2,166 research outputs found
The workings of the Maximum Entropy Principle in collective human behavior
We exhibit compelling evidence regarding how well does the MaxEnt principle
describe the rank-distribution of city-populations via an exhaustive study of
the 50 Spanish provinces (more than 8000 cities) in a time-window of 15 years
(1996-2010). We show that the dynamics that governs the population-growth is
the deciding factor that originates the observed distributions. The connection
between dynamics and distributions is unravelled via MaxEnt.Comment: Additional material available at http://sthar.com/uploads/add.pd
Trust transitivity in social networks
Non-centralized recommendation-based decision making is a central feature of
several social and technological processes, such as market dynamics,
peer-to-peer file-sharing and the web of trust of digital certification. We
investigate the properties of trust propagation on networks, based on a simple
metric of trust transitivity. We investigate analytically the percolation
properties of trust transitivity in random networks with arbitrary degree
distribution, and compare with numerical realizations. We find that the
existence of a non-zero fraction of absolute trust (i.e. entirely confident
trust) is a requirement for the viability of global trust propagation in large
systems: The average pair-wise trust is marked by a discontinuous transition at
a specific fraction of absolute trust, below which it vanishes. Furthermore, we
perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in
view of the concepts introduced. We compare different scenarios of trust
distribution: community- and authority-centered. We find that these scenarios
lead to sharply different patterns of trust propagation, due to the segregation
of authority hubs and densely-connected communities. While the
authority-centered scenario is more efficient, and leads to higher average
trust values, it favours weakly-connected "fringe" nodes, which are directly
trusted by authorities. The community-centered scheme, on the other hand,
favours nodes with intermediate degrees, in detriment of the authorities and
its "fringe" peers.Comment: 11 pages, 9 figures (with minor corrections
Candidate gene resequencing to identify rare, pedigree-specific variants influencing healthy aging phenotypes in the long life family study
Background: The Long Life Family Study (LLFS) is an international study to identify the genetic components of various healthy aging phenotypes. We hypothesized that pedigree-specific rare variants at longevity-associated genes could have a similar functional impact on healthy phenotypes. Methods: We performed custom hybridization capture sequencing to identify the functional variants in 464 candidate genes for longevity or the major diseases of aging in 615 pedigrees (4,953 individuals) from the LLFS, using a multiplexed, custom hybridization capture. Variants were analyzed individually or as a group across an entire gene for association to aging phenotypes using family based tests. Results: We found significant associations to three genes and nine single variants. Most notably, we found a novel variant significantly associated with exceptional survival in the 3' UTR OBFC1 in 13 individuals from six pedigrees. OBFC1 (chromosome 10) is involved in telomere maintenance, and falls within a linkage peak recently reported from an analysis of telomere length in LLFS families. Two different algorithms for single gene associations identified three genes with an enrichment of variation that was significantly associated with three phenotypes (GSK3B with the Healthy Aging Index, NOTCH1 with diastolic blood pressure and TP53 with serum HDL). Conclusions: Sequencing analysis of family-based associations for age-related phenotypes can identify rare or novel variants
Random Walks on Stochastic Temporal Networks
In the study of dynamical processes on networks, there has been intense focus
on network structure -- i.e., the arrangement of edges and their associated
weights -- but the effects of the temporal patterns of edges remains poorly
understood. In this chapter, we develop a mathematical framework for random
walks on temporal networks using an approach that provides a compromise between
abstract but unrealistic models and data-driven but non-mathematical
approaches. To do this, we introduce a stochastic model for temporal networks
in which we summarize the temporal and structural organization of a system
using a matrix of waiting-time distributions. We show that random walks on
stochastic temporal networks can be described exactly by an
integro-differential master equation and derive an analytical expression for
its asymptotic steady state. We also discuss how our work might be useful to
help build centrality measures for temporal networks.Comment: Chapter in Temporal Networks (Petter Holme and Jari Saramaki
editors). Springer. Berlin, Heidelberg 2013. The book chapter contains minor
corrections and modifications. This chapter is based on arXiv:1112.3324,
which contains additional calculations and numerical simulation
Estimation of proteinuria as a predictor of complications of pre-eclampsia: a systematic review
Background
Proteinuria is one of the essential criteria for the clinical diagnosis of pre-eclampsia. Increasing levels of proteinuria is considered to be associated with adverse maternal and fetal outcomes. We aim to determine the accuracy with which the amount of proteinuria predicts maternal and fetal complications in women with pre-eclampsia by systematic quantitative review of test accuracy studies.
Methods
We conducted electronic searches in MEDLINE (1951 to 2007), EMBASE (1980 to 2007), the Cochrane Library (2007) and the MEDION database to identify relevant articles and hand-search of selected specialist journals and reference lists of articles. There were no language restrictions for any of these searches. Two reviewers independently selected those articles in which the accuracy of proteinuria estimate was evaluated to predict maternal and fetal complications of pre-eclampsia. Data were extracted on study characteristics, quality and accuracy to construct 2 × 2 tables with maternal and fetal complications as reference standards.
Results
Sixteen primary articles with a total of 6749 women met the selection criteria with levels of proteinuria estimated by urine dipstick, 24-hour urine proteinuria or urine protein:creatinine ratio as a predictor of complications of pre-eclampsia. All 10 studies predicting maternal outcomes showed that proteinuria is a poor predictor of maternal complications in women with pre-eclampsia. Seventeen studies used laboratory analysis and eight studies bedside analysis to assess the accuracy of proteinuria in predicting fetal and neonatal complications. Summary likelihood ratios of positive and negative tests for the threshold level of 5 g/24 h were 2.0 (95% CI 1.5, 2.7) and 0.53 (95% CI 0.27, 1) for stillbirths, 1.5 (95% CI 0.94, 2.4) and 0.73 (95% CI 0.39, 1.4) for neonatal deaths and 1.5 (95% 1, 2) and 0.78 (95% 0.64, 0.95) for Neonatal Intensive Care Unit admission.
Conclusion
Measure of proteinuria is a poor predictor of either maternal or fetal complications in women with pre-eclampsia
A standard, single dose of inhaled terbutaline attenuates hyperpnoea-induced bronchoconstriction and mast cell activation in athletes
Release of broncho-active mediators from mast cells during exercise hyperpnoea is a key factor in the pathophysiology of exercise-induced bronchoconstriction (EIB). Our aim was to investigate the effect of a standard, single dose of an inhaled β2-adrenoceptor agonist on mast cell activation in response to dry air hyperpnoea in athletes with EIB. Twenty-seven athletes with EIB completed a randomised, double blind, placebo-controlled, crossover study. Terbutaline (0.5 mg) or placebo was inhaled15 min prior to 8 min of eucapnic voluntary hyperpnoea (EVH) with dry air. Pre- and post-bronchial challenge, urine samples were analysed by enzyme immunoassay for 11β-prostaglandin(PG)F2α. The maximum fall in forced expiratory volume in 1 sec(FEV1) of 14 (12-20)% (median and interquartile range) following placebo was attenuated to 7 (5-9)% with the administration of terbutaline (P<0.001). EVH caused a significant increase in 11β-PGF2α from (27-57) ng·mmol creatinine-1 at baseline to (43-72) ng·mmol creatinine-1 at its peak post-EVH following placebo (P=0.002). The rise in 11β-PGF2α was inhibited with administration of terbutaline: 39 (28-44) ng·mmol creatinine-1 at baseline vs. 40 (33-58) ng·mmol creatinine-1 at its peak post-EVH (P=0.118). These data provide novel in vivo evidence of mast cell stabilisation following inhalation of a standard dose of terbutaline prior to bronchial provocation with EVH in athletes with EIB
A large-scale study of a poultry trading network in Bangladesh: implications for control and surveillance of avian influenza viruses
Since its first report in 2007, avian influenza (AI) has been endemic in Bangladesh. While live poultry marketing is widespread throughout the country and known to influence AI dissemination and persistence, trading patterns have not been described. The aim of this study is to assess poultry trading practices and features of the poultry trading networks which could promote AI spread, and their potential implications for disease control and surveillance. Data on poultry trading practices was collected from 849 poultry traders during a cross-sectional survey in 138 live bird markets (LBMs) across 17 different districts of Bangladesh. The quantity and origins of traded poultry were assessed for each poultry type in surveyed LBMs. The network of contacts between farms and LBMs resulting from commercial movements of live poultry was constructed to assess its connectivity and to identify the key premises influencing it
Intraaortic Balloon Pump Counterpulsation and Cerebral Autoregulation: an observational study
The use of Intra-aortic counterpulsation is a well established supportive therapy for patients in cardiac failure or after cardiac surgery. Blood pressure variations induced by counterpulsation are transmitted to the cerebral arteries, challenging cerebral autoregulatory mechanisms in order to maintain a stable cerebral blood flow. This study aims to assess the effects on cerebral autoregulation and variability of cerebral blood flow due to intra-aortic balloon pump and inflation ratio weaning
Correct-by-construction implementation of runtime monitors using stepwise refinement
Runtime verification (RV) is a lightweight technique for verifying traces of computer systems. One challenge in applying RV is to guarantee that the implementation of a runtime monitor correctly detects and signals unexpected events. In this paper, we present a method for deriving correct-by-construction implementations of runtime monitors from high-level specifications using Fiat, a Coq library for stepwise refinement. SMEDL (Scenario-based Meta-Event Definition Language), a domain specific language for event-driven RV, is chosen as the specification language. We propose an operational semantics for SMEDL suitable to be used in Fiat to describe the behavior of a monitor in a relational way. Then, by utilizing Fiat\u27s refinement calculus, we transform a declarative monitor specification into an executable runtime monitor with a proof that the behavior of the implementation is strictly a subset of that provided by the specification. Moreover, we define a predicate on the syntax structure of a monitor definition to ensure termination and determinism. Most of the proof work required to generate monitor code has been automated
Fast Computing Betweenness Centrality with Virtual Nodes on Large Sparse Networks
Betweenness centrality is an essential index for analysis of complex networks. However, the calculation of betweenness centrality is quite time-consuming and the fastest known algorithm uses time and space for weighted networks, where and are the number of nodes and edges in the network, respectively. By inserting virtual nodes into the weighted edges and transforming the shortest path problem into a breadth-first search (BFS) problem, we propose an algorithm that can compute the betweenness centrality in time for integer-weighted networks, where is the average weight of edges and is the average degree in the network. Considerable time can be saved with the proposed algorithm when , indicating that it is suitable for lightly weighted large sparse networks. A similar concept of virtual node transformation can be used to calculate other shortest path based indices such as closeness centrality, graph centrality, stress centrality, and so on. Numerical simulations on various randomly generated networks reveal that it is feasible to use the proposed algorithm in large network analysis
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