The origin of millet from Neolithic China has generally been accepted, but it remains unknown whether common millet (Panicum miliaceum) or foxtail millet (Setaria italica) was the first species domesticated. Nor do we know the timing of their domestication and their routes of dispersal. Here, we report the discovery of husk phytoliths and biomolecular components identifiable solely as common millet from newly excavated storage pits at the Neolithic Cishan site, China, dated to between ca. 10,300 and ca. 8,700 calibrated years before present (cal yr BP). After ca. 8,700 cal yr BP, the grain crops began to contain a small quantity of foxtail millet. Our research reveals that the common millet was the earliest dry farming crop in East Asia, which is probably attributed to its excellent resistance to drought.Holocene ͉ origins of agriculture ͉ phytoliths ͉ Neolithic ͉ Cishan F oxtail millet (Setaria italica) and common millet (or broomcorn millet; Panicum miliaceum) were among the world's most important and ancient domesticated crops. They were staple foods in the semiarid regions of East

We present a new three-dimensional (3D) compressional wavespeed (V p) model for the Parkfield region, taking advantage of the recent seismicity associated with the 2003 San Simeon and 2004 Parkfield earthquake sequences to provide increased model resolution compared to the work of Eberhart-Phillips and Michael (1993) (EPM93). Taking the EPM93 3D model as our starting model, we invert the arrival-time data from about 2100 earthquakes and 250 shots recorded on both permanent network and temporary stations in a region 130 km northeast-southwest by 120 km northwest-southeast. We include catalog picks and cross-correlation and catalog differential times in the inversion, using the double-difference tomography method of Zhang and Thurber (2003). The principal V p features reported by EPM93 and Michelini and McEvilly (1991) are recovered, but with locally improved resolution along the San Andreas Fault (SAF) and near the active-source profiles. We image the previously identified strong wavespeed contrast (faster on the southwest side) across most of the length of the SAF, and we also improve the image of a high V p body on the northeast side of the fault reported by EPM93. This narrow body is at about 5-to 12-km depth and extends approximately from the locked section of the SAF to the town of Parkfield. The footwall of the thrust fault responsible for the 1983 Coalinga earthquake is imaged as a northeast-dipping high wavespeed body. In between, relatively low wavespeeds (Ͻ5 km/sec) extend to as much as 10-km depth. We use this model to derive absolute locations for about 16,000 earthquakes from 1966 to 2005 and high-precision double-difference locations for 9,000 earthquakes from 1984 to 2005, and also to determine focal mechanisms for 446 earthquakes. These earthquake locations and mechanisms show that the seismogenic fault is a simple planar structure. The aftershock sequence of the 2004 mainshock concentrates into the same structures defined by the pre-2004 seismicity, confirming earlier observations (Waldhauser et al., 2004) that the seismicity pattern at Parkfield is long lived and persists through multiple cycles of mainshocks.

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We have developed an automatic P-wave arrival detection and picking algorithm based on the wavelet transform and Akaike information criteria (AIC) picker. Wavelet coefficients at high resolutions show the fine structure of the time series, and those at low resolutions characterize its coarse features. Primary features such as the P-wave arrival are retained over several resolution scales, whereas secondary features such as scattered arrivals decay quickly at lower resolutions. We apply the discrete wavelet transform to single-component seismograms through a series of sliding time windows. In each window the AIC autopicker is applied to the thresholded absolute wavelet coefficients at different scales, and we compare the consistency of those picks to determine whether a P-wave arrival has been detected in the given time window. The arrival time is then determined using the AIC picker on the time window chosen by the wavelet transform. We test our method on regional earthquake data from the Dead Sea Rift region and local earthquake data from the Parkfield, California region. We find that 81% of picks are within 0.2-sec of the corresponding analyst pick for the Dead Sea dataset, and 93% of picks are within 0.1 sec of the analyst pick for the Parkfield dataset. We attribute the lower percentage of agreement for the Dead Sea dataset to the substantially lower signal-to-noise ratio of those data, and the likelihood that some percentage of the analyst picks are in error.