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ZmPTF1 regulates drought tolerance in maize by promoting root development and ABA synthesis, by binding to the G-box in the promoter and activating the expression of NCEDs, CBF4, NAC081, and NAC30.

This paper proposes the minimum power configuration (MPC) approach to energy conservation in wireless sensor networks. In sharp contrast to earlier research that treats topology control, power-aware routing, and sleep management in isolation, MPC integrates them as a joint optimization problem in which the power configuration of a network consists of a set of active nodes and the transmission powers of the nodes. We show through analysis that the minimum power configuration of a network is inherently dependent on the data rates of sources. We propose several approximation algorithms with provable performance bounds compared to the optimal solution, and a practical Minimum Power Configuration Protocol (MPCP) that can dynamically (re)configure a network to minimize the energy consumption based on current data rates. Simulations based on realistic radio models of the Mica2 motes show that MPCP can conserve significantly more energy than existing minimum power routing and topology control protocols.

Internet interdomain routing is policy-driven, and thus physical connectivity does not imply reachability. On average, routing on today's Internet works quite well, ensuring reachability for most networks and achieving reasonable performance across most paths. However, there is a serious lack of understanding of Internet routing resilience to significant but realistic failures such as those caused by the 911 event, the 2003 Northeast blackout, and the recent Taiwan earthquake in December 2006. In this paper, we systematically analyze how the current Internet routing system reacts to various types of failures by developing a realistic failure model, and then pinpoint reliability bottlenecks of the Internet. For validity of our simulation results, we generate topology graphs by addressing concerns over the incompleteness of topology and the inaccuracy of inferred AS relationships. By focusing on the impact of structural and policy properties, our analysis provides guidelines for future Internet design. The simulation tool we provide for analyzing routing resilience is also efficient to scale to Internet-size topologies.

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<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt; layout-grid-mode: char;" align="left"><span class="text"><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;">One of the most common communication patterns in sensor networks is routing data to a base station, while the base station can be either static or mobile. Even in static cases, a static spanning tree may not survive for a long time due to failures of sensor nodes. In this paper, we present an adaptive spanning tree routing mechanism, using real-time reinforcement learning strategies. We demonstrate via simulation that without additional control packets for tree maintenance, adaptive spanning trees can maintain the “best” connectivity to the base station, in spite of node failures or mobility of the base station. And by using a general constraint-based routing specification, one can apply the same strategy to achieve load balancing and to control network congestion effectively in real time.</span></span><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;"></span></p>

PurposeThe purpose of this paper is to examine stocks that are most actively discussed by online posters and see if the messages posted about these stocks have information or if they are just noise.Design/methodology/approachThis study uses messages posted on TheLion.com, which reports a real time list of the ten most actively discussed stocks. The stocks in this list at the daily market close during 2005‐2006 are examined. An event study is performed to estimate the daily abnormal returns on these stocks. Contemporaneous and lead–lag regressions of abnormal returns against message posting activities are performed.FindingsOnline posters prefer thinly traded micro‐cap stocks. On average, there is an abnormal return of 19.4 per cent on a stock the day it is one of the ten most talked about stocks. The number of messages posted about a stock on a given day is not only positively related with the stock's abnormal return on that day but it also positively predicts the next day's abnormal return.Research limitations/implicationsIt may be interesting to examine if the investor sentiment expressed in online messages has predictive power for micro‐cap stocks.Practical implicationsThe results provide evidence to regulators that online talk affects stock prices. They show investors that there are inefficiencies in the stock market. They also suggest that corporate managers, especially of small firms, should monitor the stock message boards.Originality/valueThis study focuses on the micro‐cap stocks favored by online posters and finds that online talk has the power to predict the next‐day returns.