Results 231 to 240 of about 806,359 (300)

β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations

Advanced Biology, Volume 9, Issue 3, March 2025.
Ammonia, detoxified by the liver into urea and glutamine, impacts autophagy differently at varying levels. Low ammonia activates autophagy via c‐Myc and β‐catenin, while high levels suppress it. Using Huh7 cells and Spf‐ash mice, c‐Myc's role in cytoprotective autophagy is revealed, offering insights into hyperammonemia and potential therapeutic ...
S. Sergio, B. Spedicato, G. Corallo, A. Inguscio, M. Greco, D. Musarò, D. Vergara, A. F. Muro, G. De Sabbata, L. R. Soria, N. Brunetti Pierri, M. Maffia   +11 more
wiley   +1 more source

Mechanochemical Synthesis and Characterization of Nanostructured ErB4 and NdB4 Rare‐Earth Tetraborides

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
ErB4 and NdB4 nanostructured powders are produced by mechanochemical synthesis. 5 h mechanical alloying and 4 M HCl acid leaching are used in the production. ErB4 and NdB4 powders exhibit maximum magnetization of 0.4726 emu g−1 accompanied with an antiferromagnetic‐to‐paramagnetic phase transition at about TN = 18 K and 0.132 emu g−1 with a maximum at ...
Burçak Boztemur, Faruk Kaya, Bora Derin, Mustafa Lütfi Öveçoğlu, Ju Li, Duygu Ağaoğulları   +5 more
wiley   +1 more source

Do feasibility studies contribute to, or avoid, waste in research? [PDF]

PLoS One, 2018
Morgan B, Hejdenberg J, Hinrichs-Krapels S, Armstrong D.   +3 more
europepmc   +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

Low‐Cost, Large‐Scale Nanoporous Metals by Mechanical Alloying, Oxide Reduction, and Dealloying of Powders

Advanced Engineering Materials, EarlyView.
Powder metal processing provides scalable advantages in nanoporous (np) metal development. Mechanical alloying is used to produce unique precursors for hybrid nanopore formation by oxide reduction and dealloying. As demonstrated in np Ag, this approach improves process efficiency while promoting smaller ligaments and larger pores, both of which are ...
Mark A. Atwater, Oliver A. Fowler
wiley   +1 more source

Innovative Processing of Compacted Waste Aluminum Alloy Powders via Controlled Remelting and Solidification

Advanced Engineering Materials, EarlyView.
This study demonstrates an efficient recycling route for out‐of‐spec AlSi10Mg atomized powders through compaction and arc remelting followed by suction casting. By correlating compaction load, cooling rate, and resulting microstructure, we show that intermediate pressures (50–80 kN) and rapid cooling refine dendrites, reduce porosity, and enhance ...
Mila Christy de Oliveira, Marcella Gaute Cavalcante Xavier, Abdoul‐Aziz Bogno, Piter Gargarella, José Eduardo Spinelli   +4 more
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Feasibility study:

, 1993
openaire   +1 more source