Investigating the topology of interacting networks - Theory and application to coupled climate subnetworks

Network theory provides various tools for investigating the structural or functional topology of many complex systems found in nature, technology and society. Nevertheless, it has recently been realised that a considerable number of systems of interest should be treated, more appropriately, as interacting networks or networks of networks. Here we introduce a novel graph-theoretical framework for studying the interaction structure between subnetworks embedded within a complex network of networks. This framework allows us to quantify the structural role of single vertices or whole subnetworks with respect to the interaction of a pair of subnetworks on local, mesoscopic and global topological scales. Climate networks have recently been shown to be a powerful tool for the analysis of climatological data. Applying the general framework for studying interacting networks, we introduce coupled climate subnetworks to represent and investigate the topology of statistical relationships between the fields of distinct climatological variables. Using coupled climate subnetworks to investigate the terrestrial atmosphere's three-dimensional geopotential height field uncovers known as well as interesting novel features of the atmosphere's vertical stratification and general circulation. Specifically, the new measure "cross-betweenness" identifies regions which are particularly important for mediating vertical wind field interactions. The promising results obtained by following the coupled climate subnetwork approach present a first step towards an improved understanding of the Earth system and its complex interacting components from a network perspective

Transport properties of strongly correlated metals:a dynamical mean-field approach

The temperature dependence of the transport properties of the metallic phase of a frustrated Hubbard model on the hypercubic lattice at half-filling are calculated. Dynamical mean-field theory, which maps the Hubbard model onto a single impurity Anderson model that is solved self-consistently, and becomes exact in the limit of large dimensionality, is used. As the temperature increases there is a smooth crossover from coherent Fermi liquid excitations at low temperatures to incoherent excitations at high temperatures. This crossover leads to a non-monotonic temperature dependence for the resistance, thermopower, and Hall coefficient, unlike in conventional metals. The resistance smoothly increases from a quadratic temperature dependence at low temperatures to large values which can exceed the Mott-Ioffe-Regel value, hbar a/e^2 (where "a" is a lattice constant) associated with mean-free paths less than a lattice constant. Further signatures of the thermal destruction of quasiparticle excitations are a peak in the thermopower and the absence of a Drude peak in the optical conductivity. The results presented here are relevant to a wide range of strongly correlated metals, including transition metal oxides, strontium ruthenates, and organic metals.Comment: 19 pages, 9 eps figure

The Tsallis statistical distribution applied to geomagnetically induced currents

Geomagnetically induced currents (GICs) have been long recognized as a ground effect arising from a chain of space weather events. GICs have been measured and modeled in many countries, resulting in a considerable amount of data. Previous statistical analyses have proposed various types of distribution functions to fit long-term GICs data sets. However, these extensive statistical approaches have been only partially successful in fitting the data sets. Here we use modeled GICs data sets calculated in four countries (Brazil, South Africa, United Kingdom, and Finland) using data from solar cycle 23 to show a plausible function based on a nonextensive statistical model of the q-exponential Tsallis function. The fitted q-exponential parameter is approximately the same for all locations, and the Lilliefors test shows good agreement with the q-exponential fits. From this fit, we compute that the likely numbers of extreme GICs events over the next ten solar cycles are 1–2 for both Finland and United Kingdom, at least one for Brazil and less than one event for South Africa. Our results indicate that the nonextensive statistics are a general characteristic of GICs, suggesting that the ground current intensity has a strong temporal correlation and long-range interaction

Managing quality of cost information in clinical costing:evidence across seven countries

Purpose: The purpose is to assess the impact of clinical costing approaches on the quality of cost information in seven countries (Denmark, England, France, Germany, Ireland, the Netherlands and Portugal). Design/methodology/approach: Costing practices in seven countries were analysed via questionnaires, interviews and relevant published material. Findings: Although clinical costing is intended to support a similar range of purposes, countries display considerable diversity in their approaches to costing in terms of the level of detail contained in regulatory guidance and the percentage of providers subject to such guidance for tariff setting. Guidance in all countries involves a mix of costing methods. Research limitations/implications: The authors propose a two-dimensional Materiality and Quality Score (2D MAQS) of costing systems that can support the complex trade-offs in managing the quality of cost information at both policy and provider level, and between financial and clinical concerns. Originality/value: The authors explore the trade-offs between different dimensions of the quality (accuracy, decision relevance and standardization) and the cost of collecting and analysing cost information for disparate purposes

Pharmacology and Surface Electrostatics of the K Channel Outer Pore Vestibule

In spite of a generally well-conserved outer vestibule and pore structure, there is considerable diversity in the pharmacology of K channels. We have investigated the role of specific outer vestibule charged residues in the pharmacology of K channels using tetraethylammonium (TEA) and a trivalent TEA analog, gallamine. Similar to Shaker K channels, gallamine block of Kv3.1 channels was more sensitive to solution ionic strength than was TEA block, a result consistent with a contribution from an electrostatic potential near the blocking site. In contrast, TEA block of another type of K channel (Kv2.1) was insensitive to solution ionic strength and these channels were resistant to block by gallamine. Neutralizing either of two lysine residues in the outer vestibule of these Kv2.1 channels conferred ionic strength sensitivity to TEA block. Kv2.1 channels with both lysines neutralized were sensitive to block by gallamine, and the ionic strength dependence of this block was greater than that for TEA. These results demonstrate that Kv3.1 (like Shaker) channels contain negatively charged residues in the outer vestibule of the pore that influence quaternary ammonium pharmacology. The presence of specific lysine residues in wild-type Kv2.1 channels produces an outer vestibule with little or no net charge, with important consequences for quaternary ammonium block. Neutralizing these key lysines results in a negatively charged vestibule with pharmacological properties approaching those of other types of K channels

Quantum magnetism in two dimensions: From semi-classical N\'eel order to magnetic disorder

This is a review of ground-state features of the s=1/2 Heisenberg antiferromagnet on two-dimensional lattices. A central issue is the interplay of lattice topology (e.g. coordination number, non-equivalent nearest-neighbor bonds, geometric frustration) and quantum fluctuations and their impact on possible long-range order. This article presents a unified summary of all 11 two-dimensional uniform Archimedean lattices which include e.g. the square, triangular and kagome lattice. We find that the ground state of the spin-1/2 Heisenberg antiferromagnet is likely to be semi-classically ordered in most cases. However, the interplay of geometric frustration and quantum fluctuations gives rise to a quantum paramagnetic ground state without semi-classical long-range order on two lattices which are precisely those among the 11 uniform Archimedean lattices with a highly degenerate ground state in the classical limit. The first one is the famous kagome lattice where many low-lying singlet excitations are known to arise in the spin gap. The second lattice is called star lattice and has a clear gap to all excitations. Modification of certain bonds leads to quantum phase transitions which are also discussed briefly. Furthermore, we discuss the magnetization process of the Heisenberg antiferromagnet on the 11 Archimedean lattices, focusing on anomalies like plateaus and a magnetization jump just below the saturation field. As an illustration we discuss the two-dimensional Shastry-Sutherland model which is used to describe SrCu2(BO3)2.Comment: This is now the complete 72-page preprint version of the 2004 review article. This version corrects two further typographic errors (three total with respect to the published version), see page 2 for detail

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Proteasome Nuclear Import Mediated by Arc3 Can Influence Efficient DNA Damage Repair and Mitosis in Schizosaccharomyces Pombe

Proteasomes must efficiently remove their substrates throughout the cells in a timely manner as many of these proteins can be toxic. This study shows that proteasomes can do so efficiently because they are highly mobile. Furthermore this study uncovers that proteasome mobility requires functional Arc3, a subunit of the Arp2/3 complex

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)