Results 121 to 130 of about 571,567 (314)
KennethEnevoldsen/scandinavian-embedding-benchmark: v0.8.0
<h1>v0.8.0 (2024-01-25)</h1> <h2>Ci</h2> <ul> <li>ci: fix mispecified yaml syntax (<a href="https://github.com/KennethEnevoldsen/scandinavian-embedding-benchmark/commit/ca5567c71d3da1ec49b59c0a74b74bd85219a46e"> ...
Márton Kardos +3 more
core +1 more source
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
SkyMap: a generative graph model for GNN benchmarking
Graph Neural Networks (GNNs) have gained considerable attention in recent years. Despite the surge in innovative GNN architecture designs, research heavily relies on the same 5-10 benchmark datasets for validation.
Axel Wassington +2 more
doaj +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source
DEVELOPMENT OF A MARKET BENCHMARK PRICE FOR AGMAS PERFORMANCE EVALUATIONS
The purpose of this research report is to identify the appropriate market benchmark price to use to evaluate the pricing performance of market advisory services that are included in the annual AgMAS pricing performance evaluations.
Irwin, Scott H. +2 more
core
KennethEnevoldsen/scandinavian-embedding-benchmark: v0.9.1
<h1>v0.9.1 (2024-01-26)</h1> <h2>Fix</h2> <ul> <li><p>fix: ran swednsts and reduced dataset size (<a href="https://github.com/KennethEnevoldsen/scandinavian-embedding-benchmark/commit ...
Márton Kardos +3 more
core +1 more source
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova +2 more
wiley +1 more source
KennethEnevoldsen/scandinavian-embedding-benchmark: v0.9.0
<h1>v0.9.0 (2024-01-26)</h1> <h2>Feature</h2> <ul> <li>feat: Added performance metrics for danfever (<a href="https://github.com/KennethEnevoldsen/scandinavian-embedding-benchmark/commit ...
Márton Kardos +3 more
core +1 more source
Graphene nanoplatelet (0.1 wt.%) reinforcement significantly enhances the performance of β Ti‐28Nb‐35.4Zr alloy. Grain refinement, reduced water contact angle, and improved surface characteristics promote osteoblast adhesion and complete surface coverage after 7 days.
Khurram Munir +5 more
wiley +1 more source
In various fields of science, certain patterns are used to describe and compare the studied features and phenomena, reference points (benchmarks), e.g.: reference rates (benchmark rates), reference ratios (benchmark ratio), or comparative analyses (the ...
Agnieszka Pobłocka
doaj

