Results 111 to 120 of about 18,304 (280)
Workflow of the parameter optimization process for ITSC fault detection, applying Differential Evolution optimization and the Smooth Pseudo Wigner‐Ville Distribution for signal processing. The optimized parameters are then used in the failure identification pipeline, which combines the signal processing with a YOLO‐based architecture for fault severity
Rafael Martini Silva +4 more
wiley +1 more source
β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations
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 +11 more
wiley +1 more source
This study investigates the photosensitizing potential of Passiflora cincinnata in Antimicrobial Photodynamic Therapy (aPDT) against skin infection caused by Methicillin‐resistant Staphylococcus aureus (MRSA) in a senescent murine model. The P. cincinnata exhibits antimicrobial activity, with reduced bacterial load, lower leukocyte infiltration, and ...
Caroline Vieira Gonçalves +14 more
wiley +1 more source
The unrolling of the peltate leaves in Syngonium podophyllum is analyzed and quantified (left‐hand side to center). These measurements serve to verify a mathematical model for leaf unrolling based on the model used in Schmidt (2007). An additional formula for obtaining a layer mismatch from a prescribed radius is derived.
Michelle Modert +4 more
wiley +1 more source
A Spatially Resolved View on the Aging Substantia nigra: An Exploratory Proteomic Study
Although aging is the most important risk factor for several neurodegenerative diseases, the molecular effects of physiological aging are still understudied. By applying spatially‐resolved proteomic analyses of the human substantia nigra pars compacta, alterations in vesicular trafficking and mitochondrial proteins are observed, as well as reduced ...
Britta Eggers +10 more
wiley +1 more source
In this study, exciting new bi‐/multi‐linear elastic behavior of soft elastic composites that accompany the activation of wrinkling in the embedded interfacial layers is analyzed. The new features and performance of these composite materials, including dramatic enhancements in energy storage, can be tailored by the concentration of interfacial layers ...
Narges Kaynia +2 more
wiley +1 more source
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
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 +2 more
wiley +1 more source
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 +5 more
wiley +1 more source
A Different Perspective on the Solid Lubrication Performance of Black Phosphorous: Friend or Foe?
Researchers investigate black phosphorous (BP) as a standalone solid lubricant coating through ball‐on‐disc linear‐reciprocating sliding experiments in dry conditions. Testing on different metals shows BP doesn't universally reduce friction and wear. However, it achieves 33% friction reduction on rougher iron surfaces and 23% wear reduction on aluminum.
Matteo Vezzelli +5 more
wiley +1 more source
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi +4 more
wiley +1 more source

