Tootfinder

Sources: Nigeria detains two senior Binance executives who flew to the country following its decision last week to ban several crypto trading websites (Financial Times)
https://t.co/aurcPCtF8F

I wish I could convey how awesome it could be to appreciate the come up to success it would be with other people instead of focusing on the people that disowned me and discarded me during my success. I'm on the way up and the following people have helped me: <null> Success is important, and I plan to take all of you people that have taken me up with me. <still null>

Local Fourier uniformity of higher divisor functions on average
Mengdi Wang
https://arxiv.org/abs/2402.18342 https://arxiv.org/pdf/24…

Local Fourier uniformity of higher divisor functions on average
Let $τ_k$ be the $k$-fold divisor function. By constructing an approximant of $τ_k$, denoted as $τ_k^*$, which is a normalized truncation of the $k$-fold divisor function, we prove that when $\exp\left(C\log^{1/2}X(\log\log X)^{1/2}\right)\leq H\leq X$ and $C>0$ is sufficiently large, the following estimate holds for almost all $x\in[X,2X]$: \[ \Big|\sum_{x

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

Mastodon is predicated on community instances, and built for following/engagement with hashtags over accounts.
But if we've learnt anything from Late Capitalism, is that just because something is not needed it doesn't mean you can't build your whole business model around it.
🤦‍♂️
Newsmast brings curated 'communities' to the open source Twitter/X alternative Mastodon | TechCrunch

“…the problem, for viewers, isn’t wokeness run amok; it’s the incoherence of the world we are watching. We see an African man solving crimes in a rural English village of the 1950s, as the sun sets on the empire — yet his race is barely mentioned or considered and never makes any material difference in his experience.”

Hollywood’s New Fantasy: A Magical, Colorblind Past
Films and TV shows keep reimagining history as a multiracial dream world. Is that really a step forward?

"The Facebook Pages of national news outlets lost approximately 64% of their Facebook engagement following the end of news availability for Canadian users. Local news outlets lost approximately 85%. Almost half of all local news outlets stopped posting on Facebook entirely in the four months following the ban."
And user used workarounds hurting newspaper visibility. Bad choice. But going to be repeated in CH 🤦

GenAI Distortion: The Effect of GenAI Fluency and Positive Affect
Xiantong Yang, Mengmeng Zhang
https://arxiv.org/abs/2404.17822 https://

GenAI Distortion: The Effect of GenAI Fluency and Positive Affect
The introduction of generative artificial intelligence (GenAI) into educational practices has been transformative, yet it brings a crucial concern about the potential distortion of users' beliefs. Given the prevalence of GenAI among college students, examining the psychological mechanisms that lead to GenAI distortion from both technological factors and the individual's psychological processes is a critical priority. A mixed-methods approach is employed to test the proposed hypotheses. Study 1 …

Filmmakers, critics, and users detail why Prime Video failed in Africa; Amazon laid off staff and scaled back operations on the continent in January 2024 (Jesusegun Alagbe/Rest of World)
https://restofworld.org/2024/amazon-prime-video-africa-layoffs/

How Prime Video failed so spectacularly in Africa
Filmmakers, critics, and users blame the platform’s struggle in Africa on poor user experience, a lack of local content, and mediocre publicity.

Filmmakers, critics, and users detail why Prime Video failed in Africa; Amazon laid off staff and scaled back operations on the continent in January 2024 (Jesusegun Alagbe/Rest of World)
https://restofworld.org/2024/amazon-prime-video-africa-layoffs/

How Prime Video failed so spectacularly in Africa
Filmmakers, critics, and users blame the platform’s struggle in Africa on poor user experience, a lack of local content, and mediocre publicity.