Nonlinear X-wave formation and conical emission at different powers of a femtosecond laser pulse in water

Nonlinear X-wave formation at different pulse powers in water is simulated using the standard model of nonlinear Schrodinger equation (NLSE). It is shown that in near field X-shape originally emerges from the interplay between radial diffraction and optical Kerr effect. At relatively low power group-velocity dispersion (GVD) arrests the collapse and leads to pulse splitting on axis. With high enough power, multi-photon ionization (NIPI) and multi-photon absorption (MPA) play great importance in arresting the collapse. The tailing part of pulse is first defocused by MPI and then refocuses. Pulse splitting on axis is a manifestation of this process. Double X-wave forms when the split sub-pulses are self-focusing. In the far field, the character of the central X structure of conical emission (CE) is directly related to the single or double X-shape in the near field. (c) 2007 Elsevier B.V. All rights reserved.

Philip公式确定吸渗率时间尺度研究

选用直径5 cm和10 cm的盘式吸渗仪,对杨凌土(粘土)和神木砂黄土(砂壤土)两种质地的土壤在1 cm、3 cm6、cm9、cm和12 cm水头5种负压下进行了室内盘式吸渗仪三维吸渗实验,选取Vandervaere公式作为参考模型,对Philip公式确定吸渗率的时间尺度选取进行了分析。结果表明,对两种质地的土壤,在相同盘径下,随着负压的降低,吸渗率随之减小;在相同负压下,盘径越小,吸渗率越大;质地较砂的砂黄土吸渗率明显大于质地较粘的土的吸渗率。从相对误差来看,两种质地土壤吸渗率均被高估;在同一盘径下,随着负压的减小,误差值逐渐降低;即在选取的时间范围内,负压越低,计算吸渗率的准确性越高。对土而言,5 cm盘径下-12 cm水头1、0 cm盘径下-9 cm水头和-12 cm水头时确定吸渗率的适宜时间分别为30~40 s和40~50 s;其余确定吸渗率的适宜时间均应小于30 s;对砂黄土而言,10 cm盘径下-9 cm水头和-12 cm水头时确定吸渗率的适宜时间分别为30~40 s和40~50 s,其余确定吸渗率的适宜时间也均应小于30 s。对于质地较砂的土壤推荐使用大盘径进行盘式吸渗仪实验。

Biologically Inspired Features for Scene Classification in Video Surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.