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#Cure

7 posts4 participants0 posts today
Arrivare da social come Facebook o Instagram, dove ti bombardano di commenti anche non richiesti, può rendere l’impatto con PixelFed un po’… stordente.

Qui l’interazione è diversa. Più contenuta. Non scontata.
A volte arriva spontanea, altre devi cercarla. Ma non è mai forzata, e forse è proprio questo il bello.

Io però sono fatta così: se una foto, un testo, un’immagine mi colpisce, commento.
Mi viene naturale. È un gesto fisico, come battere le mani velocemente o sfarfallare.
È il mio modo per dire: grazie per aver condiviso questa cosa bella, anche con me.

All’inizio ero un po’ spaesata. Ma venivo da un anno intero senza social, senza interazioni.
Quindi PixelFed è stato quasi un rientro gentile.
Un posto in cui la socialità ha un altro ritmo.

E forse in fondo va bene così. Perché qui, più che socializzare, si impara a condividere con misura. Come chi parla sottovoce.

Assoli Notturni è online.
Link nei commenti
Buonanotte 🌌

#assolinotturni #michiyospace #musica #cure

“Autistic Inclusive Meets: the grassroots group fighting Autistic abuse while uplifting the community”

by Hannah Sharland in The Canary @thecanaryuk

“Autistic Inclusive Meets (AIM) has campaigned for years for a new law to make claiming a treatment or intervention as an autism ‘cure’, illegal”

thecanary.co/long-read/2025/04

Canary · Autistic Inclusive Meets: the grassroots group fighting Autistic abuse while uplifting the communityAutistic Inclusive Meets (AIM) is a grassroots community group that’s been taking on the ‘cure culture’ around neurodivergence
#Press#UK#AIM
arXiv.orgFrom FAIR to CURE: Guidelines for Computational Models of Biological SystemsGuidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of 'data', we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility; the clarity of model descriptions and annotations for understandability; adherence to standards and open science practices for reproducibility; and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community moves to automate as many of the guidelines as possible.