Tootfinder

Want a long and healthy life?
You might want to follow the example of Italy’s Emma Maria Mazzenga.

But following her won’t be easy.

Almost 93, Mazzenga may be the fastest female nonagenarian on Earth.
She holds the 90-to-94 age-group world records in the outdoor 200 meters and the 60, 200- and 400-meter indoor events.
At 92, she’s as fit as someone half her age

At 92, she’s as fit as someone half her age
What science is learning from the muscles of Emma Mazzenga, the fastest female nonagenarian on Earth and holder of multiple sprinting world records.

This was a nice ride. Some sections involved pushing the bike. And some steep parts came a bit surprising. But overall it was nice with some quite challenging sections. It was a loop that I wanted to try since quite a while.
And it's a new elevation record since I own the Garmin 🎉
Just my #garmin now suddenly refuses to connect to my phone. 😵‍💫 Factory reset, all suggestions fro…

"Data from the UN shows that the money spent on supplies of folic acid, which can help reduce the risk of anaemia and then possible haemorrhage or stillbirth, is falling – at least in part thanks to aid cuts."
Aid cuts are making tablets needed to help fight stillbirths and mothers dying harder to buy | The Independent
https://www.independent.co.uk/news/health/women-birth-death-aid-cuts-un-b2990716.html

60 years ago tonight, the grateful dead in #SanFrancisco at the fillmore auditorium with the mothers of invention & quicksilver messenger service. the #bbc films properly absurd black & white segment. last known version of lesh’s “mindbender,” aka “confusion’s prince.”

Theoretical derivation of blood velocity from TOF-MRA based artery centerline
Abrar Faiyaz
https://arxiv.org/abs/2607.16498 https://arxiv.org/pdf/2607.16498 https://arxiv.org/html/2607.16498
arXiv:2607.16498v1 Announce Type: new
Abstract: Time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for structural vascular imaging, but extracting functional hemodynamics like blood velocity typically requires supplementary phase-contrast scans. This study proposes a novel, physics-informed computational framework to extract variable fluid velocity directly from standard TOF-MRA signal profiles. We analytically expand the Bloch equations into Bloch-McConnell flow equations, establishing a mathematical relationship between the spatial decay of longitudinal magnetization and fluid velocity. To validate this derivation and overcome the limitations of constant-velocity assumptions, a MATLAB simulation framework was developed to model fluid flow in two variable-geometry flowing tube cases i.e continuous tapering and focal stenosis -under synthetic scanner noise. A global inverse optimization approach utilizing Dual-Tikhonov regularization was deployed to stably invert the ill-posed transit time integral, actively penalizing high-frequency numerical ringing while preserving structural curve stiffness. The computational sim-ulations successfully recovered ground-truth point-wise velocities, accurately tracking gradual hemodynamic accelerations and sharp stenotic jets. This theoretical framework provides a robust mathematical proof-of-concept that quantitative, localized functional hemodynamic metrics can be extracted from standard structural MRA imaging, estab-lishing a foundation for advanced flow quantification without requiring additional scan time.
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Text2Villa: Hierarchical Generation of 3D Indoor Environments with Physics-Aware Analysis-by-Synthesis
Xiang Tang, Ruotong Li, Xiaopeng Fan
https://arxiv.org/abs/2607.17145 https://arxiv.org/pdf/2607.17145 https://arxiv.org/html/2607.17145
arXiv:2607.17145v1 Announce Type: new
Abstract: Generating 3D indoor scenes from natural language holds tremendous potential, yet existing methods predominantly fail to generate multi-room structures with vertical connectivity and arbitrary polygonal boundaries. Furthermore, they lack a deep grounding in continuous 3D physical laws, leading to severe geometric penetrations and floating artifacts. In this work, we propose Text2Villa, a novel hierarchical generative framework. At the macro level, we construct a multi-story dataset to fine-tune an autoregressive layout generator, ensuring the direct parsing of text into 3D building foundations featuring polygonal boundaries and multi-story connectivity. To enforce physical laws during micro-level asset arrangement, we introduce the Affordance-driven Physical-Semantic Scene Graph (A-PSSG) to explicitly abstract physical affordances (such as support surfaces and containment cavities) into node attributes, establishing strict geometric and semantic edge constraints. Guided by the A-PSSG, we formulate scene instantiation as a constrained closed-loop optimization problem following the analysis-by-synthesis paradigm. By integrating an underlying geometric collision detection engine with the high-level semantic reasoning of multimodal large language models (MLLMs), our heuristic solver dynamically executes physics-aware actions under the observation-evaluation-modification mechanism to effectively resolve mesh collisions, floating artifacts, and fine-grained cavity containment failures. Extensive experiments demonstrate that Text2Villa outperforms previous methods across various metrics, robustly generating high-fidelity and physically plausible villa-level 3D environments from text, thereby providing a reliable and interactive 3D content foundation for downstream applications.
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