Activity clocks: spreading dynamics on temporal networks of human contact

Dynamical processes on time-varying complex networks are key to understanding and modeling a broad variety of processes in socio-technical systems. Here we focus on empirical temporal networks of human proximity and we aim at understanding the factors that, in simulation, shape the arrival time distribution of simple spreading processes. Abandoning the notion of wall-clock time in favour of node-specific clocks based on activity exposes robust statistical patterns in the arrival times across different social contexts. Using randomization strategies and generative models constrained by data, we show that these patterns can be understood in terms of heterogeneous inter-event time distributions coupled with heterogeneous numbers of events per edge. We also show, both empirically and by using a synthetic dataset, that significant deviations from the above behavior can be caused by the presence of edge classes with strong activity correlations

Machine-z: Rapid Machine Learned Redshift Indicator for Swift Gamma-ray Bursts

Studies of high-redshift gamma-ray bursts (GRBs) provide important information about the early Universe such as the rates of stellar collapsars and mergers, the metallicity content, constraints on the re-ionization period, and probes of the Hubble expansion. Rapid selection of high-z candidates from GRB samples reported in real time by dedicated space missions such as Swift is the key to identifying the most distant bursts before the optical afterglow becomes too dim to warrant a good spectrum. Here we introduce "machine-z", a redshift prediction algorithm and a "high-z" classifier for Swift GRBs based on machine learning. Our method relies exclusively on canonical data commonly available within the first few hours after the GRB trigger. Using a sample of 284 bursts with measured redshifts, we trained a randomized ensemble of decision trees (random forest) to perform both regression and classification. Cross-validated performance studies show that the correlation coefficient between machine-z predictions and the true redshift is nearly 0.6. At the same time our high-z classifier can achieve 80% recall of true high-redshift bursts, while incurring a false positive rate of 20%. With 40% false positive rate the classifier can achieve ~100% recall. The most reliable selection of high-redshift GRBs is obtained by combining predictions from both the high-z classifier and the machine-z regressor.Comment: Accepted to the Monthly Notices of the Royal Astronomical Society Journal (10 pages, 10 figures, and 3 Tables

Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks

The idea of 'date' and 'party' hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. Thus, we suggest that a date/party dichotomy is not meaningful and it might be more useful to conceive of roles for protein-protein interactions rather than individual proteins. We find significant correlations between interaction centrality and the functional similarity of the interacting proteins.Comment: 27 pages, 5 main figures, 4 supplementary figure

Representing New Voice Services and Their Features

New voice services are investigated in the fields of Internet telephony (SIP – Session Initiation Protocol) and interactive voice systems (VoiceXML – Voice Extended Markup Language). It is explained how CRESS (Chisel Representation Employing Systematic Specification) can graphically represent services and features in these domains. CRESS is a front-end for detecting feature interactions and for implementing features. The nature of service architecture and feature composition are presented. CRESS descriptions are automatically compiled into LOTOS (Language Of Temporal Ordering Specification) and SDL (Specification and Description Language), allowing automated analysis of service behaviour and feature interaction. For implementation, CRESS diagrams can be compiled into Perl (for SIP) and VoiceXML. The approach combines the benefits of an accessible graphical notation, underlying formalisms, and practical realisation

Greater understanding of spacing needs for children’s eye movements during on-screen reading is required

This paper endeavors to consolidate current knowledge and empirical research concerning the use of typography for children’s on-screen reading. This paper is not intended as a full literature review, but attempts to raise awareness of the areas required for future investigation. This evaluation indicates a significant gap in the literature of children’s on-screen reading and proposes a need for further investigations in typographical spacing. These future studies need to objectively consider children’s eye movements and the effect of screen based text presentation on children’s comprehension

Modelling SIP Services using CRESS

CRESS (CHISEL Representation Employing Systematic Specification) is a notation and set of tools for graphical specification and analysis of services. It is applicable wherever a system consists of base functionality to which may be added selected services. The CRESS notation is introduced for root diagrams, service diagrams, and rules governing their behaviour. It is shown how CRESS can represent services in SIP (Session Initiation Protocol). For analysis, service diagrams can be automatically translated into LOTOS (Language Of Temporal Ordering Specification) or SDL (Specification and Description Language). For scripting, translation is into CPL (Call Processing Language) or CGI (Common Gateway Interface). The structure of the portable CRESS toolset is explained

Oscillations in the dark energy EoS: new MCMC lessons

We study the possibility of detecting oscillating patterns in the equation of state (EoS) of the dark energy using different cosmological datasets. We follow a phenomenological approach and study three different oscillating models for the EoS, one of them periodic and the other two damped (proposed here for the first time). All the models are characterised by the amplitude value, the centre and the frequency of oscillations. In contrast to previous works in the literature, we do not fix the value of the frequency to a fiducial value related to the time extension of chosen datasets, but consider a discrete set of values, so to avoid arbitrariness and try and detect any possible time period in the EoS. We test the models using a recent collection of SNeIa, direct Hubble data and Gamma Ray Bursts data. Main results are: I. even if constraints on the amplitude are not too strong, we detect a trend of it versus the frequency, i.e. decreasing (and even negatives) amplitudes for higher frequencies; II. the centre of oscillation (which corresponds to the present value of the EoS parameter) is very well constrained, phantom behaviour is excluded at $1\sigma$ level and trend which is in agreement with the one for the amplitude appears; III. the frequency is hard to constrain, showing similar statistical validity for all the values of the discrete set chosen, but the best fit of all the scenarios considered is associated with a period which is in the redshift range depicted by our cosmological data. The "best" oscillating models are compared with $\Lambda$CDM using dimensionally consistent a Bayesian approach based information criterion and the conclusion reached is the non existence of significant evidence against dark energy oscillations.Comment: 12 papers, mn2e, 8 figure

Reviewing the understanding of the effects of spacing on children’s eye movements for on-screen reading

This paper endeavors to consolidate current knowledge and empirical research concerning the use of typography for children’s on-screen reading. This paper is not intended as a full literature review but attempts to raise awareness of the areas required for future investigation. This evaluation indicates a significant gap in the literature of children’s on-screen reading and proposes a need for further investigations in typographical spacing. These future studies need to objectively consider children’s eye movements and the effect of screen based text presentation on children’s comprehension