Photovoltaic power has great volatility and intermittency due to environmental factors.
Forecasting photovoltaic power is of great significance to ensure the safe and economical …

Deep neural networks have revolutionized many machine learning tasks in power systems,
ranging from pattern recognition to signal processing. The data in these tasks are typically …

The genetic heterogeneities in cancer cells pose challenges to achieving precise drug treatment
in a widely applicable manner. Most single-cell gene analysis methods rely on cell lysis …

Regenerative cooling is widely employed for thermal protection of hypersonic vehicles.
Hydrocarbon fuels undergo pyrolysis in regenerative cooling channels at supercritical pressures, …

Existing methods for transformer fault diagnosis either train a classifier to fit the relationship
between dissolved gas and fault type or find some similar cases with unknown samples by …

The fluctuation and intermittence of wind power bring great challenges to the operation and
control of the distribution network. Accurate short-term prediction for wind power is helpful to …

Ultra-high quality (Q) factor resonances derived from the bound states in the continuum (BICs)
have drawn much attention in optics and photonics. Especially in meta-surfaces, they can …

Solar-driven flat-panel H 2 O-to-H 2 conversion is an important technology for value-added
solar fuel production. However, most frequently used particulate photocatalysts are hard to …

High Q factor multiple Fano resonance excitation in all-dielectric metasurfaces has become
an effective mode to design high performance optical devices. This paper proposed an all-…

Triboelectric nanogenerators (TENGs) use the displacement current as a driving force to
convert mechanical energy into electric power, which has made great contributions to micro‐…