Migration cost optimization for service provider legacy network migration to software-defined IPv6 network

This paper studies a problem for seamless migration of legacy networks of Internet service providers to a software-defined networking (SDN)-based architecture along with the transition to the full adoption of the Internet protocol version 6 (IPv6) connectivity. Migration of currently running legacy IPv4 networks into such new approaches requires either upgrades or replacement of existing networking devices and technologies that are actively operating. The joint migration to SDN and IPv6 network is considered to be vital in terms of migration cost optimization, skilled human resource management, and other critical factors. In this work, we first present the approaches of SDN and IPv6 migration in service providers' networks. Then, we present the common concerns of IPv6 and SDN migration with joint transition strategies so that the cost associated with joint migration is minimized to lower than that of the individual migration. For the incremental adoption of software-defined IPv6 (SoDIP6) network with optimum migration cost, a greedy algorithm is proposed based on optimal path and the customer priority. Simulation and empirical analysis show that a unified transition planning to SoDIP6 network results in lower migration cost.     

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10?000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.     

Evaluation of <Emphasis Type="Italic">flaA</Emphasis> Short Variable Region Sequencing,Multilocus Sequence Typing,and Fourier Transform Infrared Spectroscopy for Discrimination between <Emphasis Type="Italic">Campylobacter jejuni</Emphasis> Strains

Discriminatory and robust typing methods are needed to improve the understanding of the dynamics of food-borne Campylobacter infections and epidemiology in primary animal production. To evaluate the strain discriminatory potential of typing methods, flaA short variable region (SVR) sequencing and Fourier transform infrared (FTIR) spectroscopy were applied on a collection of 102 epidemiologically related and unrelated Campylobacter jejuni strains. Previous application of FTIR spectroscopy for subtyping of Campylobacter has been limited. A subset of isolates, initially discriminated by flaA SVR sequencing, were further subjected to multilocus sequence typing (MLST). It was found that flaA SVR sequencing had a slightly higher discriminatory power than FTIR spectroscopy, based on the Simpson diversity index. The clustering of strains indicated that FTIR spectroscopy is indeed a suitable method for discrimination of Campylobacter. The isolates were assigned to six clusters based on flaA SVR sequences and nine clusters based on the FTIR spectroscopy profiles. Furthermore, the cluster analysis of flaA SVR sequences, MLST, and FTIR spectroscopy profiles showed a high degree of congruence, assigning the isolates to similar cluster structures. In conclusion, FTIR spectroscopy can be applied for subtyping of Campylobacter, and the high discriminatory potential of both flaA SVR sequencing and FTIR spectroscopy render them suitable screening methods for large numbers of strains.     

Geranylgeraniol and Neurological Impairment: Involvement of Apoptosis and Mitochondrial Morphology

Deregulation of the cholesterol pathway is an anomaly observed in human diseases, many of which have in common neurological involvement and unknown pathogenesis. In this study we have used Mevalonate Kinase Deficiency (MKD) as a disease-model in order to investigate the link between the deregulation of the mevalonate pathway and the consequent neurodegeneration. The blocking of the mevalonate pathway in a neuronal cell line (Daoy), using statins or mevalonate, induced an increase in the expression of the inflammasome gene (NLRP3) and programmed cell death related to mitochondrial dysfunction. The morphology of the mitochondria changed, clearly showing the damage induced by oxidative stress and the decreased membrane potential associated with the alterations of the mitochondrial function. The co-administration of geranylgeraniol (GGOH) reduced the inflammatory marker and the damage of the mitochondria, maintaining its shape and components. Our data allow us to speculate about the mechanism by which isoprenoids are able to rescue the inflammatory marker in neuronal cells, independently from the block of the mevalonate pathway, and about the fact that cell death is mitochondria-related.     

Matter Timed

At best, the ageing of materials is regarded as lending a patina to historic buildings. In reality, however, materials often age disgracefully and unevenly, requiring a high level of maintenance and refurbishment. What if materials could be engineered and integrated into buildings not only to enhance but to heal? Martina Decker , Assistant Professor in the College of Architecture and Design at the New Jersey Institute of Technology (NJIT), looks at pioneering research that is being undertaken into performative, time-dependent materials.     

Lake extent changes in Basotu,Tanzania: a mixed-methods approach to understanding the impacts of anthropogenic influence and climate variability

Incompatible land use is a major contributor to ecosystem degradation, and is often exacerbated by climate change impacts. We investigate Lake Basotu, Tanzania as a case study where natural lake variability has been affected by agricultural land use. Comparisons between a satellite-derived history of lake surface area, local precipitation records, and corresponding anthropogenic activity show the impacts of agricultural and historical practices. We argue that insufficient consideration to the wider ecological impacts of large agricultural projects has lasting implications. This is particularly true in semi-arid environments where food production demands need to be continuously met. In the future, major conservation strategies should be investigated to maintain the environmental integrity and sustainability of freshwater resources.     

Preceramic polymer‐derived SiOC fibers by electrospinning

Silicon oxycarbide (SiOC) fibers with different chemical compositions were successfully fabricated by electrospinning a mixture of polyvinylpyrrolidone (PVP) and commercially available polymethylsilsesquioxane (MK) or polymethylphenylsilsesquioxane (H44) preceramic polymers, followed by cross‐linking and pyrolysis at 1000°C in Argon. The influence of the processing procedure (solvent selection, cross‐linking catalyst and additives) on the morphology of the produced fibers was investigated. For the MK/isopropanol system, the introduction of 20 vol% N,N‐dimethylformamide (DMF) enabled to decrease the diameter of the as‐spun fibers from 2.72 ± 0.12 μm to 1.65 ± 0.09 μm. For the H44/DMF systems, beads‐free fibers were obtained by adding 50 vol% choloroform. After pyrolysis, the resultant SiOC fibers derived from MK and H44 resins possessed uniform morphology, with an average diameter of 0.97 ± 0.07 μm and 1.07 ± 0.08 μm, respectively. Due to their different chemical compositions, the MK‐derived and H44‐derived SiOC ceramic fibers could find different potential applications. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 39836.     

How Different Characterization Techniques Elucidate the Nature of the Gold Species in a Polycrystalline Au/TiO2 Catalyst

TiO₂‐supported gold species were prepared via the deposition‐precipitation route, with conservation of the initial speciation by freeze‐drying. The structural and electronic properties of the Au species were investigated by X‐ray absorption spectroscopy, electron microscopy, and IR spectroscopy of adsorbed CO in four states. Exclusively Au^III was deposited on the TiO₂ surface in patches ranging from isolated Au ions to three‐dimensional clusters. This paper illustrates in detail the unique contributions of all characterization techniques to this structural model.