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Article
2D Laplace-Fourier domain acoustic wave equation modeling with an optimal finite-difference method
Laplace-Fourier (L-F) domain finite-difference (FD) forward modeling is an important foundation for L-F domain full-waveform inversion (FWI). An optimal modeling method can improve the efficiency and accuracy ...
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Article
Open AccessImpact of Mean Platelet Volume on Long-Term Mortality in Chinese Patients with ST-Elevation Myocardial Infarction
We investigated the association between mean platelet volume (MPV) and risk of all-cause mortality in Chinese patients with ST-Elevation Myocardial Infarction (STEMI). We enrolled 1836 patients with STEMI in X...
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Article
Protective effect of Bu-7, a flavonoid extracted from Clausena lansium, against rotenone injury in PC12 cells
To investigate the protective effect and underlying mechanisms of Bu-7, a flavonoid isolated from the leaves of Clausena lansium, against rotenone-induced injury in PC12 cells.
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Article
PEG-conjugated PAMAM Dendrimers Mediate Efficient Intramuscular Gene Expression
Generations 5 and 6 (G5 and G6) poly(amidoamine) (PAMAM) dendrimers have been shown to be highly efficient nonviral carriers in in vitro gene delivery. However, their high toxicity and unsatisfied in vivo efficac...
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Article
Polygalasaponin XXXII from Polygala tenuifolia root improves hippocampal-dependent learning and memory
The aim of this study was to investigate the cognition-enhancing activity and underlying mechanisms of a triterpenoid saponin (polygalasaponin XXXII, PGS32) isolated from the roots of Polygala tenuifolia Willd.
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Chapter and Conference Paper
Remote Sensing Image Fusion Based on Adaptive RBF Neural Network
With the availability of multi-sensor and multi-frequency image data from operational observation satellites, the fusion of image data has become an important tool in remote sensing image evaluation and segmen...
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Chapter and Conference Paper
Classifying Unbalanced Pattern Groups by Training Neural Network
When training set is unbalanced, the conventional least square error (LSE) training strategy is less efficient to train neural network (NN) for classification because it often lead the NN to overcompensate for...
