Results 161 to 170 of about 258,723 (263)

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

Advanced Engineering Materials, EarlyView.
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

GR2ST: spatial transcriptomics prediction based on graph-enhanced multimodal contrastive learning. [PDF]

Bioinformatics
Zhou J, Li S, Han R, Wang X, Wang Y, Li J.   +5 more
europepmc   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

EMERALD-UI: an interactive web application to unveil novel protein biology hidden in the alternative alignment space. [PDF]

Bioinformatics
Preoteasa A, Grigorjew A, Tomescu AI, Drost HG.   +3 more
europepmc   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Lancet2: Improved and accelerated somatic variant calling with joint multi-sample local assembly graphs. [PDF]

NAR Genom Bioinform
Musunuri RL, Zhu B, Clarke WE, Hooper W, Chu T, Shelton J, Corvelo A, Chung D, Sundar S, Novak AM, Paten B, Zody MC, Robine N, Narzisi G.   +13 more
europepmc   +1 more source

The PRIMA Thesaurus for Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa, Alexey Boubnov, Dario De Angelis, Catriona Eschke, Maximilian Kabbe, Felix Kraus, Mirco Panighel, Richard Thelen, Davide Valentinis   +8 more
wiley   +1 more source

Autonomic Signature-Driven Anesthesia Depth Monitoring with Biomimetic Wearable ECG and Knowledge Graph-Augmented Deep Networks. [PDF]

Sensors (Basel)
Bao A, Ding C.
europepmc   +1 more source

Tailoring Functional Properties of Ti–Ni–Cu Shape Memory Alloy Thin Films for MEMS Actuators

Advanced Engineering Materials, EarlyView.
A comprehensive study of critical parameters required to develop well‐performing Ti–Ni–Cu thin film shape memory alloy microactuators is provided. Materials science and device integration aspects are integrated by addressing structural and physical relationships using complementary characterization techniques as well as a practical fabrication solution
Elaheh Akbarnejad, Aleksander Kostka, Gowtham Arivanandhan, Yujiao Li, Alan Savan, Manfred Kohl, Alfred Ludwig   +6 more
wiley   +1 more source

Analysis of the interaction network relationship between drugs using a graph neural network. [PDF]

Front Pharmacol
Chai Z, Wang J, Du H.
europepmc   +1 more source