Module identification in bipartite and directed networks

Modularity is one of the most prominent properties of real-world complex networks. Here, we address the issue of module identification in two important classes of networks: bipartite networks and directed unipartite networks. Nodes in bipartite networks are divided into two non-overlapping sets, and the links must have one end node from each set. Directed unipartite networks only have one type of nodes, but links have an origin and an end. We show that directed unipartite networks can be conviniently represented as bipartite networks for module identification purposes. We report a novel approach especially suited for module detection in bipartite networks, and define a set of random networks that enable us to validate the new approach

Correlation, Network and Multifractal Analysis of Global Financial Indices

We apply RMT, Network and MF-DFA methods to investigate correlation, network and multifractal properties of 20 global financial indices. We compare results before and during the financial crisis of 2008 respectively. We find that the network method gives more useful information about the formation of clusters as compared to results obtained from eigenvectors corresponding to second largest eigenvalue and these sectors are formed on the basis of geographical location of indices. At threshold 0.6, indices corresponding to Americas, Europe and Asia/Pacific disconnect and form different clusters before the crisis but during the crisis, indices corresponding to Americas and Europe are combined together to form a cluster while the Asia/Pacific indices forms another cluster. By further increasing the value of threshold to 0.9, European countries France, Germany and UK constitute the most tightly linked markets. We study multifractal properties of global financial indices and find that financial indices corresponding to Americas and Europe almost lie in the same range of degree of multifractality as compared to other indices. India, South Korea, Hong Kong are found to be near the degree of multifractality of indices corresponding to Americas and Europe. A large variation in the degree of multifractality in Egypt, Indonesia, Malaysia, Taiwan and Singapore may be a reason that when we increase the threshold in financial network these countries first start getting disconnected at low threshold from the correlation network of financial indices. We fit Binomial Multifractal Model (BMFM) to these financial markets.Comment: 32 pages, 25 figures, 1 tabl

Quantum Singularities in Horava-Lifshitz Cosmology

The recently proposed Horava-Lifshitz (HL) theory of gravity is analyzed from the quantum cosmology point of view. By employing usual quantum cosmology techniques, we study the quantum Friedmann-Lemaitre-Robertson-Walker (FLRW) universe filled with radiation in the context of HL gravity. We find that this universe is quantum mechanically nonsingular in two different ways: the expectation value of the scale factor $(t)$ never vanishes and, if we abandon the detailed balance condition suggested by Horava, the quantum dynamics of the universe is uniquely determined by the initial wave packet and no boundary condition at $a=0$ is indeed necessary.Comment: 13 pages, revtex, 1 figure. Final version to appear in PR

Autonomous clustering using rough set theory

This paper proposes a clustering technique that minimises the need for subjective human intervention and is based on elements of rough set theory. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease and results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency

An intelligent assistant for exploratory data analysis

In this paper we present an account of the main features of SNOUT, an intelligent assistant for exploratory data analysis (EDA) of social science survey data that incorporates a range of data mining techniques. EDA has much in common with existing data mining techniques: its main objective is to help an investigator reach an understanding of the important relationships ina data set rather than simply develop predictive models for selectd variables. Brief descriptions of a number of novel techniques developed for use in SNOUT are presented. These include heuristic variable level inference and classification, automatic category formation, the use of similarity trees to identify groups of related variables, interactive decision tree construction and model selection using a genetic algorithm

Therapist telephone-delivered CBT and web-based CBT compared with treatment as usual in refractory irritable bowel syndrome: the ACTIB three-arm RCT

Background: Irritable bowel syndrome (IBS) affects 10–22% of people in the UK. Abdominal pain, bloating and altered bowel habits affect quality of life and can lead to time off work. Current treatment relies on a positive diagnosis, reassurance, lifestyle advice and drug therapies, but many people suffer ongoing symptoms. Cognitive–behavioural therapy (CBT) is recommended in guidelines for patients with ongoing symptoms but its availability is limited. Objectives: To determine the clinical effectiveness and cost-effectiveness of therapist telephone-delivered CBT (TCBT) and web-based CBT (WCBT) with minimal therapist support compared with treatment as usual (TAU) in refractory IBS. Design: This was a three-arm randomised controlled trial. Setting: This trial took place in UK primary and secondary care. Participants: Adults with refractory IBS (clinically significant symptoms for 12 months despite first-line therapies) were recruited from 74 general practices and three gastroenterology centres from May 2014 to March 2016. Interventions: TCBT – patient CBT self-management manual, six 60-minute telephone sessions over 9 weeks and two 60-minute booster sessions at 4 and 8 months (8 hours’ therapist time). WCBT – interactive, tailored web-based CBT, three 30-minute telephone sessions over 9 weeks and two 30-minute boosters at 4 and 8 months (2.5 hours’ therapist time). Main outcome measures: Primary outcomes – IBS symptom severity score (IBS SSS) and Work and Social Adjustment Scale (WSAS) at 12 months. Cost-effectiveness [quality-adjusted life-years (QALYs) and health-care costs]. Results: In total, 558 out of 1452 patients (38.4%) screened for eligibility were recruited – 186 were randomised to TCBT, 185 were randomised to WCBT and 187 were randomised to TAU. The mean baseline Irritable Bowel Syndrome Symptom Severity Score (IBS SSS) was 265.0. An intention-to-treat analysis with multiple imputation was carried out at 12 months; IBS SSS were 61.6 points lower in the TCBT arm [95% confidence interval (CI) 89.5 to 33.8; p < 0.001] and 35.2 points lower in the WCBT arm (95% CI 57.8 to 12.6; p = 0.002) than in the TAU arm (IBS SSS of 205.6). The mean WSAS score at 12 months was 10.8 in the TAU arm, 3.5 points lower in the TCBT arm (95% CI 5.1 to 1.9; p < 0.001) and 3.0 points lower in the WCBT arm (95% CI 4.6 to 1.3; p = 0.001). For the secondary outcomes, the Subject’s Global Assessment showed an improvement in symptoms at 12 months (responders) in 84.8% of the TCBT arm compared with 41.7% of the TAU arm [odds ratio (OR) 6.1, 95% CI 2.5 to 15.0; p < 0.001] and 75.0% of the WCBT arm (OR 3.6, 95% CI 2.0 to 6.3; p < 0.001). Patient enablement was 78.3% (responders) for TCBT, 23.5% for TAU (OR 9.3, 95% CI 4.5 to 19.3; p < 0.001) and 54.8% for WCBT (OR 3.5, 95% CI 2.0 to 5.9; p < 0.001). Adverse events were similar between the trial arms. The incremental cost-effectiveness ratio (ICER) (QALY) for TCBT versus TAU was £22,284 and for WCBT versus TAU was £7724. Cost-effectiveness reduced after imputation for missing values. Qualitative findings highlighted that, in the CBT arms, there was increased capacity to cope with symptoms, negative emotions and challenges of daily life. Therapist input was important in supporting WCBT. Conclusions: In this large, rigorously conducted RCT, both CBT arms showed significant improvements in IBS outcomes compared with TAU. WCBT had lower costs per QALY than TCBT. Sustained improvements in IBS symptoms are possible at an acceptable cost. Suggested future research work is longer-term follow-up and research to translate these findings into usual clinical practice. Future work: Longer-term follow-up and research to translate these findings into usual clinical practice is needed

Noisy Monte Carlo: Convergence of Markov chains with approximate transition kernels

Monte Carlo algorithms often aim to draw from a distribution $\pi$ by simulating a Markov chain with transition kernel $P$ such that $\pi$ is invariant under $P$. However, there are many situations for which it is impractical or impossible to draw from the transition kernel $P$. For instance, this is the case with massive datasets, where is it prohibitively expensive to calculate the likelihood and is also the case for intractable likelihood models arising from, for example, Gibbs random fields, such as those found in spatial statistics and network analysis. A natural approach in these cases is to replace $P$ by an approximation $\hat{P}$. Using theory from the stability of Markov chains we explore a variety of situations where it is possible to quantify how 'close' the chain given by the transition kernel $\hat{P}$ is to the chain given by $P$. We apply these results to several examples from spatial statistics and network analysis.Comment: This version: results extended to non-uniformly ergodic Markov chain

Classification of Westminster Parliamentary constituencies using e-petition data

In a representative democracy it is important that politicians have knowledge of the desires, aspirations and concerns of their constituents. Opportunities to gauge these opinions are however limited and, in the era of novel data, thoughts turn to what alternative, secondary, data sources may be available to keep politicians informed about local concerns. One such source of data are signatories to electronic petitions (e-petitions). Such e-petitions have risen greatly in popularity over the past decade and allow members of the public to initiate and sign an e-petition online, with popular e-petitions resulting in media attention, a response from the government or ultimately a debate in parliament. These data are thus novel in their availability and have not yet been widely used for research purposes. In this article we will use the e-petition data to show how semantic classes of Westminster Parliamentary constituencies, fitted as Gaussian finite mixture models via EM algorithm, can be used to typify constituencies. We identify four classes: Domestic Liberals; International Liberals; Nostalgic Brits and Rural Concerns, and illustrate how they map onto electoral results. The findings and the utility of this approach to incorporate new e-petitions and adapt to changes in electoral geography are discussed

Millimeter wave radiation-induced magnetoresistance oscillations in the high quality GaAs/AlGaAs 2D electron system under bichromatic excitation

Millimeter wave radiation-induced magnetoresistance oscillations are examined in the GaAs/AlGaAs 2D electron system under bichromatic excitation in order to study the evolution of the oscillatory diagonal magnetoresistance, R-xx as the millimeter wave intensity is changed systematically for various frequency combinations. The results indicate that at low magnetic fields, the lower frequency millimeter wave excitation sets the observed R-xx response, as the higher frequency millimeter wave component determines the R-xx response at higher magnetic fields. The observations are qualitatively explained in terms of the order of the involved transitions. The results are also modeled using the radiation-driven electron orbit theory

The structure and function of complex networks

Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.Comment: Review article, 58 pages, 16 figures, 3 tables, 429 references, published in SIAM Review (2003