Results 21 to 30 of about 1,344 (211)

Longitudinal Relationship Between Pain and Depression in People With Inflammatory Arthritis: A Narrative Review

Arthritis Care &Research, EarlyView.
As many patients with inflammatory arthritis (IA) have chronic pain, understanding how to best assess and manage pain in IA is a priority. Comorbid depression is prevalent in adults with IA, affecting 15% to 39% of people. Although pain and depression are thought to be associated in IA, this concept is largely based on cross‐sectional data.
Natasha Cox, Saeed Farooq, Helen Twohig, Ian C. Scott   +3 more
wiley   +1 more source

Time trends and predictors of gout remission over six years

Arthritis Care &Research, Accepted Article.
Objectives This study aims to describe the trends in remission rates over six years of follow‐up among people with gout taking urate‐lowering therapy (ULT), and to identify variables that predict remission. Methods A post hoc analysis was conducted using data from the Cardiovascular Safety of Febuxostat or Allopurinol in Patients with Gout (CARES ...
Adwoa Dansoa Tabi‐Amponsah, Sarah Stewart, Greg Gamble, Lisa K Stamp, William J Taylor, Nicola Dalbeth   +5 more
wiley   +1 more source

Numerical Studies of Influencing Factors on the Homogeneity of the Powder Mixture during the Powder Spreading Process of Powder Bed Fusion–Laser Beam/Metal

Advanced Engineering Materials, EarlyView.
AISI 304L stainless steel powder is mixed with silicon nitride (Si3N4) powder and processed by PBF‐LB/M, allowing partial retention of Si3N4. The numerical approach effectively predicts the Si3N4 powder homogeneity and N content distribution on the powder bed. Recent studies have focused on the alloying of nitrogen (N) in high‐alloy stainless steels by
Yuanbin Deng, Ziping Sang, Jiali Zhang, Felix Radtke, Louis Becker, Simone Herzog, Sebastian Weber, Christoph Broeckmann   +7 more
wiley   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes [PDF]

, 2021
Veit Wild, Motonobu Kanagawa, Dino Sejdinović   +2 more
openalex   +3 more sources

A Novel Approach on Rapid Alloy Development of Tool Steels for Laser Powder Bed Fusion by In Situ Alloying

Advanced Engineering Materials, EarlyView.
A novel approach for alloy development in laser powder bed fusion is introduced. Instead of producing massive samples of one composition at a time, prepressed powder bed samples produced from powder mixtures are processed. Guidelines for the selection of precursor powders are developed.
Felix Großwendt, Anna Strauch, Jonathan Lentz, Arne Röttger, Rainer Fechte‐Heinen, Sebastian Weber, Werner Theisen   +6 more
wiley   +1 more source

Nanoparticle‐Coated X2CrNiMo17‐12‐2 Powder for Additive Manufacturing – Part I: Surface, Flowability, and Optical Properties of SiC, Si, and Si3N4 Coated Metal Powders

Advanced Engineering Materials, EarlyView.
Herein, silicon‐based nanoparticle coatings on X2CrNiMo17‐12‐2 metal powder are presented. The coating process scale, process parameters, nanoparticle size (65–200 nm) as well as the coating amount are discussed regarding powder properties. The surface roughness affects the flowability, while reflectance depends on the coating material and surface ...
Arne Lüddecke, Nick Hantke, Harald Zetzener, Jan T. Sehrt, Arno Kwade   +4 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Statistical Distributions of Morphologically Classified Defects in Metal Additive Manufacturing with Implications for Fatigue Life Prediction

Advanced Engineering Materials, EarlyView.
Morphological features of three defect types in metal additive manufacturing (AM)—lack of fusion, keyhole, and gas‐entrapped pores—are statistically characterized using best‐fit distributions evaluated via coefficient‐of‐determination, Kolmogorov–Smirnov test, and quantile–quantile plots.
Ahmad Serjouei, Golnaz Shahtahmassebi
wiley   +1 more source

Performance Comparison of Surface Sensitizers for Diode Laser Powder Bed Fusion of Polyamide 12

Advanced Engineering Materials, EarlyView.
Laser‐generated nanoparticles transform standard PA12 powders into high‐performance, dye‐free feedstocks for diode laser 3D printing. Despite identical absorbance at 808 nm, CuS, LaB6, and CB coatings reveal striking differences in fusion and strength—unlocking new design space for recyclable, industrial‐grade polymers.
Michael Willeke, Alexander Sommereyns, Simon Leupold, Arne Lüddecke, Arno Kwade, Nick Hantke, Jan T. Sehrt, Michael Schmidt, Anna R. Ziefuss, Stephan Barcikowski   +9 more
wiley   +1 more source