Fast Adaptive S-ALOHA Scheme for Event-driven Machine-to-Machine Communications

Machine-to-Machine (M2M) communication is now playing a market-changing role in a wide range of business world. However, in event-driven M2M communications, a large number of devices activate within a short period of time, which in turn causes high radio congestions and severe access delay. To address this issue, we propose a Fast Adaptive S-ALOHA (FASA) scheme for M2M communication systems with bursty traffic. The statistics of consecutive idle and collision slots, rather than the observation in a single slot, are used in FASA to accelerate the tracking process of network status. Furthermore, the fast convergence property of FASA is guaranteed by using drift analysis. Simulation results demonstrate that the proposed FASA scheme achieves near-optimal performance in reducing access delay, which outperforms that of traditional additive schemes such as PB-ALOHA. Moreover, compared to multiplicative schemes, FASA shows its robustness even under heavy traffic load in addition to better delay performance.Comment: 5 pages, 3 figures, accepted to IEEE VTC2012-Fal

Waiting but not Aging: Optimizing Information Freshness Under the Pull Model

The Age-of-Information is an important metric for investigating the timeliness performance in information-update systems. In this paper, we study the AoI minimization problem under a new Pull model with replication schemes, where a user proactively sends a replicated request to multiple servers to "pull" the information of interest. Interestingly, we find that under this new Pull model, replication schemes capture a novel tradeoff between different values of the AoI across the servers (due to the random updating processes) and different response times across the servers, which can be exploited to minimize the expected AoI at the user's side. Specifically, assuming Poisson updating process for the servers and exponentially distributed response time, we derive a closed-form formula for computing the expected AoI and obtain the optimal number of responses to wait for to minimize the expected AoI. Then, we extend our analysis to the setting where the user aims to maximize the AoI-based utility, which represents the user's satisfaction level with respect to freshness of the received information. Furthermore, we consider a more realistic scenario where the user has no prior knowledge of the system. In this case, we reformulate the utility maximization problem as a stochastic Multi-Armed Bandit problem with side observations and leverage a special linear structure of side observations to design learning algorithms with improved performance guarantees. Finally, we conduct extensive simulations to elucidate our theoretical results and compare the performance of different algorithms. Our findings reveal that under the Pull model, waiting does not necessarily lead to aging; waiting for more than one response can often significantly reduce the AoI and improve the AoI-based utility in most scenarios.Comment: 15 pages. arXiv admin note: substantial text overlap with arXiv:1704.0484

Divergence in function and expression of the NOD26-like intrinsic proteins in plants

<p>Abstract</p> <p>Background</p> <p>NOD26-like intrinsic proteins (NIPs) that belong to the aquaporin superfamily are plant-specific and exhibit a similar three-dimensional structure. Experimental evidences however revealed that functional divergence should have extensively occurred among NIP genes. It is therefore intriguing to further investigate the evolutionary mechanisms being responsible for the functional diversification of the NIP genes. To better understand this process, a comprehensive analysis including the phylogenetic, positive selection, functional divergence, and transcriptional analysis was carried out.</p> <p>Results</p> <p>The origination of NIPs could be dated back to the primitive land plants, and their diversification would be no younger than the emergence time of the moss <it>P. patens</it>. The rapid proliferation of NIPs in plants may be primarily attributed to the segmental chromosome duplication produced by polyploidy and tandem duplications. The maximum likelihood analysis revealed that <it>NIPs </it>should have experienced strong selective pressure for adaptive evolution after gene duplication and/or speciation, prompting the formation of distinct <it>NIP </it>groups. Functional divergence analysis at the amino acid level has provided strong statistical evidence for shifted evolutionary rate and/or radical change of the physiochemical properties of amino acids after gene duplication, and DIVERGE2 has identified the critical amino acid sites that are thought to be responsible for the divergence for further investigation. The expression of plant NIPs displays a distinct tissue-, cell-type-, and developmental specific pattern, and their responses to various stress treatments are quite different also. The differences in organization of <it>cis</it>-acting regulatory elements in the promoter regions may partially explain their distinction in expression.</p> <p>Conclusion</p> <p>A number of analyses both at the DNA and amino acid sequence levels have provided strong evidences that plant NIPs have suffered a high divergence in function and expression during evolution, which is primarily attributed to the strong positive selection or a rapid change of evolutionary rate and/or physiochemical properties of some critical amino acid sites.</p

Learning Adaptive Display Exposure for Real-Time Advertising

In E-commerce advertising, where product recommendations and product ads are presented to users simultaneously, the traditional setting is to display ads at fixed positions. However, under such a setting, the advertising system loses the flexibility to control the number and positions of ads, resulting in sub-optimal platform revenue and user experience. Consequently, major e-commerce platforms (e.g., Taobao.com) have begun to consider more flexible ways to display ads. In this paper, we investigate the problem of advertising with adaptive exposure: can we dynamically determine the number and positions of ads for each user visit under certain business constraints so that the platform revenue can be increased? More specifically, we consider two types of constraints: request-level constraint ensures user experience for each user visit, and platform-level constraint controls the overall platform monetization rate. We model this problem as a Constrained Markov Decision Process with per-state constraint (psCMDP) and propose a constrained two-level reinforcement learning approach to decompose the original problem into two relatively independent sub-problems. To accelerate policy learning, we also devise a constrained hindsight experience replay mechanism. Experimental evaluations on industry-scale real-world datasets demonstrate the merits of our approach in both obtaining higher revenue under the constraints and the effectiveness of the constrained hindsight experience replay mechanism.Comment: accepted by CIKM201

Elevated atmospheric CO2 delays the key timing for split N applications to improve wheat (Triticum aestivum L.) protein composition

Late stage nitrogen (N) applications following basic fertilization are commonly used to ensure grain yield and increase grain protein content in wheat. Split N applications at the late growth stage of wheat are an effective measure to improve N absorption and transport and thus increase grain protein content. However, whether split N applications can alleviate the decrease in grain protein content induced by elevated atmospheric CO2 concentrations (e[CO2]) remains unclear. In the present study, a free-air CO2 enrichment system was used to investigate the effects of split N applications (at booting or anthesis) on grain yield, N utilization, protein content, and the composition of wheat under atmospheric (ACO2; 400 ± 15 ppm) and elevated CO2 concentrations (ECO2; 600 ± 15 ppm). The results showed that wheat grain yield and grain N uptake increased by 5.0% (being grains per ear by 3.0%, 1000-grain weight by 2.0%, and harvest index by 1.6%) and 4.3%, respectively, whereas grain protein content decreased by 2.3% under ECO2 conditions. Although the negative effect of e[CO2] on grain protein content was not alleviated by split N applications, gluten protein content was enhanced due to the alteration of N distribution in different protein fractions (albumins, globulins, gliadins, and glutenins). Compared to that without split N applications, the gluten content of wheat grains increased by 4.2% and 4.5% when late stage N was applied at the booting stage under ACO2 and anthesis under ECO2 conditions, respectively. The results indicate that rational handling of N fertilizers may be a promising approach to coordinating grain yield and quality under the effects of future climate change. However, compared to ACO2 conditions, the key timing for improving grain quality by split N applications should be postponed from the booting stage to anthesis under e[CO2] conditions