Pluggable SDN framework for managing heterogeneous SDN networks

Software‐defined networking (SDN) is a new network paradigm that is separating the data plane and the control plane of the network, making one or more centralized controllers to supervise the behaviour of the entire network. Different types of SDN controller software exist, and research dealing with the difficulties of consistently integrating these different controller types has mostly been declared future work. In this paper, the Domino framework is proposed, a pluggable SDN framework for managing heterogeneous SDN networks. In contrast to related work, the proposed framework allows research into SDN networks controlled by different types of SDN controllers attempting to standardize the northbound API of them. Domino implements a microservice plugin architecture where users can link different SDN networks to a processing algorithm. Such an algorithm allows for, eg, adapting the flows by building a pipeline using plugins that either invoke other SDN operations or generic data processing algorithms. The Domino framework is evaluated by implementing a proof‐of‐concept implementation, which is tested on the initial requirements. It achieves the modifiability and the interoperability with an average successful exchange ratio of 99.99%. The performance requirements are met for the frequently used commands with an average response time of 0.26 seconds, and the framework can handle at least 72 plugins simultaneously depending on the available amount of RAM. The proposed framework is evaluated by means of the implementation of a shortest path routing algorithm between heterogeneous SDN networks.     

Towards distributed emergency flow prioritization in software-defined networks

Emergency services must be able to transfer data with high priority over different networks. With 5G, slicing concepts at mobile network connections are introduced, allowing operators to divide portions of their network for specific use cases. In addition, Software-Defined Networking (SDN) principles allow to assign different Quality-of-Service (QoS) levels to different network slices. This paper proposes a microservices-based framework, able to run both centralized and distributed, that guarantees the required bandwidth for the emergency flows and maximizes the best-effort flows over the remaining bandwidth based on their priority. The proposed framework consists of an offline linear model, allowing to optimize the problem for a batch of flow requests. For dynamic situations, an online approach is also required in the framework to handle new incoming flows by calculating the path with a shortest path algorithm and utilizing a greedy approach in assigning bandwidth to the intermediate flows. In this article, the linear model is evaluated through simulation, the distributed architecture is evaluated through emulation while the online approach is validated through physical experiments with SDN switches. The results show that the linear model is able to guarantee the resource allocation for the emergency flows while optimizing the best-effort flows with a sub-second execution time. The distributed architecture is able to split up the managed network into different parts, allowing division of work between controllers. As a proof-of-concept, a prototype with Zodiac switches validates the feasibility of the centralized framework.     

Statistical analysis of the mechanical properties of natural fibers and their composite materials. I. Natural fibers

In this study, we extended a statistical approach to develop a comparative study on the behavior of different natural fibers such as flax, jute, abaca, and sisal. In particular, the dimensional characterization and mechanical properties of natural fibers were considered. The wide dispersion of fiber properties, which is a well‐known characteristic of natural systems, has been described here by means of a new advanced statistical approach based on neural network algorithms that can provide a more accurate prediction of the behavior of natural fibers. The new statistical model was developed to interpolate the experimental data, using algorithms based on neural networks. POLYM. COMPOS., 2008. © 2008 Society of Plastics Engineers     

Statistical analysis of the mechanical properties of natural fibers and their composite materials. II. Composite materials

In this study, the tensile behavior of different natural fiber reinforced composite materials were analyzed. The statistical analysis used to study the natural fibers in the first article, has been extended to analyze the behavior of PP‐matrix composites, combining the probability density function estimation of fiber properties with the Halpin‐Tsai equation. In this case, the advanced statistical approach overestimates the mechanical properties of the composites, probably because of the poor matrix‐fiber adhesion between polypropylene and natural fibers in the real system. POLYM. COMPOS., 2008. © 2008 Society of Plastics Engineers     

Desertification? Northern Ethiopia re-photographed after 140 years

A collection of sepia photographs, taken during Great Britain's military expedition to Abyssinia in 1868, are the oldest landscape photographs from northern Ethiopia, and have been used to compare the status of vegetation and land management 140 years ago with that of contemporary times. Thirteen repeat landscape photographs, taken during the dry seasons of 1868 and 2008, were analyzed for various environmental indicators and show a significant improvement of vegetation cover. New eucalypt woodlands, introduced since the 1950s are visible and have provided a valuable alternative for house construction and fuel-wood, but more importantly there has also been locally important natural regeneration of indigenous trees and shrubs. The situation in respect to soil and water conservation measures in farmlands has also improved. According to both historical information and measured climatic data, rainfall conditions around 1868 and in the late 19th century were similar to those of the late 20th/early 21st century. Furthermore, despite a ten-fold increase in population density, land rehabilitation has been accomplished over extensive areas by large-scale implementation of reforestation and terracing activities, especially in the last two decades. In some cases repeat photography shows however that riparian vegetation has been washed away. This is related to river widening in recent degradation periods, particularly in the 1970s-1980s. More recently, riverbeds have become stabilized, and indicate a decreased runoff response. Environmental recovery programmes could not heal all scars, but this study shows that overall there has been a remarkable recovery of vegetation and also improved soil protection over the last 140 years, thereby invalidating hypotheses of the irreversibility of land degradation in semi-arid areas. In a highly degraded environment with high pressure on the land, rural communities were left with no alternative but to improve land husbandry: in northern Ethiopia such interventions have been demonstrably successful.     

A systematic investigation on the influence of the chemical treatment of natural fibers on the properties of their polymer matrix composites

This paper reports a systematic study of the effects on composite properties of different chemical treatments on natural fibers. Both short flax fibers and flax cellulose pulp in a polypropylene matrix have been investigated. The influence of treatments on fiber properties was investigated by means of spectroscopic, thermal and mechanical tests. Moreover, the effects of fiber treatment on the crystallinity of the matrix were analyzed using differential scanning calorimetry and optical microscopy. The mechanical properties of the composites obtained were studied using tensile and bending tests. It is shown that most of the main properties of the composites can be improved by adequately treating the fibers. The results of this study provide a database mainly devoted to material selection for the automotive industry. This research has been performed as a part of the ECOFINA project in the framework of the 5th European Research Program of the European Community. Polym. Compos. 25:470–479, 2004. © 2004 Society of Plastics Engineers.     

Comparative study of the effects of different fibers on the processing and properties of ternary composites based on PP-EPDM blends

The effects of the incorporation of different kinds of fibers on the physical and mechanical properties of thermoplastics elastomers based on blends of isotactic polypropylene (iPP) and ethylene-propylene diene rubber (EPDM) are described. For this purpose, three different compositions of PP-EPDM blends reinforced with fibers are studied and reported here. In particular, the flow behavior, mechanical properties (tensile, flexural and impact resistance) and morphology are examined. Rheological measurements confirm the viscosity increase of thermoplastics elastomers with the incorporation of the fibers. This increment is more evident in the presence of aramid fibers. In addition, the results obtained by dynamic-mechanical analysis and mechanical properties show that the fibers act as an effective reinforcing agent of PP-EPDM blends. In fact, a significant increase of the modulus and strength is obtained in presence of all fibers, this effect being more noticeable at higher elastomer percentages in the thermoplastic. The morphology of the ternary composites is also analyzed by scanning electron microscopy (SEM). A good interfacial adhesion between fibers and matrix is observed, but also in this case, aramid fibers are the most effective ones.     

Rheological behavior and processability of polypropylene blends with rubber ethylene propylene diene terpolymer

A study of the dynamic complex and steady shear viscosity of isotactic polypropylene (iPP), ethylene–propylene diene terpolymer rubber (EPDM) and three different blends of both polymers are presented over a range of temperatures and frequencies. Moreover, the processability of these materials is studied through torque measurements during blend mixing. The results obtained show that the viscosity gradually increases with rubber content in the blend and decreases with both temperature and frequency. Plots of η″ versus η′ (Cole–Cole plots) show that the blend with the lower rubber content (25%), has a certain rheological compatibility with neat PP. Furthermore, torque curves measured during blend mixing confirm these results, demonstrating that the blend with 25% of elastomer has a similar behavior of iPP during processing. To analyze the morphological structure of the blends, a dynamic mechanical analysis of the solid state is also presented. It is observed that the blends have two distinct values of T_g close to the corresponding values of the pure polymers, confirming that this type of blends based on a semicrystalline polymer and an amorphous elastomer forms a two‐phase system with a limited degree of miscibility between both components. In addition, the polymer present with the higher concentration forms the continuous phase and controls the rheological properties of the blend. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 81: 1–10, 2001     

Predicting Proteolysis in Complex Proteomes Using Deep Learning

Both protease- and reactive oxygen species (ROS)-mediated proteolysis are thought to be key effectors of tissue remodeling. We have previously shown that comparison of amino acid composition can predict the differential susceptibilities of proteins to photo-oxidation. However, predicting protein susceptibility to endogenous proteases remains challenging. Here, we aim to develop bioinformatics tools to (i) predict cleavage site locations (and hence putative protein susceptibilities) and (ii) compare the predicted vulnerabilities of skin proteins to protease- and ROS-mediated proteolysis. The first goal of this study was to experimentally evaluate the ability of existing protease cleavage site prediction models (PROSPER and DeepCleave) to identify experimentally determined MMP9 cleavage sites in two purified proteins and in a complex human dermal fibroblast-derived extracellular matrix (ECM) proteome. We subsequently developed deep bidirectional recurrent neural network (BRNN) models to predict cleavage sites for 14 tissue proteases. The predictions of the new models were tested against experimental datasets and combined with amino acid composition analysis (to predict ultraviolet radiation (UVR)/ROS susceptibility) in a new web app: the Manchester proteome susceptibility calculator (MPSC). The BRNN models performed better in predicting cleavage sites in native dermal ECM proteins than existing models (DeepCleave and PROSPER), and application of MPSC to the skin proteome suggests that: compared with the elastic fiber network, fibrillar collagens may be susceptible primarily to protease-mediated proteolysis. We also identify additional putative targets of oxidative damage (dermatopontin, fibulins and defensins) and protease action (laminins and nidogen). MPSC has the potential to identify potential targets of proteolysis in disparate tissues and disease states.     

Starch‐based biocomposite films reinforced with cellulose nanocrystals from garlic stalks

The study was conducted to reinforce starch‐based biocomposite films using cellulose nanocrystals (CNCs) from garlic stalks. An average yield of 4.6% by mass based from air‐dried garlic stalks was obtained through alkali delignification, acid hydrolysis and sonication. The isolated CNCs are spherical and have an average diameter of 35 nm and crystallinity of 62%. Fourier transform infrared spectra correspond to the structure of cellulose, but some absorption bands corresponding to hemicelluloses were also noticed. Starch‐based biocomposite films with varying amount of the isolated CNCs as reinforcing filler were prepared by solution casting and evaporation method. Scanning electron micrographs of the films showed homogeneous dispersion of CNC in the starch matrix. Improvement in tensile strength and modulus was at maximum when the starch to CNC ratio is 100:5. The thermal stability of the films, on the other hand, decreased with the addition of CNC. Finally, CNC‐reinforced films had lower moisture uptake than nonreinforced films. POLYM. COMPOS. 34:1325–1332, 2013. © 2013 Society of Plastics Engineers