A Perspective on Organic Agriculture in China - Opportunities and Challenges

With the rapid development of international production and trade in organic food, organic agriculture is also boosting in China. The milestone of Chinese organic agri-culture was set in 1990 with the first export of a certified organic product (tea) from Lin’an county of Zhejiang Province, China, which marked the launch of organic pro-duction in China. By the end of 2005, there had been about 4.384 million ha organic land, including 1.694 million ha organic, 0.61 million ha conversion as well as 2.08 million ha collection area, about half of which is certified area. About 4.93 million tons organic products and nearly 1600 projects had been certified with 300~400 varieties. According to the above data, now China ranks the 3rd largest country of organic production in the world. In China, organic development mostly is export oriented, the export products include beans, rice, tea, mushroom, vegetable, processed oil and herbs, etc. According to the certifying body COFCC of Ministry of Agriculture (MOA), the value of exported organic products increased from 0.3 million USD in 1995 to 0.35 billion USD at the end of the year 2004. Chinese domestic organic market started from 2000. Presently, most of the products sold in domestic markets are certified by COFCC and OFDC in some largest cities such as Beijing, Shanghai, Guangzhou, Nanjing and Shenzhen, etc. The price of the organic products is often up to 3 times the price of conventional products. Average organic food consumption accounts for 0.08% of the conventional food (LI 2006)

Warm spiral streamers over Gulf Stream warm-core rings

Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 50(11),(2020): 3331–3351, https://doi.org/10.1175/JPO-D-20-0035.1.This study examines the generation of warm spiral structures (referred to as spiral streamers here) over Gulf Stream warm-core rings. Satellite sea surface temperature imagery shows spiral streamers forming after warmer water from the Gulf Stream or newly formed warm-core rings impinges onto old warm-core rings and then intrudes into the old rings. Field measurements in April 2018 capture the vertical structure of a warm spiral streamer as a shallow lens of low-density water winding over an old ring. Observations also show subduction on both sides of the spiral streamer, which carries surface waters downward. Idealized numerical model simulations initialized with observed water-mass densities reproduce spiral streamers over warm-core rings and reveal that their formation is a nonlinear submesoscale process forced by mesoscale dynamics. The negative density anomaly of the intruding water causes a density front at the interface between the intruding water and surface ring water, which, through thermal wind balance, drives a local anticyclonic flow. The pressure gradient and momentum advection of the local interfacial flow push the intruding water toward the ring center. The large-scale anticyclonic flow of the ring and the radial motion of the intruding water together form the spiral streamer. The observed subduction on both sides of the spiral streamer is part of the secondary cross-streamer circulation resulting from frontogenesis on the stretching streamer edges. The surface divergence of the secondary circulation pushes the side edges of the streamer away from each other, widens the warm spiral on the surface, and thus enhances its surface signal.Authors W. G. Zhang and D. J. McGillicuddy are both supported by the National Science Foundation through Grant OCE 1657803

High-throughput optical neural networks based on temporal computing

An emerging generative artificial intelligence (AI) based on neural networks starts to grow in popularity with a revolutionizing capability of creating new and original content. As giant generative models with millions to billions of parameters are developed, trained and maintained, a massive and energy-efficient computing power is highly required. However, conventional digital computers are struggling to keep up with the pace of the generative model improvements. In this paper, we propose and demonstrate high-throughput optical neural networks based on temporal computing. The core weighted summation operation is realized with the use of high-speed electro-optic modulation and low-speed balanced photodetection. The input data and weight are encoded in a time sequence separately and loaded on an optical signal via two electro-optic modulators sequentially. By precisely controlling the synchronization time of the data and weight loading, the matrix multiplication is performed. Followed by a balanced photodetector, the summation is conducted, thanks to the electron accumulation of the inherent electronic integrator circuit of the low-speed photodetector. Thus, the linear weighted summation operation is implemented based on temporal computing in the optical domain. With the proposed optical linear weighted summation, a fully-connected neural network and convolutional neural network are realized. Thanks to the high-speed feature of temporal computing, a high data throughput of the optical neural network is experimentally demonstrated, and the weighting coefficients can be specified on demand, which enables a strong programmability of the optical neural network. By leveraging wavelength multiplexing technology, a scalable optical neural network could be created with a massive computing power and strong reconfigurability, which holds great potential for future giant AI applications

The dispersal of dense water formed in an idealized coastal polynya on a shallow sloping shelf

Author Posting. © American Meteorological Society, 2014. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 44 (2014): 1563–1581, doi:10.1175/JPO-D-13-0188.1.This study examines the dispersal of dense water formed in an idealized coastal polynya on a sloping shelf in the absence of ambient circulation and stratification. Both numerical and laboratory experiments reveal two separate bottom pathways for the dense water: an offshore plume moving downslope into deeper ambient water and a coastal current flowing in the direction of Kelvin wave propagation. Scaling analysis shows that the velocity of the offshore plume is proportional not only to the reduced gravity, bottom slope, and inverse of the Coriolis parameter, but also to the ratio of the dense water depth to total water depth. The dense water coastal current is generated by the along-shelf baroclinic pressure gradient. Its dynamics can be separated into two stages: (i) near the source region, where viscous terms are negligible, its speed is proportional to the reduced gravity wave speed and (ii) in the far field, where bottom drag becomes important and balances the pressure gradient, the velocity is proportional to Hc[g′/(LCd)]1/2 in which Hc is the water depth at the coast, g′ the reduced gravity, Cd the quadratic bottom drag coefficient, and L the along-shelf span of the baroclinic pressure gradient. The velocity scalings are verified using numerical and laboratory sensitivity experiments. The numerical simulations suggest that only 3%–23% of the dense water enters the coastal pathway, and the percentage depends highly on the ratio of the velocities of the offshore and coastal plumes. This makes the velocity ratio potentially useful for observational studies to assess the amount of dense water formed in coastal polynyas.WGZ was sponsored by the WHOI Arctic Research Initiative program. CC received support from the National Science Foundation Project OCE-1130008.2014-12-0