π₯πͺ Obliviate Shredder π is a secure anti-forensics tool that obliterates files and folders beyond recovery. Inspired by the "Obliviate" spell from Harry Potter, this tool ensures that no digital trace remains after shredding.
Check it out: https://github.com/tsumarios/Obliviate-Shredder
#cybersecurity #privacy #antiforensics #shred #digitaltraces #python #script
@shansterable β
And btw. any hint how to help from abroad without hurting you personally #digitaltraces would be appreciated.
Bc you know best how..
...and it's never enough being against something.
β
edit: All this (on a global scale) is only to the advantage of antidemocratic systems/countries of all sorts.
"Divide and conquer" is such an old recipe.π
The audio features of sleep music: Universal and subgroup characteristics
In this groundbreaking study, researchers elucidated the characteristics of music associated with sleep by extracting audio features from a large number of tracks retrieved from sleep playlists at the global streaming platform, Spotify. The study found that, compared to music in general, sleep music tends to be softer, slower, and more often instrumental, without lyrics, and played on acoustic instruments. However, despite these common characteristics, the study also revealed a large amount of variation in sleep music, which clustered into six distinct subgroups.
Interestingly, three of the subgroups included popular tracks that were faster, louder, and more energetic than the average sleep music. These findings shed new light on the audio features of sleep music and highlight the individual variation in the choice of music used for sleep.
Using digital traces, the researchers were able to determine the universal and subgroup characteristics of sleep music in a unique, global dataset, advancing our understanding of how humans use music to regulate their behavior in everyday life. This study provides important insights into the powerful impact of music on sleep, and opens the door to new research into the therapeutic potential of music for promoting healthy sleep patterns.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0278813
#Sleep #Music #Audio #Global #Dataset #Spotify #Therapeutic #Lullabies #Instrumental #SleepScience #MusicTherapy #SleepBetter #Relaxation #AcousticMusic #Playlist #Insomnia #MentalHealth #Wellness #HealthyHabits #Research #SoundTherapy #GlobalResearch #SleepCycle #SleepDisorders #DigitalTraces #BehavioralScience #CognitiveFunction
Throughout history, lullabies have been used to help children sleep, and today, with the increasing accessibility of recorded music, many people report listening to music as a tool to improve sleep. Nevertheless, we know very little about this common human habit. In this study, we elucidated the characteristics of music associated with sleep by extracting audio features from a large number of tracks (N = 225,626) retrieved from sleep playlists at the global streaming platform Spotify. Compared to music in general, we found that sleep music was softer and slower; it was more often instrumental (i.e. without lyrics) and played on acoustic instruments. Yet, a large amount of variation was present in sleep music, which clustered into six distinct subgroups. Strikingly, three of the subgroups included popular tracks that were faster, louder, and more energetic than average sleep music. The findings reveal previously unknown aspects of the audio features of sleep music and highlight the individual variation in the choice of music used for sleep. By using digital traces, we were able to determine the universal and subgroup characteristics of sleep music in a unique, global dataset, advancing our understanding of how humans use music to regulate their behaviour in everyday life.
Johannes Breuer
Mario Raciti π§π‘οΈ
Gondor
personally