Conservation agriculture has been shown to have multiple benefits for soils, crop yield and the environment, and consequently, no-till, the central practice of conservation agriculture, has rapidly expanded. However, studies show that the potential for carbon (C) sequestration in no-till farming sometimes is not realized, let alone the ability to maintain or improve crop yield. Here we present a global analysis of no-till-induced changes of soil C and crop yield based on 260 and 1,970 paired studies; respectively. We show that, relative to local conventional tillage, arid regions can benefit the most from conservation agriculture by achieving a win-win outcome of enhanced C sequestration and increased crop yield. However, more humid regions are more likely to increase SOC only, while some colder regions have yield losses and soil C loss as likely as soil C gains. In addition to site-specific characteristics and management, a careful assessment of the regional climate is needed to determine the potential benefits of adopting conservation agriculture. K E Y W O R D S climate, conservation agriculture, crop yield, meta-analysis, soil organic carbon, win-win outcome See also the Commentary on this article by Hunt et al. 26, 3188-3189

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Both distributed systems and multicore systems are difficult programming environments. Although the expert programmer may be able to carefully tune these systems to achieve high performance, the non-expert may struggle. We argue that high level abstractions are an effective way of making parallel computing accessible to the non-expert. An abstraction is a regularly structured framework into which a user may plug in simple sequential programs to create very large parallel programs. By virtue of a regular structure and declarative specification, abstractions may be materialized on distributed, multicore, and distributed multicore systems with robust performance across a wide range of problem sizes. In previous work, we presented the All-Pairs abstraction for computing on distributed systems of single CPUs. In this paper, we extend All-Pairs to multicore systems, and introduce the Wavefront and Makeflow abstractions, which represent a number of problems in economics and bioinformatics. We demonstrate good scaling of both abstractions up to 32 cores on one machine and hundreds of cores in a distributed system.

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The influence of Chinese university students' entrepreneurial experience, alertness, and prior knowledge on opportunity recognition was examined using the novice–experienced entrepreneurs contrast paradigm. After viewing a self-made opportunity situation, 94 entrepreneurial university students and 114 nonentrepreneurial university students were instructed to complete via email or paper and pencil tests measures of opportunity recognition, entrepreneurial alertness, and prior knowledge. The results showed that entrepreneurial alertness significantly and directly predicted opportunity recognition, whereas prior knowledge significantly and indirectly affected opportunity recognition through its impact on entrepreneurial alertness. The entrepreneurial alertness of nonentrepreneurial university students significantly influenced their opportunity recognition; in contrast, the prior knowledge of entrepreneurial university students greatly influenced their opportunity recognition. Practical implications for entrepreneurial training and future directions for research on opportunity recognition are discussed.

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