Survivable design in WDM mesh networks

This dissertation addresses several important survivable design issues in WDM mesh networks;Shared backup path protection has been shown to be efficient in terms of capacity utilization, due to the sharing of backup capacity. However, sharing of backup capacity also complicates the restoration process, and leads to slow recovery. The p-cycle scheme is the most efficient ring-type protection method in terms of capacity utilization. Recently, the concept of pre-cross-connected protection was proposed to increase the recovery speed of shared path protection. We overview these protection methods. The recovery time of these schemes are compared analytically. We formulate integer programming optimization problems for three protection methods in static traffic scenario, considering wavelength continuity constraint;We develop a p-cycle based scheme to deal with dynamic traffic in WDM networks. We use a two-step approach. In first step, we find a set of p-cycles to cover the network and reserve enough capacity in p-cycles. In second step, we route the requests as they randomly arrive one by one. We propose two routing algorithms. Compared to the shared path protection, the p-cycle based design has the advantage of fast recovery, less control signaling, less dynamic state information to be maintained. To evaluate the blocking performance of proposed method, we compare it with shared backup path protection by extensive simulations;We propose a path-based protection method for two-link failures in mesh optical networks. We identify the scenarios where the backup paths can share their wavelengths without violating 100% restoration guarantee (backup multiplexing). We use integer linear programming to optimize the total capacity requirement for both dedicated- and shared-path protection schemes;The recently proposed light trail architecture offers a promising candidate for carrying IP centric traffic over optical networks. The survivable design is a critical part of the integral process of network design and operation. We propose and compare two protection schemes. The survivable light trail design problem using connection based protection model is solved using a two-step approach. (Abstract shortened by UMI.

Capacity optimization for surviving double-link failures in mesh-restorable optical networks

Network survivability is a crucial requirement in high-speed optical networks. Most research to date has been focused on the failure of a single component such as a link or a node. A double-link failures model in which any two links in the network may fail in an arbitrary order was proposed recently in literature. Three loop-back methods of recovering from double-link failures were also presented. The basic idea behind these methods is to pre-compute two backup paths for each link on the primary paths and reserve resources on these paths. Compared to protection methods for single-link failure model, the protection methods for double-link failure model require much more spare capacity. Reserving dedicated resources on every backup path at the time of establishing primary path itself would reserve excessive resources. In this thesis, we capture the surviving double link failures in WDM optical networks as a single Integer Linear Programming (ILP) based optimization problem. We use the double-link failures recovery method available in literature, develop rules to identify the scenarios where the backup capacity among intersecting demand sets can be shared. We employ the backup multiplexing technique and use ILP to optimize the capacity requirement while providing 100% protection for double-link failures. The numerical results indicate that, for the given example network and randomly picked demand matrix, the shared-link protection scheme that uses backup multiplexing provides 10-15% saving in capacity utilization over the dedicated-link protection scheme that reserves dedicated capacity on two backup paths for each link. The main contribution of this thesis is that we provide a way of adapting the heuristic based double-link failure recovery method into a mathematical framework, and use technique to improve wavelength utilization for optimal capacity usage

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities

Characterization of a pathway-specific activator of milbemycin biosynthesis and improved milbemycin production by its overexpression in Streptomyces bingchenggensis

Additional file 3: Figure S3. Diagrams of site-directed mutation of Walker A and Walker B motifs in MilR. A: Mutation in Walker A motif. The first line shows the wild-type Walker A sequence. From the second to the eighth line, red words indicate the Ala or Arg substitution was performed in the corresponding position. B: Mutation in Walker B motif. The first line shows the wild-type Walker B sequence, from the second to the third line, blue words indicate the Ala substitution was carried out to replace Asp in the corresponding position

Infectomic Analysis of Gene Expression Profiles of Human Brain Microvascular Endothelial Cells Infected with Cryptococcus neoformans

In order to dissect the pathogenesis of Cryptococcus neoformans meningoencephalitis, a genomic survey of the changes in gene expression of human brain microvascular endothelial cells infected by C. neoformans was carried out in a time-course study. Principal component analysis (PCA) revealed significant fluctuations in the expression levels of different groups of genes during the pathogen-host interaction. Self-organizing map (SOM) analysis revealed that most genes were up- or downregulated 2 folds or more at least at one time point during the pathogen-host engagement. The microarray data were validated by Western blot analysis of a group of genes, including β-actin, Bcl-x, CD47, Bax, Bad, and Bcl-2. Hierarchical cluster profile showed that 61 out of 66 listed interferon genes were changed at least at one time point. Similarly, the active responses in expression of MHC genes were detected at all stages of the interaction. Taken together, our infectomic approaches suggest that the host cells significantly change the gene profiles and also actively participate in immunoregulations of the central nervous system (CNS) during C. neoformans infection

Capacity optimization for surviving double-Link failures in mesh-restorable optical networks

Most research to date in survivable optical network design and operation, focused on the failure of a single component such as a link or a node. A double-link failure model in which any two links in the network may fail in an arbitrary order was proposed recently in literature. Three loop-back methods of recovering from double-link failures were also presented. The basic idea behind these methods is to pre-compute two backup paths for each link on the primary paths and reserve resources on these paths. Compared to protection methods for single-link failure model, the protection methods for double-link failure model require much more spare capacity. Reserving dedicated resources on every backup path at the time of establishing primary path itself would consume excessive resources. In Ref. 2 and 3, we captured the various operational phases in survivable WDM networks as a single integer programming based (ILP) optimization problem. In this work, we extend our optimization framework to include double-link failures. We use the double-link failure recovery methods available in literature, employ backup multiplexing schemes to optimize capacity utilization, and provide 100\% protection guarantee for double-link failure recovery. We develop rules to identify scenarios when capacity sharing among interacting demand sets is possible. Our results indicate that for the double-link failure recovery methods, the shared-link protection scheme provides 10-15\% savings in capacity utilization over the dedicated link protection scheme which reserves dedicated capacity on two backup paths for each link. We provide a way of adapting the heuristic based double-link failure recovery methods into a mathematical framework, and use techniques to improve wavelength utilization for optimal capacity usage

A lightweight dual-branch semantic segmentation network for enhanced obstacle detection in ship navigation

Semantic segmentation is essential for ship navigation as it enables the identification and understanding of semantic regions, thereby enhancing the navigational capabilities of smart ships. However, current deep learning techniques encounter challenges in balancing model size and segmentation accuracy due to the complexity of water surface features. In response, we propose a novel lightweight dual-branch semantic segmentation network. The model initially utilizes a specially designed dual-branch backbone to independently extract local details and global semantics from water surface images. The detail branch compresses and reconstructs feature information to mitigate interference from water dynamics, while the semantic branch efficiently expands the receptive field to capture global object relationships. Additionally, we introduce an aggregation module that holistically guides the feature responses to facilitate the sufficient aggregation of dual-branch information. Furthermore, a cascaded fusion approach is proposed to restore diminished localization precision, while also ensuring fusion accuracy by leveraging the segmentation attributes of deep features. Experimental results on visible light datasets from real navigation scenarios demonstrate that our network achieves approximately a 10% improvement in obstacle detection precision compared to existing advanced maritime models. Moreover, within the domain of the latest lightweight and real-time research, our network attains an optimal balance among accuracy, parameter efficiency, and real-time performance. This contributes to enhancing the navigation safety of intelligent vessels and promotes adaptability for onboard deployment

Optimal light trail design in WDM optical networks

The enabling technology for supporting IP centric traffic over optical transport networks evolves as the amount of traffic grows. In this paper, we first review a recently proposed concept called light trails. Light trails can enable high speed provisioning, accommodate multigranularity traffic, support high data rates and offer a good candidate for carrying IP traffic over optical networks. Next, we focus on light trail design. We propose a two-step approach for solving the light trail design problem. The first step is called traffic matrix preprocessing, it divides single long hop paths into several shorter paths that satisfy the hop-length constraint. In the second step, the light trail design problem is formulated as an integer linear programming (ILP) optimization problem. The results obtained from our experiments show that the resulting light trail network has high wavelength utilization

Durable, Low-cost, Improved Fuel Cell Membranes

The development of low cost, durable membranes and membranes electrode assemblies (MEAs) that operate under reduced relative humidity (RH) conditions remain a critical challenge for the successful introduction of fuel cells into mass markets. It was the goal of the team lead by Arkema, Inc. to address these shortages. Thus, this project addresses the following technical barriers from the fuel cells section of the Hydrogen Fuel Cells and Infrastructure Technologies Program Multi-Year Research, Development and Demonstration Plan: (A) Durability (B) Cost Arkema’s approach consisted of using blends of polyvinylidenefluoride (PVDF) and proprietary sulfonated polyelectrolytes. In the traditional approach to polyelectrolytes for proton exchange membranes (PEM), all the required properties are “packaged” in one macromolecule. The properties of interest include proton conductivity, mechanical properties, durability, and water/gas transport. This is the case, for example, for perfluorosulfonic acid-containing (PFSA) membranes. However, the cost of these materials is high, largely due to the complexity and the number of steps involved in their synthesis. In addition, they suffer other shortcomings such as mediocre mechanical properties and insufficient durability for some applications. The strength and originality of Arkema’s approach lies in the decoupling of ion conductivity from the other requirements. Kynar® PVDF provides an exceptional combination of properties that make it ideally suited for a membrane matrix (Kynar® is a registered trademark of Arkema Inc.). It exhibits outstanding chemical resistance in highly oxidative and acidic environments. In work with a prior grant, a membrane known as M41 was developed by Arkema. M41 had many of the properties needed for a high performance PEM, but had a significant deficiency in conductivity at low RH. In the first phase of this work, the processing parameters of M41 were explored as a means to increase its proton conductivity. Optimizing the processing of M41 was found to increase its proton conductivity by almost an order of magnitude at 50% RH. Characterization of the membrane morphology with Karren More at Oak Ridge National Laboratory showed that the membrane morphology was complex. This technology platform was dubbed M43 and was used as a baseline in the majority of the work on the project. Although its performance was superior to M41, M43 still showed proton conductivity an order of magnitude lower than that of a PFSA membrane at 50% RH. The MEA performance of M43 could be increased by reducing the thickness from 1 to 0.6 mils. However, the performance of the thinner M43 still did not match that of a PFSA membrane