Intra-domain Networks Research Articles

Soil microbial community assembly and stability are associated with potato (Solanum tuberosum L.) fitness under continuous cropping regime.

Continuous cropping obstacles caused by the over-cultivation of a single crop trigger soil degradation, yield reduction and the occurrence of plant disease. However, the relationships among stability, complexity and the assembly process of soil microbial community with continuous cropping obstacles remains unclear. In this study, molecular ecological networks analysis (MENs) and inter-domain ecological networks analysis (IDENs), and a new index named cohesion tools were used to calculate the stability and complexity of soil microbial communities from eight potato cultivars grown under a continuous cropping regime by using the high-throughput sequencing data. The results showed that the stability (i.e., robustness index) of the bacterial and fungal communities for cultivar ZS5 was significantly higher, and that the complexity (i.e., cohesion values) was also significantly higher in the bacterial, fungal and inter-domain communities (i.e., bacterial-fungal community) of cultivar ZS5 than other cultivars. Network analysis also revealed that Actinobacteria and Ascomycota were the dominant phyla within intra-domain networks of continuous cropping potato soil communities, while the phyla Proteobacteria and Ascomycota dominated the correlation of the bacterial-fungal network. Infer community assembly mechanism by phylogenetic-bin-based null model analysis (iCAMP) tools were used to calculate the soil bacterial and fungal communities’ assembly processes of the eight potato cultivars under continuous cropping regime, and the results showed that the bacterial community was mainly dominated by deterministic processes (64.19% - 81.31%) while the fungal community was mainly dominated by stochastic processes (78.28% - 98.99%), indicating that the continuous-cropping regime mainly influenced the potato soil bacterial community assembly process. Moreover, cultivar ZS5 possessed a relatively lower homogeneous selection, and a higher TP, TN, AP and yield than other cultivars. Our results indicated that the soil microbial network stability and complexity, and community assemble might be associated with yield and soil properties, which would be helpful in the study for resistance to potato continuous cropping obstacles.

Narrowband Radar Automatic Target Recognition Based on a Hierarchical Fusing Network With Multidomain Features

Narrowband radar automatic target recognition (ATR) is often implemented in a single-feature domain, where recognition performance is limited because only one target property is considered. Fusing features from multiple domains is an effective way to improve recognition accuracy. Existing fusion methods utilize simple fusion strategies, such as concatenation and addition, and the classier design is not considered. In this letter, a hierarchical fusion network (HFN) with multidomain features for narrowband radar ATR is proposed. The HFN contains an intradomain network and an interdomain network with abundant features in multiple domains from the radar echo signal as the input of the network. In the intradomain network, the autoencoder (AE) network is used to learn low-dimensional features and reduce the redundancy of features in the same domain. Moreover, the ratio of within-class distance to between-class distance is introduced into the intradomain network to increase the separability of low-dimensional features. The interdomain network fuses different domain features and obtains the classification result through neural networks. The intradomain and interdomain networks construct a whole framework with a unified loss function, which is jointly optimized via backpropagation. Experimental results on the aerial target data set (drones vs. birds) and the ground target data set (wheeled vehicles, tracked vehicles, and humans) demonstrate that the proposed method is effective for narrowband radar ATR.

Both intra and inter-domain interactions define the intrinsic dynamics and allosteric mechanism in DNMT1s

DNA methyltransferase 1 (DNMT1), a large multidomain enzyme, is believed to be involved in the passive transmission of genomic methylation patterns via methylation maintenance. Yet, the molecular mechanism of interaction networks underlying DNMT1 structures, dynamics, and its biological significance has yet to be fully characterized. In this work, we used an integrated computational strategy that combined coarse-grained and atomistic simulations with coevolution information and network modeling of the residue interactions for the systematic investigation of allosteric dynamics in DNMT1. The elastic network modeling has proposed that the high plasticity of RFTS has strengthened the correlated behaviors of DNMT1 structures through the hinge sites located at the RFTS-CD interface, which mediate the collective motions between domains. The perturbation response scanning (PRS) analysis combined with the enrichment analysis of disease mutations have further highlighted the allosteric potential of the RFTS domain. Furthermore, the long-range paths connect the intra-domain interactions through the TRD interface and catalytic interface, emphasizing some key inter-domain interactions as the bridges in the global allosteric regulation of DNMT1. The observed interplay between conserved intra-domain networks and dynamical plasticity encoded by inter-domain interactions provides insights into the intrinsic dynamics and functional evolution, as well as the design of allosteric modulators of DNMT1 based on the TRD interface.

Routing optimization for IP networks with loop-free alternates

Loop-free alternates (LFAs) have been developed for fast reroute (FRR) in intradomain IP networks. They are simple, standardized, and already offered by several vendors. However, LFAs have two major drawbacks. They often cannot provide failure protection against all single link or node failures in spite of physical connectedness, and some LFAs cause routing loops in scenarios with node or multiple failures.LFAs may be applied for various reasons that we call applications in this work. We propose several definitions for LFA coverage that quantify the application-specific utility of LFAs available in the network. The availability of LFAs and whether they can cause routing loops heavily depend on the IP routing which is determined by the choice of administrative IP link costs. To maximize the benefit of LFA usage, we optimize the IP link costs using LFA coverage as objective function. We demonstrate the feasibility and effectiveness of that approach in several test networks, and show that the choice of the right optimization function is crucial to maximize LFA coverage. However, maximizing LFA coverage can lead to significant traffic imbalance and may result in high link loads. Therefore, we suggest Pareto-optimization and demonstrate that resulting link costs can lead to both high LFA coverage and low link loads.

How Much to Coordinate? Optimizing In-Network Caching in Content-Centric Networks

In content-centric networks, it is challenging how to optimally provision in-network storage to cache contents, to balance the tradeoffs between the network performance and the provisioning cost. To address this problem, we first propose a holistic model for intradomain networks to characterize the network performance of routing contents to clients and the network cost incurred by globally coordinating the in-network storage capability. We then derive the optimal strategy for provisioning the storage capability that optimizes the overall network performance and cost, and analyze the performance gains via numerical evaluations on real network topologies. Our results reveal interesting phenomena; for instance, different ranges of the Zipf exponent can lead to opposite optimal strategies, and the tradeoffs between the network performance and the provisioning cost have great impacts on the stability of the optimal strategy. We also demonstrate that the optimal strategy can achieve significant gain on both the load reduction at origin servers and the improvement on the routing performance. Moreover, given an optimal coordination level $\ell^\ast$ , we design a routing-aware content placement (RACP) algorithm that runs on a centralized server. The algorithm computes and assigns contents to each CCN router to store, which can minimize the overall routing cost, e.g., transmission delay or hop counts, to deliver contents to clients. By conducting extensive simulations using a large-scale trace dataset collected from a commercial 3G network in China, our results demonstrate that our caching scheme can achieve 4% to 22% latency reduction on average over the state-of-the-art caching mechanisms.

Efficient techniques and tools for intra-domain traffic engineering

Intra-domain routing protocols are based on Shortest Path First (SPF) routing, where shortest paths are calculated between each pair of nodes (routers) using pre-assigned link weights, also referred to as link metric. These link weights can be modified by network administrators in accordance with the routing policies of the network operator. The operator's objective is usually to minimize traffic congestion or minimize total routing costs subject to the traffic demands and the protocol constraints. However, determining a link weight combination that meets a network operator's objectives is a difficult task. In this paper, we study the link weight optimization problem in intra-domain networks. This problem is proved to be NP-hard with hard protocol constraints, e.g., a flow is evenly distributed along the shortest paths between its origin and destination nodes. We present two fast heuristic approaches to generate efficient link metrics for intra-domain routing. Some promising experimental results are reported.