Power generation expansion planning model towards low-carbon economy and its application in china

Climate change poses a huge threat to human welfare. Hence, developing a low-carbon economy has become a prevailing and inevitable trend. Decarbonization of power generation, especially converting the current power mix into a low-carbon structure, will be a critical option for CO2 emission mitigation. In this paper, an integrated power generation expansion (PGE) planning model towards low-carbon economy is proposed, which properly integrates and formulates the impacts of various low-carbon factors on PGE models. In order to adapt to the characteristics of PGE models based on low-carbon scenario, a compromised modeling approach is presented, which reasonably decreases complexities of the model, while properly keeping the significant elements and maintaining moderate precision degree. In order to illustrate the proposed model and approach, a numerical case is studied based on the background of China's power sector, making decisions on the optimal PGE plans and revealing the prospects and potentials for CO2 emission reduction. © 2010 IEEE.published_or_final_versio

Momentum Distribution of Near-Zero-Energy Photoelectrons in the Strong-Field Tunneling Ionization in the Long Wavelength Limit

We investigate the ionization dynamics of Argon atoms irradiated by an ultrashort intense laser of a wavelength up to 3100 nm, addressing the momentum distribution of the photoelectrons with near-zero-energy. We find a surprising accumulation in the momentum distribution corresponding to meV energy and a \textquotedblleft V"-like structure at the slightly larger transverse momenta. Semiclassical simulations indicate the crucial role of the Coulomb attraction between the escaping electron and the remaining ion at extremely large distance. Tracing back classical trajectories, we find the tunneling electrons born in a certain window of the field phase and transverse velocity are responsible for the striking accumulation. Our theoretical results are consistent with recent meV-resolved high-precision measurements.Comment: 5 pages, 4 figure

The use of artificial neural networks in the motor program

Though it is commonly assumed that the brain creates 'motor programs' which store the information essential to perform a motor skill, little direct evidence exists for such motor programs. Electromyography (EMG) provides a look into the motoneurons - level of a movement by measuring the electrical activity in relation to the muscle's involvement in the movement In this paper, artificial neural networks (ANNs) were applied to define the temporal patterns of EMG activity used by normal subjects in performing step-tracking tasks, and how such patterns change with practice. Our results demonstrate that ANNs could be trained to detect the input-output relationship between muscles' onset times and reaction times, and provided evidence to support the existence of a motor program.published_or_final_versio

Effectiveness of a community-based multifaceted fall-prevention intervention in active and independent older Chinese adults

This paper is freely available online under the BMJ Journals unlocked scheme, se