Tootfinder

“Three independent scientific studies analyze how the human brain transforms notes into feelings, a mystery that has intrigued psychologists and musicologists for decades”
https://english.elpais.com/scien…

Music scientists find the connection between music and emotion: ‘Our neurons dance to the same rhythm’
Three independent scientific studies analyze how the human brain transforms notes into feelings, a mystery that has intrigued psychologists and musicologists for decades

Im Zug: Letzte Vorbereitung für das BarCamp Flensburg. Auf allen Sketchnotes-Büchlein für den Workshop das TwitterHandle mit dem MastodonHandle überkleben.
#bcfl #bcfl24

Im Zug: Letzte Vorbereitung für das BarCamp Flensburg. Auf allen Sketchnotes-Büchlein für den Workshop das TwitterHandle mit dem MastodonHandle überkleben.
#bcfl #bcfl24

Im Zug: Letzte Vorbereitung für das BarCamp Flensburg. Auf allen Sketchnotes-Büchlein für den Workshop das TwitterHandle mit dem MastodonHandle überkleben.
#bcfl #bcfl24

Raiders’ Feelings On Free Agent RB Josh Jacobs Revealed https://www.yardbarker.com/nfl/articles/raiders_feelings_on_free_agent_rb_josh_jacobs_revealed/s1_17150_40022538

Raiders’ Feelings On Free Agent RB Josh Jacobs Revealed
Las Vegas Raiders running back Josh Jacobs is getting set to hit free agency, and the Raiders apparently want him back. However, the Raiders only want to retain Jacobs at the right price and will not be placing a franchise tag on him, according to Adam Schefter of ESPN. Jacobs’ tag would be worth a tick over $14 million in 2024, which is evidently too costly for Las Vegas’ blood. Given Jacobs’ production this past season, that does not come as much of a surprise. Injuries limited Jacobs t…

Deutschland 09 ist auch schon wieder 15 Jahre her. Das einzige Mal, als ich über einen roten #Berlinale Teppich lief.
Hier nicht zu sehen, aber immerhin die Schauspielerin, die mich spielte.
https://www.

Kitten breaking change: Route handlers, etc., now take parameter objects
Just pushed the API updates I’d posted about earlier to main and to the latest Kitten release.
This change affects:
- Route handlers (all types of routes)
- `onConnect()` handlers
- The default export on main.script.js files
I’ve updated all the examples, documentation, etc., on Kitten to use the new API but if you see anything I’ve missed, please let me know.

app
A web development kit that’s small, purrs, and loves you.

Über die von der EU verpflichtete Browser-Auswahl von iOS 17.4 habe ich über die Tage wieder #Firefox für iOS ausprobiert:
Ohne die fehlenden Browser-Add-Ons v.a. für Ad-Blocker und WebKit statt Gecko als Engine ist das nutzlos für mich. Das liegt aber mehr an Apple als an Mozilla.
Als die App mich um eine Rezension gebeten hat, habe ich das dort so geschrieben.
Darauf kam eine E-…

Self-supervised learning for classifying paranasal anomalies in the maxillary sinus
Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Lennart Maack, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer
https://arxiv.org/abs/2404.18599 https://arxiv.org/pdf/2404.18599
arXiv:2404.18599v1 Announce Type: new
Abstract: Purpose: Paranasal anomalies, frequently identified in routine radiological screenings, exhibit diverse morphological characteristics. Due to the diversity of anomalies, supervised learning methods require large labelled dataset exhibiting diverse anomaly morphology. Self-supervised learning (SSL) can be used to learn representations from unlabelled data. However, there are no SSL methods designed for the downstream task of classifying paranasal anomalies in the maxillary sinus (MS).
Methods: Our approach uses a 3D Convolutional Autoencoder (CAE) trained in an unsupervised anomaly detection (UAD) framework. Initially, we train the 3D CAE to reduce reconstruction errors when reconstructing normal maxillary sinus (MS) image. Then, this CAE is applied to an unlabelled dataset to generate coarse anomaly locations by creating residual MS images. Following this, a 3D Convolutional Neural Network (CNN) reconstructs these residual images, which forms our SSL task. Lastly, we fine-tune the encoder part of the 3D CNN on a labelled dataset of normal and anomalous MS images.
Results: The proposed SSL technique exhibits superior performance compared to existing generic self-supervised methods, especially in scenarios with limited annotated data. When trained on just 10% of the annotated dataset, our method achieves an Area Under the Precision-Recall Curve (AUPRC) of 0.79 for the downstream classification task. This performance surpasses other methods, with BYOL attaining an AUPRC of 0.75, SimSiam at 0.74, SimCLR at 0.73 and Masked Autoencoding using SparK at 0.75.
Conclusion: A self-supervised learning approach that inherently focuses on localizing paranasal anomalies proves to be advantageous, particularly when the subsequent task involves differentiating normal from anomalous maxillary sinuses. Access our code at https://github.com/mtec-tuhh/self-supervised-paranasal-anomaly

Automating Boundary Filling in Cubical Agda
Maximilian Dor\'e, Evan Cavallo, Anders M\"ortberg
https://arxiv.org/abs/2402.12169 https://

Automating Boundary Filling in Cubical Agda
When working in a proof assistant, automation is key to discharging routine proof goals such as equations between algebraic expressions. Homotopy Type Theory allows the user to reason about higher structures, such as topological spaces, using higher inductive types (HITs) and univalence. Cubical Agda is an extension of Agda with computational support for HITs and univalence. A difficulty when working in Cubical Agda is dealing with the complex combinatorics of higher structures, an infinite-dim…