Measuring the transport of the Changjiang (also known as the Yangtze) River-derived buoyant coastal current, that is, the Min-Zhe Coastal Current, is of great importance for understanding the fate of terrestrial materials from this large river into the open ocean, but it is usually difficult to achieve because of the energetic tidal currents along the Chinese coast. In February 2012, a detiding cruise survey was carried out using the phase-averaging method. For the first time, this coastal current has been quantified with in situ data and has been shown to have a volume transport of 0.215 Sv (1 Sv [ 10 6 m 3 s 21 ) and a maximum surface velocity of ;50 cm s 21 . The ratio between the volume transport of the buoyant coastal current and that of the Changjiang is O(10). Freshwater transport by the buoyant coastal current accounts for over 90% of the Changjiang River's discharge. Buoyancy and winds are both important in driving this current.

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Currently, porcine circovirus type 2 (PCV2) is considered the major pathogen of porcine circovirus associated-diseases (PCVAD) that causes large economic losses for the swine industry in the world annually, including China. Since the first report of PCV2 in 1998, it has been drawing tremendous attention for the government, farming enterprises, farmers, and veterinary practitioners. Chinese researchers have conducted a number of molecular epidemiological work on PCV2 by molecular approaches in the past several years, which has resulted in the identification of novel PCV2 genotypes and PCV2-like agents as well as the description of new prevalence patterns. Since late 2009, commercial PCV2 vaccines, including the subunit vaccines and inactivated vaccines, have already been used in Chinese swine farms. The aim of this review is to update the insights into the prevalence and control of PCV2 in China, which would contribute to understanding the epidemiology, control measures and design of novel vaccines for PCV2.

Road surface monitoring and maintenance are essential for driving comfort, transport safety and preserving infrastructure integrity. Traditional road condition monitoring is regularly conducted by specially designed instrumented vehicles, which requires time and money and is only able to cover a limited proportion of the road network. In light of the ubiquitous use of smartphones, this paper proposes an automatic pothole detection system utilizing the built-in vibration sensors and global positioning system receivers in smartphones. We collected road condition data in a city using dedicated vehicles and smartphones with a purpose-built mobile application designed for this study. A series of processing methods were applied to the collected data, and features from different frequency domains were extracted, along with various machine-learning classifiers. The results indicated that features from the time and frequency domains outperformed other features for identifying potholes. Among the classifiers tested, the Random Forest method exhibited the best classification performance for potholes, with a precision of 88.5% and recall of 75%. Finally, we validated the proposed method using datasets generated from different road types and examined its universality and robustness.

The dissolved silica (DSi) concentration and silicon isotopic composition (δ30Si) of surface water samples from the Changjiang Estuary was measured in summer and winter to study the behavior of DSi fluvial inputs into the estuary. The DSi concentration decreased away from the estuary and had a linear relationship with salinity, suggesting that mixing between river water and seawater is the dominant effect on DSi levels in the study area. Measured δ30Si in the Changjiang Estuary ranged from +1.48‰ to +2.35‰ in summer, and from +1.54‰ to +1.95‰ in winter. As a result of low light levels and abundant DSi riverine inputs, DSi remains relatively unaffected by biological utilization and fractionation in the near‐shore region, and the isotopic imprint of water from the Changjiang can still be detected up to a salinity level of 20 in summer. An obvious increase in δ30Si was observed beyond this salinity level, indicating a significant increase in biological utilization and fractionation of DSi in high salinity waters. Lower water temperatures and light levels that prevail over the winter lead to the reduced fractionation of DSi compared with that in summer. The fractionation factor (30ɛ) was estimated using a steady state model to the high salinity waters, yielding a value of −0.95‰, which is in agreement with previous results obtained for Skeletonema costatum in cultivation experiments. The results of this study suggest that silicon isotopes can be used to identify the impact of biological utilization on the behavior of DSi in highly dynamic estuarine environments.