Results 131 to 140 of about 5,387,499 (270)
On energy harvesting from ambient vibration
, 2006 Future MEMS devices will harvest energy from their environment. One can envisage an autonomous condition monitoring vibration sensor being powered by that same vibration, and transmitting data over a wireless link; inaccesible or hostile environments are
Stephen, N.G.
core +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source
Piezoelectric Impact Energy Harvester Based on the Composite Spherical Particle Chain for Self-Powered Sensors. [PDF]
Sensors (Basel), 2021 Yang S, Wu B, Liu X, Li M, Wang H, He C.
europepmc +1 more source
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 +11 more
wiley +1 more source
Advanced SciencePrecise agriculture based on intelligent agriculture plays a significant role in sustainable development. The agricultural Internet of Things (IoTs) is a crucial foundation for intelligent agriculture.
Along Gao +8 more
doaj +1 more source
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 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 +2 more
wiley +1 more source
Traditional semiconductor gas sensors have a single-plane electrode structure; therefore, an external bias voltage is needed to create an electric field to help carriers move within the sensing material. However, the importance of developing self-powered
Chun-Ying Huang (4372900) +5 more
core +1 more source
Creating Ti–Fe α/β Alloys by Diffusion‐Driven Solid‐State Processing
Advanced Engineering Materials, EarlyView.This study proposes making alloys containing fast diffusing elements that are difficult to produce by ingot metallurgy, by diffusion‐driven solid‐state HIP processing of elemental powders and low‐temperature homogenisation. Here, novel Fe‐Ti α–β alloys are formed having fine α–β lamellae, a small β prior grain size without significant intermetallics ...
Jiaqi Xu +10 more
wiley +1 more source