Resilience Notions for Scale-free Networks

AbstractMuch of traditional graph theoretic analysis of networks had focused on regular or near-regular network models such as random Erdos-Renyi models, where the degree distribution is either the same for every node or highly concentrated about the mean. As such, much beautiful theoretical machinery exists to analyze various properties including analysis of network resilience via eigenvalues of the adjacency matrix representing the network. However, it has been recently observed that real world networks tend to be scale-free, which usually implies a high variance and power-law degree distribution. This poses a problem in applying existing theoretical machinery to some problems, particularly that of the resilience of networks to node attacks. In this work we examine networks in which the greatest discrepancy arises in attempting to apply previous resilience notions, and we tailor a new mathematical notion of resilience that works for scale-free networks in the presence of node attacks

Soft morphological filter optimization using a genetic algorithm for noise elimination

Digital image quality is of importance in almost all image processing applications. Many different approaches have been proposed for restoring the image quality depending on the nature of the degradation. One of the most common problems that cause such degradation is impulse noise. In general, well known median filters are preferred for eliminating different types of noise. Soft morphological filters are recently introduced and have been in use for many purposes. In this study, we present a Genetic Algorithm (GA) which combines different objectives as a weighted sum under a single evaluation function and generates a soft morphological filter to deal with impulse noise, after a training process with small images. The automatically generated filter performs better than the median filter and achieves comparable results to the best known filters from the literature over a set of benchmark instances that are larger than the training instances. Moreover, although the training process involves only impulse noise added images, the same evolved filter performs better than the median filter for eliminating Gaussian noise as well

Soft morphological filter optimization using a genetic algorithm for noise elimination

Digital image quality is of importance in almost all image processing applications. Many different approaches have been proposed for restoring the image quality depending on the nature of the degradation. One of the most common problems that cause such degradation is impulse noise. In general, well known median filters are preferred for eliminating different types of noise. Soft morphological filters are recently introduced and have been in use for many purposes. In this study, we present a Genetic Algorithm (GA) which combines different objectives as a weighted sum under a single evaluation function and generates a soft morphological filter to deal with impulse noise, after a training process with small images. The automatically generated filter performs better than the median filter and achieves comparable results to the best known filters from the literature over a set of benchmark instances that are larger than the training instances. Moreover, although the training process involves only impulse noise added images, the same evolved filter performs better than the median filter for eliminating Gaussian noise as well

Simulating Retrieval from a Highly Clustered Network: Implications for Spoken Word Recognition

Network science describes how entities in complex systems interact, and argues that the structure of the network influences processing. Clustering coefficient, C – one measure of network structure – refers to the extent to which neighbors of a node are also neighbors of each other. Previous simulations suggest that networks with low C dissipate information (or disease) to a large portion of the network, whereas in networks with high C information (or disease) tends to be constrained to a smaller portion of the network (Newman, 2003). In the present simulation we examined how C influenced the spread of activation to a specific node, simulating retrieval of a specific lexical item in a phonological network. The results of the network simulation showed that words with lower C had higher activation values (indicating faster or more accurate retrieval from the lexicon) than words with higher C. These results suggest that a simple mechanism for lexical retrieval can account for the observations made in Chan and Vitevitch (2009), and have implications for diffusion dynamics in other fields

Postharvest Application of Thiol Compounds Affects Surface Browning and Antioxidant Activity of Fresh-Cut Potatoes

The aim of this study was to compare the effects of sodium metabisulphite and the thiol compounds, glutathione (GSH), L-cysteine (CYS), and N-acetylcysteine (NAC), on the enzymatic browning, antioxidant activities, total phenolic, and ascorbic acid content of potatoes after 1, 24, and 48 hr. Three different concentrations (0.5%, 1.0%, and 2.0%) of each thiol compound were tested. While sulphite solution inhibited polyphenol oxidase as expected, NAC and CYS also decreased its activity. CYS-treated samples exhibited the highest residual thiol content, while the amount of residual thiol in GSH-treated samples was the lowest. The 2.0% NAC and 2.0% CYS solutions were the most effective at increasing antioxidant activity and ascorbic acid content; however, the results of total phenolic content assays were complicated. In summary, solutions containing 2.0% NAC, 1.0% CYS, and 2.0% CYS prevented enzymatic browning and increased the residual thiol content, ascorbic acid, and antioxidant activities of fresh-cut potatoes significantly, but GSH did not significantly inhibit browning. Practical applications: Fresh-cut potatoes are susceptible to enzymatic browning, which significantly reduces their commercial value. In literature, there have been several methods to protect the enzymatic browning of fruits and vegetables. Among these methods, thiols are good inhibitors of enzymatic browning. So, GSH, CYS, and NAC were used in this study. The outcomes of current work may help to inhibit polyphenol oxidase activity and increase the ascorbic acid content, residual thiol content, and antioxidant activity of fresh-cut potatoes. Both CYS and NAC may be useful alternatives to sulphite anti-browning agents, which may have adverse health effects

Thiol Antioxidants Protect Human Lens Epithelial (HLE B-3) Cells Against Tert-Butyl Hydroperoxide-Induced Oxidative Damage and Cytotoxicity

Oxidative damage to lens epithelial cells plays an important role in the development of age-related cataract, and the health of the lens has important implications for overall ocular health. As a result, there is a need for effective therapeutic agents that prevent oxidative damage to the lens. Thiol antioxidants such as tiopronin or N-(2-mercaptopropionyl)glycine (MPG), N-acetylcysteine amide (NACA), N-acetylcysteine (NAC), and exogenous glutathione (GSH) may be promising candidates for this purpose, but their ability to protect lens epithelial cells is not well understood. The effectiveness of these compounds was compared by exposing human lens epithelial cells (HLE B-3) to the chemical oxidant tert-butyl hydroperoxide (tBHP) and treating the cells with each of the antioxidant compounds. MTT cell viability, apoptosis, reactive oxygen species (ROS), and levels of intracellular GSH, the most important antioxidant in the lens, were measured after treatment. All four compounds provided some degree of protection against tBHP-induced oxidative stress and cytotoxicity. Cells treated with NACA exhibited the highest viability after exposure to tBHP, as well as decreased ROS and increased intracellular GSH. Exogenous GSH also preserved viability and increased intracellular GSH levels. MPG scavenged significant amounts of ROS, and NAC increased intracellular GSH levels. Our results suggest that both scavenging ROS and increasing GSH may be necessary for effective protection of lens epithelial cells. Further, the compounds tested may be useful for the development of therapeutic strategies that aim to prevent oxidative damage to the lens

Prevention and Reversal of Selenite-Induced Cataracts by N-Acetylcysteine Amide in Wistar Rats

Background: The present study sought to evaluate the efficacy of N-acetylcysteine amide (NACA) eye drops in reversing the cataract formation induced by sodium selenite in male Wistar rat pups. Methods: Forty male Wistar rat pups were randomly divided into a control group, an N-acetylcysteine amide-only group, a sodium selenite-induced cataract group, and a NACA-treated sodium selenite-induced cataract group. Sodium selenite was injected intraperitoneally on postpartum day 10, whereas N-acetylcysteine amide was injected intraperitoneally on postpartum days 9, 11, and 13 in the respective groups. Cataracts were evaluated at the end of week 2 (postpartum day 14) when the rat pups opened their eyes. N-acetylcysteine amide eye drops were administered beginning on week 3 until the end of week 4 (postpartum days 15 to 30), and the rats were sacrificed at the end of week 4. Lenses were isolated and examined for oxidative stress parameters such as glutathione, lipid peroxidation, and calcium levels along with the glutathione reductase and thioltransferase enzyme activities. Casein zymography and Western blot of m-calpain were performed using the water soluble fraction of lens proteins. Results: Morphological examination of the lenses in the NACA-treated group indicated that NACA was able to reverse the cataract grade. In addition, glutathione level, thioltransferase activity, m-calpain activity, and m-calpain level (as assessed by Western blot) were all significantly higher in the NACA-treated group than in the sodium selenite-induced cataract group. Furthermore, sodium selenite- injected rat pups had significantly higher levels of malondialdehyde, glutathione reductase enzyme activity, and calcium levels, which were reduced to control levels upon treatment with NACA. Conclusions: The data suggest that NACA has the potential to significantly improve vision and decrease the burden of cataract-related loss of function. Prevention and reversal of cataract formation could have a global impact. Development of pharmacological agents like NACA may eventually prevent cataract formation in high-risk populations and may prevent progression of early-stage cataracts. This brings a paradigm shift from expensive surgical treatment of cataracts to relatively inexpensive prevention of vision loss