A pie chart where the vast majority of the circle is filled with a space nebula background, labeled "Shit you don't know you don't know." A small blue sliver is labeled "Shit you know you don't know," and a tiny green line represents "Shit you know."

You see, until a few years ago, it was thought that certain pains were of psychosomatic origin. Perfect test results, no instrumental readings, impossible to explain: invented, self-induced. Then we understood that they weren't invented, but real - today we know how to treat them, with good results, restoring a normal life to those who suffer from them. We are not yet able to detect the markers that tell us which nerve endings, transmitters, or whatever element gives or causes these pains, but we know they exist and we know how to treat them. Science will explain this too.

Passion has no age. And that look, that spark, that satisfaction of having identified something others had ignored - I won't forget it easily.

TL;DR; "Humans aren’t very efficient movers—until you put us on a bicycle, when we become some of the most energy-efficient land travelers in the animal kingdom."

SimpleFold atteint 95% des performances d’AlphaFold2 tout en étant infiniment plus léger. En effet, AlphaFold nécessite des supercalculateurs avec des GPU à 20 000 balles pièce alors SimpleFold, lui tourne tranquille sur un MacBook Pro M2 avec 64GB de RAM.

Et c’est super cool parce que prédire la structure d’une protéine, c’est pas juste un truc de geek pour s’amuser. C’est LA base pour créer de nouveaux médicaments, comprendre des maladies, développer des vaccins… Jusqu’à présent, seuls les gros labos avec des budgets de malade pouvaient se permettre de faire ça, c’est pourquoi SimpleFold change complètement la donne en rendant cette technologie accessible à n’importe quel chercheur avec un MacBook.

Le document est disponible sur https://arxiv.org/abs/2509.18480

CauseNet aims at creating a causal knowledge base that comprises all human causal knowledge and to separate it from mere causal beliefs, with the goal of enabling large-scale research into causal inference.

Scientists have developed a breakthrough food supplement that could help save honeybees from devastating declines. By engineering yeast to produce six essential sterols found in pollen, researchers provided bees with a nutritionally complete diet that boosted reproduction up to 15-fold. Unlike commercial substitutes that lack key nutrients, this supplement mimics natural pollen’s sterol profile, giving bees the equivalent of a balanced diet.

A priori, exposer quelqu'un souffrant du mal des transports à un son à 100 hertz suffit à alléger son inconfort.

(via https://nicolas-delsaux.hd.free.fr/Shaarli/shaare/NtDtJw)

Pour aider à la classification des galaxies des images du téléscope spatial Euclid: https://www.zooniverse.org/projects/zookeeper/galaxy-zoo/classify?language=fr

Why research needs free open source softwares.

It shows two things:

• Science must not use commercial software
• Science is underpaid if it has to use pirated software

(via https://nicolas-delsaux.hd.free.fr/Shaarli/shaare/eptdLQ)

Innovations and progress since 1500 per theme

Si vous voulez une réparation très rapide et très solide de quoi que ce soit que vous êtes en train de réparer à la colle : utilisez du fil de coton ou même du coton sous forme de ouate. Ensuite, imbibez ça de superglu et laissez durcir. La réparation sera dure comme la pierre.

Les matériaux composites sont donc excellents: un dire mais cassant et l'autre souple mais résistant. L'exemple le plus courant est le béton armé, comme le verre feuilleté.

OpenAlex est une base de données bibliographiques entièrement ouverte indexant fin 2023 environ 250 millions de travaux scientifiques, 90 millions d’auteurs, 100 000 institutions et 32 000 financeurs.

For papers submitted since the 1st December 2023

HTML is not replacing PDF but will be an additional format available for arXiv users.

The goal is to convert all papers on arxiv to HTML files.
It will moreover allow easier analysis through HTML parsing.