the ball of gas and dust around the central nucleus, and the tail are starting to form.
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And normally a comet within the solar system, say from the Oort cloud, is only giving off between 3 and 5% of its surface is giving away water when it's this distance away from the sun.
speaker_0
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And so you have less heavier elements.
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This is gonna be really interesting as the comet gets closer, as it reaches higher amounts of sublimation from the radiation coming from the sun, and then astronomers are gonna be able to watch it through this entire process once it crosses that closest point and starts to move away from the sun again.
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How quickly will that tail die down?
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You'll get even more information about the star system that the comet came from.
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One other thing is that normally at this point when you see a comet, you see cyanogen gas coming off a comet.
speaker_0
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But normally at this point, you see cyanogen gas coming off of the comet, and yet so far, we don't see any of that gas.
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We've got a longer story about that by Andy Thomas Wick.
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[static] And, of course, the Hubble Space Telescope has joined in the fun and taken its first images of Comet 3I Atlas.
speaker_0
angry
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So here is your picture of 3I Atlas taken by Hubble, and this picture was taken at 3.
speaker_0
angry
en
All of this gas and dust is starting to surround the central nucleus of the comet.
speaker_0
neutral
en
And of course, as we said, a lot of this, a surprising amount of this, is water, and you're starting to see that tail start to form, and this is just getting bigger and bigger and bigger.
speaker_0
happy
en
As it gets closer to the sun, there's more radiation pressure, it's starting to push away this material.
speaker_0
angry
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You're gonna see that big, wonderful tail from an interstellar object.
speaker_0
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So thanks to Hubble, we're learning a ton more about this.
speaker_0
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And again, like we're still, you know, it's not gonna get to its closest point until October.
speaker_0
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We've got lots more time to study this object as it gets closer and closer and then gets farther and farther.
speaker_0
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[static] All right, let's go back to talking about little red dots.
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angry
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What do we know about them?
speaker_0
angry
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They are bright and they are early.
speaker_0
angry
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They're within the first billion years after the Big Bang, and they're putting out a surprising amount of radiation in a very tight place.
speaker_0
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And so how do you get that much radiation from such a small grouping?
speaker_0
angry
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Like they probably have about one tenth the size of a galaxy like the Milky Way.
speaker_0
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One possibility is that you've got a supermassive black hole that is starting to feed and is putting out large amounts of radiation.
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The other possibility is that you've just got a very compact galaxy where you've got lots of stars in a small area.
speaker_0
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But as we talked about last week, if it is a supermassive black hole, not only would you expect to see large amounts of the radiation seen by Webb, but you would detect the radiation with other telescopes in other wavelengths, like in x-rays, and we don't see that.
speaker_0
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en
And so if these things are rotating very quickly, which is what is more common, then you get this centripetal outward force that causes the galaxy and the stars to get more distributed.
speaker_0
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en
And so that might help explain why you can get all those stars that much closer together.
speaker_0
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You know, the, the quest to understand these little red dots goes on, and we still have decades left to try and figure this out before we lose Webb.
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And we've got a story on this from Mark Thompson.
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Just for comparison, the supermassive black hole at the heart of the Milky Way, Sgr A*, contains 4.
speaker_0
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There's probably 100 million solar mass black hole at the heart of Andromeda, and astronomers have found ones that have billions of times the mass of the sun.
speaker_0
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And now they think they found the most massive, one with $36-Billion times the mass of the sun.
speaker_0
angry
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And the gravity around the cosmic horseshoe is so strong that it has a beautiful Einstein lens surrounding it, where you've got almost this perfect circle of gravitational lensing around this galaxy.
speaker_0
happy
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Astronomers have used several methods to try to measure the mass of the black hole at the heart of this galaxy.
speaker_0
neutral
en
And so one method is that they measure the pathways that the light is taking, that as it gets closer to the center of the galaxy, it's pulled by the super massive black hole, and that allows you to measure how much mass is pulling on that light.
speaker_0
happy
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The other method is to be able to actually measure the movements of the stars at the center of the galaxy.
speaker_0
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And they're going very fast.
speaker_0
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In fact, this is how they discovered the super massive black hole at the heart of the Milky Way.
speaker_0
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They did the same thing with the cosmic horseshoe and measured the stars moving 400 kilometers per second around nothing.
speaker_0
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I'm sure this record will be broken again, but still, uh, very interesting.
speaker_0
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And you can learn more about the method they used to figure this out by reading the story from Evan Gough.
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[tape scratching] When our sun dies, it will become a white dwarf star.
speaker_0
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And that accounts for about 50% the mass of the sun.
speaker_0
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And if a white dwarf eventually feeds off some partner star and gets up to 1.
speaker_0
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So how did it get that massive?
speaker_0
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Well, one possibility is that it fed off some partner star and isn't doing that anymore.
speaker_0
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But the other possibility is that it merged with another white dwarf star, and some really valuable clues there.
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When astronomers observed this white dwarf, they detected the presence of carbon in the atmosphere of the star.
speaker_0
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But not only do you see carbon, you see other heavier elements, like silicon or neon.
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But in this case, they didn't find those heavier elements.
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And so it appears that you got two white dwarfs that merged to become a 1.
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[tape scratching] Every week we do a vote on our channel where you tell us what you thought was the best space news story of the week, and the winner this week was, what?
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What a surprise.
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[children cheering] Planet found at Alpha Centauri.
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[mouse clicking] Click on the notifications bell [bell ringing] and then train the algorithm.
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[tape scratching] On to Mars.
speaker_0
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One of the big challenges in driving a rover round on Mars is the regolith, and we learned this when NASA's Spirit Rover got stuck in the sand as it was trying to go across an area on Mars.
speaker_0
angry
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Its wheels got stuck, it wasn't able to point its solar panels towards the sun, and then it wasn't able to keep itself warm during the night on Mars, and it died.
speaker_0
neutral
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So don't get caught in the sand is like rule number one for Mars rover drivers.
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Does that look like sand?
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Let's avoid it.
speaker_0
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Try to stay on the rock.
speaker_0
angry
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You can reduce the weight of your rover.
speaker_0
angry
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You know, you tie ropes to it and then it appears like it's one third the normal weight is what it would feel like when it's on Mars.
speaker_0
neutral
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But you can't change the weight of the individual particles of the sand, and the sand changes differently when it's in a lower gravity environment.
speaker_0
angry
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And so researchers are now trying to split the difference.
speaker_0
angry
en
They've developed a really cool simulation on computer where they simulate the effect of a rover going on sand.
speaker_0
angry
en
End of preview. Expand in Data Studio

test4

This is a merged speech dataset containing 345 audio segments from 2 source datasets.

Dataset Information

  • Total Segments: 345
  • Speakers: 7
  • Languages: en
  • Emotions: neutral, sad, angry, happy
  • Original Datasets: 2

Dataset Structure

Each example contains:

  • audio: Audio file (WAV format, 16kHz sampling rate)
  • text: Transcription of the audio
  • speaker_id: Unique speaker identifier (made unique across all merged datasets)
  • emotion: Detected emotion (neutral, happy, sad, etc.)
  • language: Language code (en, es, fr, etc.)

Usage

Loading the Dataset

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Codyfederer/test4")

# Access the training split
train_data = dataset["train"]

# Example: Get first sample
sample = train_data[0]
print(f"Text: {sample['text']}")
print(f"Speaker: {sample['speaker_id']}")
print(f"Language: {sample['language']}")
print(f"Emotion: {sample['emotion']}")

# Play audio (requires audio libraries)
# sample['audio']['array'] contains the audio data
# sample['audio']['sampling_rate'] contains the sampling rate

Alternative: Load from CSV

import pandas as pd
from datasets import Dataset, Audio, Features, Value

# Load the CSV file
df = pd.read_csv("data.csv")

# Define features
features = Features({
    "audio": Audio(sampling_rate=16000),
    "text": Value("string"),
    "speaker_id": Value("string"),
    "emotion": Value("string"),
    "language": Value("string")
})

# Create dataset
dataset = Dataset.from_pandas(df, features=features)

Dataset Structure

The dataset includes:

  • data.csv - Main dataset file with all columns
  • *.wav - Audio files in the root directory
  • load_dataset.txt - Python script for loading the dataset (rename to .py to use)

CSV columns:

  • audio: Audio filename (in root directory)
  • text: Transcription of the audio
  • speaker_id: Unique speaker identifier
  • emotion: Detected emotion
  • language: Language code

Speaker ID Mapping

Speaker IDs have been made unique across all merged datasets to avoid conflicts. For example:

  • Original Dataset A: speaker_0, speaker_1
  • Original Dataset B: speaker_0, speaker_1
  • Merged Dataset: speaker_0, speaker_1, speaker_2, speaker_3

Original dataset information is preserved in the metadata for reference.

Data Quality

This dataset was created using the Vyvo Dataset Builder with:

  • Automatic transcription and diarization
  • Quality filtering for audio segments
  • Music and noise filtering
  • Emotion detection
  • Language identification

License

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Citation

@dataset{vyvo_merged_dataset,
  title={test4},
  author={Vyvo Dataset Builder},
  year={2025},
  url={https://huggingface.co/datasets/Codyfederer/test4}
}

This dataset was created using the Vyvo Dataset Builder tool.

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