大脑序列记忆信息的提取

The purpose of this study was to examine the cognitive and neural mechanism underlying the serial position effects using cognitive experiments and ERPs(the event related potentials), for 11 item lists in very short-term and the continuous-distractor paradigm with Chinese character. The results demonstrated that when the length of list was 11 Chinese character, and the presentation time, the item interval and the retention interval was 400ms, the primacy effect and recency effect belong to the associative memory and absolute memory respectively. The retrieval of the item at the primacy part depended mainly on the context cues, but the retrieval of the item at the recency part depended mainly on the memory trace. The same results was concluded in the continuous-distractor paradigm (the presentation time was 1sec, the item interval is 12sec, and the retention interval was 30sec). Cognitive results revealed the robust serial position effects in the continuous-distractor paradigm. The different retrieval process between items at the primacy part and items at the recency part of the serial position curve was found. The behavioral responses data of ERP illustrated that the responses for the prime and recent items differed neither in accuracy nor reaction time, the retrieval time for the items at the primacy part was longer than that for the items at the recency part. And the accuracy of retrieval for the primacy part item was lower than that for the recency part items. That meant the retrieval of primacy part items needed more cognitive processes. The recent items, compared with the prime items, evoked ERPs that were more positive, this enhanced positivity occurred in a positive component peaking around 360ms. And for the same retrieval direction (forward or backward), the significant positive component difference between the retrieval for prime items and the retrieval for recent items was found. But there was no significant difference between the forward and backward retrieval at both the primacy and recency part of the serial position curve. These revealed the two kind of retrieval (forward and backward) at the same part of the serial position curve belonged to the same property. These findings fit more closely with the notion of the distinct between the associative memory and the absolute memory.

Retrieval of Electron Return Time from High-order Harmonics Generated in a Mixture of He and Ne Gases

In terms of single-atom induced dipole moment by Lewenstein model, we present the macroscopic high-order harmonic generation from mixed He and Ne gases with different mixture ratios by solving three-dimensional Maxwell's equation of harmonic field. And then we show the validity of mixture formulation by Wagner et al. [Phys. Rev. A 76 (2007) 061403(R)] in macroscopic response level. Finally, using least squares fitting we retrieve the electron return time of short trajectory by formulation in Kanai et al. [Phys. Rev. Lett. 98 (2007) 153904] when the gas jet is put after the laser focus.

Neural network retrieval of ocean surface parameters from SSM/I data

A new algorithm based on the multiparameter neural network is proposed to retrieve wind speed (WS), sea surface temperature (SST), sea surface air temperature, and relative humidity ( RH) simultaneously over the global oceans from Special Sensor Microwave Imager (SSM/I) observations. The retrieved geophysical parameters are used to estimate the surface latent heat flux and sensible heat flux using a bulk method over the global oceans. The neural network is trained and validated with the matchups of SSM/I overpasses and National Data Buoy Center buoys under both clear and cloudy weather conditions. In addition, the data acquired by the 85.5-GHz channels of SSM/I are used as the input variables of the neural network to improve its performance. The root-mean-square (rms) errors between the estimated WS, SST, sea surface air temperature, and RH from SSM/I observations and the buoy measurements are 1.48 m s(-1), 1.54 degrees C, 1.47 degrees C, and 7.85, respectively. The rms errors between the estimated latent and sensible heat fluxes from SSM/I observations and the Xisha Island ( in the South China Sea) measurements are 3.21 and 30.54 W m(-2), whereas those between the SSM/ I estimates and the buoy data are 4.9 and 37.85 W m(-2), respectively. Both of these errors ( those for WS, SST, and sea surface air temperature, in particular) are smaller than those by previous retrieval algorithms of SSM/ I observations over the global oceans. Unlike previous methods, the present algorithm is capable of producing near-real-time estimates of surface latent and sensible heat fluxes for the global oceans from SSM/I data.