Results 111 to 120 of about 5,143,841 (243)

Artificial Intelligence‐Driven Extraction of Patient‐Reported Pain Outcomes in Osteoarthritis Using Large Language Models

Arthritis Care &Research, Accepted Article.
Objective Patient‐reported outcome measures (PROMs) are central to assessing symptom burden and treatment response in Osteoarthritis (OA) but are often embedded in unstructured clinical notes. We evaluated whether prompt‐engineered large language models (LLMs) could accurately extract or infer pain scores on a 0‐10 scale from routine OA clinical ...
Jainesh Doshi, Stephen Batter, Yiyuan Wu, William Salerno, Alice Santilli, Sandhya Kannayiram, Susan Goodman, Bella Mehta   +7 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Influence of Scan Strategies in Electron Beam Powder Bed Fusion on Solidification, Microstructure, and High‐Temperature Compressive Properties of γ′‐Strengthened Inconel 738LC

Advanced Engineering Materials, EarlyView.
Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati, Karthik Kumar Banku, Prasanth Bondi, Ivan Zhirnov, Yangyiwei Yang, Gordon Schmidt, Jürgen Christen, Georg Hasemann, Manja Krüger, Bai‐Xiang Xu, Bilal Gökce, Silja‐Katharina Rittinghaus   +11 more
wiley   +1 more source

Cryogenic Deformation Behavior of TiAl and Insights Into Embrittlement After High‐Temperature Exposure Combined With Secondary Ion Mass Spectroscopy of Near Surface Chemistry

Advanced Engineering Materials, EarlyView.
Near‐surface deuterium enrichment profiles for different microstructural types of TiAl after exposure at 700 °C in a heavy water‐containing environment. The deuterium levels are significantly higher than expected from natural occurrence, indicating that the heavy water dissociated during the exposure treatment and entered the specimens.
Jonathan D. H. Paul, Alexander Welle, Dirk Matthiessen, Michael Oehring, Fritz Appel, Florian Pyczak   +5 more
wiley   +1 more source

Mitigating Creep Anisotropy and Enhancing Performance in Additively Manufactured Ni‐Based Superalloys: A Review

Advanced Engineering Materials, EarlyView.
Additive manufacturing introduces pronounced microstructural and crystallographic anisotropy in Ni‐based superalloys, resulting in orientation‐dependent creep deformation and damage. This review identifies the key microstructural origins of creep anisotropy, examines their influence on dominant deformation mechanisms, and highlights processing ...
Chandan Kumar, Shobhit Pratap Singh, Gaurav Mohanty, Praveen Kumar   +3 more
wiley   +1 more source

Constructing Time-Frequency Dictionaries for Source Separation via Time-Frequency Masking and Source Localisation

, 2009
We describe a new localisation and source separation algo- rithm which is based upon the accurate construction of time-frequency spatial signatures. We present a technique for constructing time-frequency spatial signatures with the required accuracy ...
Pearlmutter, Barak A.,, de Fréin, Ruairí,, Rickard, Scott T.,   +2 more
core  

Source-separated susceptibility tensor MRI reveals paramagnetic and diamagnetic anisotropy in a postmortem chimpanzee brain

Communications Biology
Abstract Magnetic susceptibility in brain white matter is anisotropic because of the ordered arrangement of myelin lipids, whereas paramagnetic iron is generally not considered a source of susceptibility anisotropy.
Jingjia Chen, Dimitrios G. Gkotsoulias, Jenny E. Jaffe, Tobias Gräßle, Carsten Jäger, Zoro B. Goné Bi, Catherine Crockford, Roman Wittig, Harald E. Möller, Chunlei Liu   +9 more
openaire   +1 more source

Microstructure‑Dependent Phase Transformations Under High‑Pressure Laser Heating in Additively Manufactured AlCrFe2Ni2

Advanced Engineering Materials, EarlyView.
Additively manufactured AlCrFe2Ni2 with contrasting BCC/B2‐dominant and lamellar FCC + BCC/B2 microstructures exhibits the same pressure‐induced BCC/B2 → HCP transformation. Under laser heating at high pressure, HCP is destabilized, and a cubic BCC/B2 + FCC assemblage is recovered, while the lower‐scan‐speed microstructure transforms at a lower ...
Raimundas Sereika, Hunter Kantelis, Yogesh K. Vohra, Shengbiao Zhang, Wuxian Yang, Wen Chen   +5 more
wiley   +1 more source

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

Advanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad, Saurabh Thorat, Andre Loch Gesing, Dominik Huber, Christopher Zellner, Patrick Egger, Georg Pfusterschmied, Ulrich Schmid, Michael Schneider   +8 more
wiley   +1 more source