Results 151 to 160 of about 982,283 (286)

Temporal Dynamic Machine Learning Prediction of Postoperative Gastrointestinal Dysfunction Duration in Esophageal Cancer: Integrating Preoperative and Perioperative Routine Blood Temporal Data and Dynamic Ultrasonic Features. [PDF]

Int J Gen Med
Jin L, Chang Y, Liu H, Guo J.
europepmc   +1 more source

Microstructure Evolution of a VMnFeCoNi High‐Entropy Alloy After Synthesis, Swaging, and Annealing

Advanced Engineering Materials, EarlyView.
The synthesis and processing (rotary swaging and annealing) of the novel VMnFeCoNi alloy is investigated, alongside the estimation of the grain size effect on hardness. Analysis of a wide grain size range of recrystallized microstructures (12–210 µm) reveals a low annealing twin density.
Aditya Srinivasan Tirunilai, Zeki Ayrildi, Buse Şen, Maik Rajkowski, Mathias Redondo Garcia, Markus Stricker, Guillaume Laplanche   +6 more
wiley   +1 more source

mean squared error of calibration

Citation: 'mean squared error of calibration' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.10151 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms ...
openaire   +1 more source

A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
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, Sarath Menon, Raphael Röske, Johannes Steinhülb, Michael Selzer, Jan Janssen, Tilmann Hickel, Ruth Schwaiger, Jörg Neugebauer   +8 more
wiley   +1 more source

Simulation based new method for population variance using auxiliary information. [PDF]

Sci Rep
Ahmadini AAH, Semary HE, Ahmad S, Ullah K, Zahid E, Al-Moisheer AS.   +5 more
europepmc   +1 more source

Influence of Test Temperature and Test Frequency on Fatigue Life of Aluminum Alloy EN AW‐2618A

Advanced Engineering Materials, EarlyView.
The influence of test temperature and test frequency on the fatigue life of EN AW‐2618A is investigated. High‐cycle fatigue tests are performed at different test temperatures and frequencies on the 1000 h/230°C overaged state. Both test parameters reduce fatigue life due to time‐dependent damage mechanisms.
Ying Han, Julian M. Rosalie, Jan Radners, Mauro Madia, Philipp von Hartrott, Birgit Skrotzki   +5 more
wiley   +1 more source

mean squared error of prediction

Citation: 'mean squared error of prediction' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.10099 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms ...
openaire   +1 more source

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

Advanced Engineering Materials, EarlyView.
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, Steffen Brinckmann, Ruth Schwaiger   +2 more
wiley   +1 more source

Estimating the Growth Rate of a Birth and Death Process Using data From a Small Sample. [PDF]

Bull Math Biol
Heinzel CS, Schweinsberg J.
europepmc   +1 more source

Optimization of the Production of Rubber Compounds Using Mathematical Models

Advanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann   +7 more
wiley   +1 more source