Requirements for optimization of electrodes and electrolyte for the iron/chromium Redox flow cell

Improved catalyzation techniques that included a pretreatment of carbon substrate and provided normalized carbon surface for uniform gold deposition were developed. This permits efficient use of different batches of carbon felt materials which initially vary significantly in their physical and surface chemical properties, as well as their electrochemical behavior. Further modification of gold impregnation technique gave the best performing electrodes. In addition to the linear sweep voltammetry, cyclic voltammetry was used to determine the effects of different activation procedures on the Cr(3)/Cr(2) Redox and H2 evolution reactions. The roles of carbon, gold and lead in the overall Redox cycle are identified. The behavior of the electrodes at both normal battery operating potentials and more extreme potentials is discussed preparing efficient and stable electrodes for the energy storage battery is implicated

Deformed Gaussian Orthogonal Ensemble description of Small-World networks

The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, Random Matrix Theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully chaotic behavior it has been found that an extrapolation formula of the Brody type can be used. In the present paper we analyze the regular to chaotic behavior of Small World (SW) networks using an extension of the Gaussian Orthogonal Ensemble. This RMT ensemble, coined the Deformed Gaussian Orthogonal Ensemble (DGOE), supplies a natural foundation of the Brody formula. SW networks follow GOE statistics till certain range of eigenvalues correlations depending upon the strength of random connections. We show that for these regimes of SW networks where spectral correlations do not follow GOE beyond certain range, DGOE statistics models the correlations very well. The analysis performed in this paper proves the utility of the DGOE in network physics, as much as it has been useful in other physical systems.Comment: Replaced with the revised version, accepted for publication in Phys. Rev.

Spectral analysis of Gene co-expression network of Zebrafish

We analyze the gene expression data of Zebrafish under the combined framework of complex networks and random matrix theory. The nearest neighbor spacing distribution of the corresponding matrix spectra follows random matrix predictions of Gaussian orthogonal statistics. Based on the eigenvector analysis we can divide the spectra into two parts, first part for which the eigenvector localization properties match with the random matrix theory predictions, and the second part for which they show deviation from the theory and hence are useful to understand the system dependent properties. Spectra with the localized eigenvectors can be characterized into three groups based on the eigenvalues. We explore the position of localized nodes from these different categories. Using an overlap measure, we find that the top contributing nodes in the different groups carry distinguished structural features. Furthermore, the top contributing nodes of the different localized eigenvectors corresponding to the lower eigenvalue regime form different densely connected structure well separated from each other. Preliminary biological interpretation of the genes, associated with the top contributing nodes in the localized eigenvectors, suggests that the genes corresponding to same vector share common features.Comment: 6 pages, four figures (accepted in EPL

Interplay of degree correlations and cluster synchronization

We study the evolution of coupled chaotic dynamics on networks and investigate the role of degree-degree correlation in the networks' cluster synchronizability. We find that an increase in the disassortativity can lead to an increase or a decrease in the cluster synchronizability depending on the degree distribution and average connectivity of the network. Networks with heterogeneous degree distribution exhibit significant changes in cluster synchronizability as well as in the phenomena behind cluster synchronization as compared to those of homogeneous networks. Interestingly, cluster synchronizability of a network may be very different from global synchronizability due to the presence of the driven phenomenon behind the cluster formation. Furthermore, we show how degeneracy at the zero eigenvalues provides an understanding of the occurrence of the driven phenomenon behind the synchronization in disassortative networks. The results demonstrate the importance of degree-degree correlations in determining cluster synchronization behavior of complex networks and hence have potential applications in understanding and predicting dynamical behavior of complex systems ranging from brain to social systems

Low myo-inositol and high glutamine levels in brain are associated with neuropsychological deterioration after induced hyperammonemia

The neuropsychological effect of hyperammonemia is variable. This study tests the hypothesis that the effect of ammonia on the neuropsychological function in patients with cirrhosis is determined by the ability of the brain to buffer ammonia-induced increase in glutamine within the astrocyte by losing osmolytes like myo-inositol (mI) and not by the magnitude of the induced hyperammonemia. Fourteen cirrhotic patients with no evidence of overt hepatic encephalopathy were given a 75-g amino acid (aa) solution mimicking the hemoglobin molecule to induce hyperammonemia. Measurement of a battery of neuropsychological function tests including immediate memory, ammonia, aa, and short-echo time proton magnetic resonance spectroscopy were performed before and 4 h after administration of the as solution. Eight patients showed deterioration in the Immediate Memory Test at 4 h. Demographic factors, severity of liver disease, change in plasma ammonia, and as profiles after the as solution were similar in those that showed a deterioration compared with those who did not. In patients who showed deterioration in the memory test, the mI-to-creatine ratio (mI/Cr) was significantly lower at baseline than those that did not deteriorate. In contrast, the glutamate/glutamine-to-Cr ratio was significantly greater in the patients that deteriorated. The observation that deterioration in the memory test scores was greater in those with lower mI/Cr supports the hypothesis that the neuropsychological effects of induced hyperammonemia is determined by the capacity of the brain to handle ammonia-induced increase in glutamine

'Equity' and 'Justice' for patients with acute-on chronic liver failure: A call to action

Acute-on chronic liver failure (ACLF) occurs in hospitalised patients with cirrhosis and is characterised by multiorgan failures and high rates of short-term mortality. Without liver transplantation (LT), the 28-day mortality of patients with ACLF ranges between 18-25% in those with ACLF Grade 1 to 68-89% in those with ACLF Grade 3. It has become clear that there is lack of equity of access to LT for patients with ACLF across the world due to the current allocation policies, which are based on prognostic scores that underestimate the risk of death of these patients and lack of appreciation that there is clear evidence of transplant benefit for carefully selected patients as they can have excellent post-LT outcomes. This expert opinion provides evidence supporting the argument that patients with ACLF should be given priority for LT using prognostic models that define the risk of death for these patients, pinpoint risk factors for poor post-LT outcomes, identify unanswered questions and describe the design of a global study, the CHANCE study, which will provide answers to the outstanding issues. It also suggests widespread adoption of pilot programmes across the world as have been initiated in the UK and recommended in Spain to introduce new policies for organ allocation for patients with ACLF

Random matrix analysis of localization properties of Gene co-expression network

We analyze gene co-expression network under the random matrix theory framework. The nearest neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral rigidity test follows random matrix prediction for a certain range, and deviates after wards. Eigenvector analysis of the network using inverse participation ratio (IPR) suggests that the statistics of bulk of the eigenvalues of network is consistent with those of the real symmetric random matrix, whereas few eigenvalues are localized. Based on these IPR calculations, we can divide eigenvalues in three sets; (A) The non-degenerate part that follows RMT. (B) The non-degenerate part, at both ends and at intermediate eigenvalues, which deviate from RMT and expected to contain information about {\it important nodes} in the network. (C) The degenerate part with $zero$ eigenvalue, which fluctuates around RMT predicted value. We identify nodes corresponding to the dominant modes of the corresponding eigenvectors and analyze their structural properties

Random matrix analysis of complex networks

We study complex networks under random matrix theory (RMT) framework. Using nearest-neighbor and next-nearest-neighbor spacing distributions we analyze the eigenvalues of adjacency matrix of various model networks, namely, random, scale-free and small-world networks. These distributions follow Gaussian orthogonal ensemble statistic of RMT. To probe long-range correlations in the eigenvalues we study spectral rigidity via $\Delta_3$ statistic of RMT as well. It follows RMT prediction of linear behavior in semi-logarithmic scale with slope being $\sim 1/\pi^2$. Random and scale-free networks follow RMT prediction for very large scale. Small-world network follows it for sufficiently large scale, but much less than the random and scale-free networks.Comment: accepted in Phys. Rev. E (replaced with the final version

Spectral analysis of deformed random networks

We study spectral behavior of sparsely connected random networks under the random matrix framework. Sub-networks without any connection among them form a network having perfect community structure. As connections among the sub-networks are introduced, the spacing distribution shows a transition from the Poisson statistics to the Gaussian orthogonal ensemble statistics of random matrix theory. The eigenvalue density distribution shows a transition to the Wigner's semicircular behavior for a completely deformed network. The range for which spectral rigidity, measured by the Dyson-Mehta $\Delta_3$ statistics, follows the Gaussian orthogonal ensemble statistics depends upon the deformation of the network from the perfect community structure. The spacing distribution is particularly useful to track very slight deformations of the network from a perfect community structure, whereas the density distribution and the $\Delta_3$ statistics remain identical to the undeformed network. On the other hand the $\Delta_3$ statistics is useful for the larger deformation strengths. Finally, we analyze the spectrum of a protein-protein interaction network for Helicobacter, and compare the spectral behavior with those of the model networks.Comment: accepted for publication in Phys. Rev. E (replaced with the final version