Optimal Caching Policy of Stochastic Updating Information in Delay Tolerant Networks

To increase the speed of information retrieval, one message may have multiple replicas in Delay Tolerant Networks (DTN). In this paper, we adopt a discrete time model and focus on the caching policy of stochastic updating information. In particular, the source creates new version in every time slot with certain probability. New version is usually more useful than the older one. We use a utility function to denote the availability of different versions. To constrain the number of replicas, we propose a probabilistic management policy and nodes to discard information with certain probability determined by the version of the information. Our objective is to find the best value of the probability to maximize the total utility value. Because new version is created with certain probability, nodes other than the source may not know whether the information stored in them is the latest version. Therefore, they can make decisions only according to the local state and decisions based on the local state can be seen as local-policy. We also explore the global-policy, that is, nodes understand the real state. We prove that the optimal policies in both cases conform to the threshold form. Simulations based on both synthetic and real motion traces show the accuracy of our theoretical model. Surprisingly, numerical results show that local-policy is better than the global-policy in some cases

Assembling convolution neural networks for automatic viewing transformation

Images taken under different camera poses are rotated or distorted, which leads to poor perception experiences. This paper proposes a new framework to automatically transform the images to the conformable view setting by assembling different convolution neural networks. Specifically, a referential 3D ground plane is firstly derived from the RGB image and a novel projection mapping algorithm is developed to achieve automatic viewing transformation. Extensive experimental results demonstrate that the proposed method outperforms the state-ofthe-art vanishing points based methods by a large margin in terms of accuracy and robustness

Simultaneous Identification of Multiple Causal Mutations in Rice

Next-generation sequencing technologies (NGST) are being used to discover causal mutations in ethyl methanesulfonate (EMS)-mutagenized plant populations. However, the published protocols often deliver too many candidate sites and sometimes fail to find the mutant gene of interest. Accurate identification of the causal mutation from massive background polymorphisms and sequencing deficiencies remains challenging. Here we describe a NGST-based method, named SIMM, that can simultaneously identify the causal mutations in multiple independent mutants. Multiple rice mutants derived from the same parental line were back-crossed, and for each mutant, the derived F2 individuals of the recessive mutant phenotype were pooled and sequenced. The resulting sequences were aligned to the Nipponbare reference genome, and single nucleotide polymorphisms (SNPs) were subsequently compared among the mutants. Allele index (AI) and Euclidean distance (ED) were incorporated into the analysis to reduce noises caused by background polymorphisms and re-sequencing errors. Corrections of sequence bias against GC- and AT-rich sequences in the candidate region were conducted when necessary. Using this method, we successfully identified seven new mutant alleles from Huanghuazhan (HHZ), an elite indica rice cultivar in China. All mutant alleles were validated by phenotype association assay.Guangdong Innovative Research Team Program [201001S0104725509]; Ministry of Agriculture Transgenic Project [2012ZX08001001]; National Program on Key Basic Research Project of China [973 Program] [2011CB100101, 2013CBA01402]; National High Technology Research and Development Program of China [863 Program] [2014AA10A602]; Natural Science Foundation of China [31110103917]; Shenzhen Commission on Innovation and Technology [KQF201109160004A, CXZZ20140411140647863]SCI(E)ARTICLE

Effects of precipitation changes on aboveground net primary production and soil respiration in a switchgrass field

Switchgrass (Panicum virgatum L.) is widely selected as a model feedstock for sustainable replacement of fossil fuels and climate change mitigation. However, how climate changes, such as altered precipitation (PPT), will influence switchgrass growth and soil carbon storage potential have not been well investigated. We conducted a two-year PPT manipulation experiment with five treatments: −50%, −33%, +0%, +33%, and +50% of ambient PPT, in an “Alamo” switchgrass field in Nashville, TN. Switchgrass aboveground net primary production (ANPP), leaf gas exchange, and soil respiration (SR) were determined each growing season. Data collected from this study was then used to test whether switchgrass ANPP responds to PPT changes in a double asymmetry pattern as framed by Knapp et al. (2017), and whether it is held true for other ecosystem processes such as SR. Results showed that the wet (+33%, and +50%) treatments had little effects on ANPP and leaf gas exchange compared to the ambient precipitation treatment, regardless of fertilization or not. The −33% treatment did not change ANPP and leaf photosynthesis, but significantly decreased transpiration and enhanced water use efficiency (WUE). Only the −50% treatment significantly decreased ANPP and LAI, without changing leaf photosynthesis. SR generally decreased under the drought treatments and increased under the wet treatments, while there was no significant difference between the two drought treatments or between the two wet treatments. Our results demonstrate that switchgrass ANPP responded in a single negative asymmetry model to PPT changes probably due to relative high PPT in the region. However, even in such a mesic ecosystem, SR responded strongly to PPT changes in an “S” curve model, suggesting that future climate changes may have greater but more complex effects on switchgrass belowground than aboveground processes. The contrasting models for switchgrass ANPP and SR in response to PPT indicate that extreme wet or dry PPT conditions may shift ecosystem from carbon accumulation toward debt, and in turn provide government and policy makers with useful information for sustainable management of switchgrass

Total and horizontal distances of the foveal stereotaxic displacement can be prognostic indicators for patients with idiopathic epiretinal membrane

IntroductionThis study aimed to examine the foveal stereo deviations in the different ectopic inner foveal layer (EIFL) stages of idiopathic epiretinal membrane (iERM) and assess its predictive utility for the baseline and postoperative best-corrected visual acuity (BCVA).MethodsBased on the calculational combination of foveal displacements in the horizontal and vertical axial optical coherence tomography (OCT) images, the foveal stereotaxic displacement was estimated through the total distance (TD, the distance from the foveal bottom to the inner edge of displaced central foveal) and horizontal distance (HD, projection of the TD in the retinal plane). The preoperative TD, HD, and other OCT- and OCT angiography (OCTA)-related indicators were obtained. The correlations between structural parameters and baseline and postoperative BCVA were evaluated through correlation and multiple linear regression analyses.ResultsIn patients with advanced EIFL stage, there was a significant increase in the HD, TD, baseline log of the minimum angle of resolution unit for BCVA, central macular thickness (CMT), acircularity index, and incidence of microcystic macular edema (MME; p < 0.05). Further, they showed a decreased foveal avascular zone (FAZ) area and perimeter (p < 0.001). HD, TD, CMT, MME, FAZ area, and FAZ perimeter were significantly correlated with the baseline and postoperative BCVA (p < 0.05). TD had the highest correlation indexic and was an individual predictor of the baseline and postoperative BCVA. Moreover, FD-300 and MME were individual predictors of postoperative BCVA.DiscussionStereoscopic foveal deviations significantly correlated with the baseline and postoperative visual acuity. TD may be used as an independent prognostic factor for BCVA

Microbial functional diversity covaries with permafrost thaw-induced environmental heterogeneity in tundra soil.

Permafrost soil in high latitude tundra is one of the largest terrestrial carbon (C) stocks and is highly sensitive to climate warming. Understanding microbial responses to warming-induced environmental changes is critical to evaluating their influences on soil biogeochemical cycles. In this study, a functional gene array (i.e., geochip 4.2) was used to analyze the functional capacities of soil microbial communities collected from a naturally degrading permafrost region in Central Alaska. Varied thaw history was reported to be the main driver of soil and plant differences across a gradient of minimally, moderately, and extensively thawed sites. Compared with the minimally thawed site, the number of detected functional gene probes across the 15-65 cm depth profile at the moderately and extensively thawed sites decreased by 25% and 5%, while the community functional gene β-diversity increased by 34% and 45%, respectively, revealing decreased functional gene richness but increased community heterogeneity along the thaw progression. Particularly, the moderately thawed site contained microbial communities with the highest abundances of many genes involved in prokaryotic C degradation, ammonification, and nitrification processes, but lower abundances of fungal C decomposition and anaerobic-related genes. Significant correlations were observed between functional gene abundance and vascular plant primary productivity, suggesting that plant growth and species composition could be co-evolving traits together with microbial community composition. Altogether, this study reveals the complex responses of microbial functional potentials to thaw-related soil and plant changes and provides information on potential microbially mediated biogeochemical cycles in tundra ecosystems

Performance Analysis of Epidemic Routing in Delay Tolerant Networks with Overlapping Communities and Selfish Nodes

Routing in delay tolerant networks (DTN) adopts the store-carry-forward mode, and it requires nodes to forward data in a cooperative way. However, nodes may be not willing to help others in many applications and this behavior can be called as individual selfish. On the other hand, nodes often can be divided into different communities, and nodes in the same community often have some social ties. Due to these social ties, nodes are more willing to help the one in the same community, but not others. This behavior can be called as social selfish. Note that some nodes may belong to more than one community in the real world, and this phenomenon makes the network have overlapping communities. This paper proposed a theoretical model by the continuous time Markov process to describe the performance of epidemic routing (ER) in such network. Simulation results show the accuracy of our model. Numerical results show that the selfish nature can make the performance of the routing policy be worse, but those nodes belonging to multi-communities can decrease the impact of the selfish nature in some degree

Carbon-nitrogen interactions during afforestation in central China

We conducted a field study in Danjiangkou Reservoir region of central China to evaluate soil C and N dynamics following afforestation by comparing soil organic C and N (SOC and SON), soil net N mineralization and nitrification, and inorganic N concentrations in the plant rhizosphere and open areas in the forest, shrubland and adjacent cropland. Afforestation increased SOC but did not significantly affect SON in the plant rhizosphere. Due to large quantity of low-quality litter (with high C:N ratios) inputs, afforestation enhanced soil C recalcitrant indexes (RIC) but decreased soil N recalcitrance indexes (RIN) in the plant rhizosphere. Both SON and RIN significantly decreased following afforestation in the open areas. Afforestation decreased inorganic N concentrations and net N mineralization. Soil net N mineralization were negatively correlated with soil C:N ratios across land use types. These results suggest that afforestation could increase SOC stocks resulting from large low-quality litter input, but over the long-term, this increase was likely limited due to decreased soil N availability. (C) 2013 Elsevier Ltd. All rights reserved