Results 101 to 110 of about 4,718 (211)
Complete 146-work bibliographic compilation and seven-domain mathematical synthesis of Stanford mathematician R. James (“Jim”) Milgram (b. 1939), unifying his sixty-year corpus into the executable milgramsuite topological discovery engine and the solidSF + Jesse CAD/CAE/CAM verification stack.This monograph compiles and indexes 146 ...
Norris, Andy +1 more
openaire +3 more sources
An effective deep learning algorithm for medical image registration. [PDF]
Deng J +5 more
europepmc +1 more source
Origami turns a single silicone chamber into three different soft fluidic actuators. Crease angles alone decide whether it elongates, bends, or twists, and the fully folded chambers are cast monolithically in one day. Below 15 kPa, they reach 268% axial stretch, 72° bending, and 55° twist—no strain‐limiting layers, no rigid reinforcements, no vacuum ...
Alexia Le Gall +4 more
wiley +1 more source
What topological and geometric structure do biological foundation models learn? Evidence from 141 hypotheses. [PDF]
Kendiukhov I.
europepmc +1 more source
## Binary Failure → Geometry Solution **Analysis of Findings:** The search results reveal a critical gap: while machine learning has made inroads into *applied* topology (e.g., persistent homology for data analysis), the *core unsolved problems* in geometric topology—like the inscribed square/rectangle problem—remain untouched by statistical methods.
openaire +1 more source
Objectives and Key Results–Driven Multiagent Framework for Mechanical Design and Simulation
Objectives and key results (OKR)‐agent, an OKR‐driven multiagent framework, turns a plain‐language engineering goal into completed mechanical simulations. Three peer agents—supervisor, modeler, and simulator—share a compact board of OKR and coordinate external molecular dynamics (MD) and finite‐element solvers through a standardized tool interface. The
Jie Tian +10 more
wiley +1 more source
Horizon data: existence results and a near-horizon equation on general null hypersurfaces. [PDF]
Manzano M, Mars M.
europepmc +1 more source
An automated, AI‐powered system generates a 3D liver fat volumetric map for precise fat fraction quantification from MRI. By overcoming manual analysis constraints, it provides high‐fidelity spatial characterization of steatosis. This graphical abstract highlights a clinically robust framework that enables efficient, anatomically informed assessment ...
Bincan Deng +9 more
wiley +1 more source

