The Impact of Heterogeneous Thresholds on Social Contagion with Multiple Initiators

The threshold model is a simple but classic model of contagion spreading in complex social systems. To capture the complex nature of social influencing we investigate numerically and analytically the transition in the behavior of threshold-limited cascades in the presence of multiple initiators as the distribution of thresholds is varied between the two extreme cases of identical thresholds and a uniform distribution. We accomplish this by employing a truncated normal distribution of the nodes thresholds and observe a non-monotonic change in the cascade size as we vary the standard deviation. Further, for a sufficiently large spread in the threshold distribution, the tipping-point behavior of the social influencing process disappears and is replaced by a smooth crossover governed by the size of initiator set. We demonstrate that for a given size of the initiator set, there is a specific variance of the threshold distribution for which an opinion spreads optimally. Furthermore, in the case of synthetic graphs we show that the spread asymptotically becomes independent of the system size, and that global cascades can arise just by the addition of a single node to the initiator set.

An Analysis of the Matching Hypothesis in Networks

The matching hypothesis in social psychology claims that people are more likely to form a committed relationship with someone equally attractive. Previous works on stochastic models of human mate choice process indicate that patterns supporting the matching hypothesis could occur even when similarity is not the primary consideration in seeking partners. Yet, most if not all of these works concentrate on fully-connected systems. Here we extend the analysis to networks. Our results indicate that the correlation of the couples attractiveness grows monotonically with the increased average degree and decreased degree diversity of the network. This correlation is lower in sparse networks than in fully-connected systems, because in the former less attractive individuals who find partners are likely to be coupled with ones who are more attractive than them. The chance of failing to be matched decreases exponentially with both the attractiveness and the degree. The matching hypothesis may not hold when the degree-attractiveness correlation is present, which can give rise to negative attractiveness correlation. Finally, we find that the ratio between the number of matched couples and the size of the maximum matching varies non-monotonically with the average degree of the network. Our results reveal the role of network topology in the process of human mate choice and bring insights into future investigations of different matching processes in networks.

OGLE-IV: Fourth Phase of the Optical Gravitational Lensing Experiment

We present both the technical overview and main science drivers of the fourth phase of the Optical Gravitational Lensing Experiment (hereafter OGLE-IV). OGLE-IV is currently one of the largest sky variability surveys worldwide, targeting the densest stellar regions of the sky. The survey covers over 3000 square degrees in the sky and monitors regularly over a billion sources. The main targets include the inner Galactic Bulge and the Magellanic System. Their photometry spans the range of $12<I<21$ mag and $13<I<21.7$ mag, respectively. Supplementary shallower Galaxy Variability Survey covers the extended Galactic bulge and 2/3 of the whole Galactic disk within the magnitude range of $10<I<19$ mag. All OGLE-IV surveys provide photometry with milli-magnitude accuracy at the bright end. The cadence of observations varies from 19-60 minutes in the inner Galactic bulge to 1-3 days in the remaining Galactic bulge fields, Magellanic System and the Galactic disk. OGLE-IV provides the astronomical community with a number of real time services. The Early Warning System (EWS) contains information on two thousand gravitational microlensing events being discovered in real time annually, the OGLE Transient Detection System (OTDS) delivers over 200 supernovae a year. We also provide the real time photometry of unpredictable variables such as optical counterparts to the X-ray sources and R CrB stars. Hundreds of thousands new variable stars have already been discovered and classified by the OGLE survey. The number of new detections will be at least doubled during the current OGLE-IV phase. The survey was designed and optimized primarily to conduct the second generation microlensing survey for exoplanets. It has already contributed significantly to the increase of the discovery rate of microlensing exoplanets and free-floating planets.

Identifying robust communities and multi-community nodes by combining top-down and bottom-up approaches to clustering

Biological functions are carried out by groups of interacting molecules, cells or tissues, known as communities. Membership in these communities may overlap when biological components are involved in multiple functions. However, traditional clustering methods detect non-overlapping communities. These detected communities may also be unstable and difficult to replicate, because traditional methods are sensitive to noise and parameter settings. These aspects of traditional clustering methods limit our ability to detect biological communities, and therefore our ability to understand biological functions. To address these limitations and detect robust overlapping biological communities, we propose an unorthodox clustering method called SpeakEasy which identifies communities using top-down and bottom-up approaches simultaneously. Specifically, nodes join communities based on their local connections, as well as global information about the network structure. This method can quantify the stability of each community, automatically identify the number of communities, and quickly cluster networks with hundreds of thousands of nodes. SpeakEasy shows top performance on synthetic clustering benchmarks and accurately identifies meaningful biological communities in a range of datasets, including: gene microarrays, protein interactions, sorted cell populations, electrophysiology and fMRI brain imaging.

Over 38000 RR Lyrae Stars in the OGLE Galactic Bulge Fields

We present the most comprehensive picture ever obtained of the central parts of the Milky Way probed with RR Lyrae variable stars. This is a collection of 38257 RR Lyr stars detected over 182 square degrees monitored photometrically by the Optical Gravitational Lensing Experiment (OGLE) in the most central regions of the Galactic bulge. The sample consists of 16804 variables found and published by the OGLE collaboration in 2011 and 21453 RR Lyr stars newly detected in the photometric databases of the fourth phase of the OGLE survey (OGLE-IV). 93% of the OGLE-IV variables were previously unknown. The total sample consists of 27258 RRab, 10825 RRc, and 174 RRd stars. We provide OGLE-IV I- and V-band light curves of the variables along with their basic parameters. About 300 RR Lyr stars in our collection are plausible members of 15 globular clusters. Among others, we found the first pulsating variables that may belong to the globular cluster Terzan 1 and the first RRd star in the globular cluster M54. Our survey also covers the center and outskirts of the Sagittarius Dwarf Spheroidal Galaxy enabling studies of the spatial distribution of the old stellar population from this galaxy. A group of double-mode RR Lyr stars with period ratios around 0.740 form a stream in the sky that may be a relic of a cluster or a dwarf galaxy tidally disrupted by the Milky Way. Three of our RR Lyr stars experienced a pulsation mode switching from double-mode to single fundamental mode or vice versa. We also present the first known RRd stars with large-amplitude Blazhko effect.

Simulations of gamma quanta scattering in a single module of the J-PET detector

This article describes simulations of scattering of annihilation gamma quanta in a strip of plastic scintillator. Such strips constitute basic detection modules in a newly proposed Positron Emission Tomography which utilizes plastic scintillators instead of inorganic crystals. An algorithm simulating chain of Compton scatterings was elaborated and series of simulations have been conducted for the scintillator strip with the cross section of 5 mm x 19 mm. Obtained results indicate that secondary interactions occur only in the case of about 8% of events and out of them only 25$%$ take place in the distance larger than 0.5 cm from the primary interaction. It was also established that light signals produced at primary and secondary interactions overlap with the delay which distribution is characterized by FWHM of about 40 ps.

Failure dynamics of the global risk network

Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of risks likelihoods and influence underlie a quantitative model of the global risk network dynamics. The modeled risks range from environmental to economic and technological and include difficult to quantify risks, such as geo-political or social. Using the maximum likelihood estimation, we find the optimal model parameters and demonstrate that the model including network effects significantly outperforms the others, uncovering full value of the expert collected data. We analyze the model dynamics and study its resilience and stability. Our findings include such risk properties as contagion potential, persistence, roles in cascades of failures and the identity of risks most detrimental to system stability. The model provides quantitative means for measuring the adverse effects of risk interdependence and the materialization of risks in the network.

Cascading failures in spatially-embedded random networks

Cascading failures constitute an important vulnerability of interconnected systems. Here we focus on the study of such failures on networks in which the connectivity of nodes is constrained by geographical distance. Specifically, we use random geometric graphs as representative examples of such spatial networks, and study the properties of cascading failures on them in the presence of distributed flow. The key finding of this study is that the process of cascading failures is non-self-averaging on spatial networks, and thus, aggregate inferences made from analyzing an ensemble of such networks lead to incorrect conclusions when applied to a single network, no matter how large the network is. We demonstrate that this lack of self-averaging disappears with the introduction of a small fraction of long-range links into the network. We simulate the well studied preemptive node removal strategy for cascade mitigation and show that it is largely ineffective in the case of spatial networks. We introduce an altruistic strategy designed to limit the loss of network nodes in the event of a cascade triggering failure and show that it performs better than the preemptive strategy. Finally, we consider a real-world spatial network viz. a European power transmission network and validate that our findings from the study of random geometric graphs are also borne out by simulations of cascading failures on the empirical network.

The Variable Stars from the OGLE-III Shallow Survey in the Large Magellanic Cloud

We describe variable stars found in the data collected during the OGLE-III Shallow Survey covering the I-band magnitude range from 9.7 mag to 14.5 mag. The main result is the extension of period--luminosity relations for Cepheids up to 134 days. We also detected 82 binary systems and 110 long-period variables not present in the main OGLE catalogs. Additionally 558 objects were selected as candidates for miscellaneous variables.

Distributed flow optimization and cascading effects in weighted complex networks

We investigate the effect of a specific edge weighting scheme $sim (k_i k_j)^{beta}$ on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter $beta$ and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we show the dependence of transport efficiency upon the correlations between the topology and weights. By studying the severity of cascades for different control parameter $beta$, we find that network resilience to cascading overloads and network throughput is optimal for the same value of $beta$ over the range of node capacities and available bandwidth.