Data Integration by combining big data and survey sample data for finite population inference

The statistical challenges in using big data for making valid statistical inference in the finite population have been well documented in literature. These challenges are due primarily to statistical bias arising from under-coverage in the big data source to represent the population of interest and measurement errors in the variables available in the data set. By stratifying the population into a big data stratum and a missing data stratum, we can estimate the missing data stratum by using a fully responding probability sample, and hence the population as a whole by using a data integration estimator. By expressing the data integration estimator as a regression estimator, we can handle measurement errors in the variables in big data and also in the probability sample. We also propose a fully nonparametric classification method for identifying the overlapping units and develop a bias-corrected data integration estimator under misclassification errors. Finally, we develop a two-step regression data integration estimator to deal with measurement errors in the probability sample. An advantage of the approach advocated in this paper is that we do not have to make unrealistic missing-at-random assumptions for the methods to work. The proposed method is applied to the real data example using 2015-16 Australian Agricultural Census data

Bounded Search Tree Algorithms for Parameterized Cograph Deletion: Efficient Branching Rules by Exploiting Structures of Special Graph Classes

Many fixed-parameter tractable algorithms using a bounded search tree have been repeatedly improved, often by describing a larger number of branching rules involving an increasingly complex case analysis. We introduce a novel and general search strategy that branches on the forbidden subgraphs of a graph class relaxation. By using the class of $P_4$-sparse graphs as the relaxed graph class, we obtain efficient bounded search tree algorithms for several parameterized deletion problems. We give the first non-trivial bounded search tree algorithms for the cograph edge-deletion problem and the trivially perfect edge-deletion problems. For the cograph vertex deletion problem, a refined analysis of the runtime of our simple bounded search algorithm gives a faster exponential factor than those algorithms designed with the help of complicated case distinctions and non-trivial running time analysis [21] and computer-aided branching rules [11].Comment: 23 pages. Accepted in Discrete Mathematics, Algorithms and Applications (DMAA

The prediction of preference for unfamiliar urban places

Preferences for unfamiliar urban environments were studied as a function of urban categories, viewing time, and four predictor variables: complexity, coherence, identifiability, and mystery. A nonmetric factor analysis of the preference ratings for the longest viewing-time condition yielded five dimensions: Contemporary Life, Alley/Factory, Urban Nature, Unusual Architecture, and Older Buildings. The five categories differed significantly in preference, with Urban Nature by far the most preferred and Alley/Factory distinctly disliked. The combination of low coherence and high complexity characterizes the least liked Alley/Factory category, while the role of mystery in the urban setting is highlighted by the most preferred Urban Nature category. The results point to various ways in which the urban environment could be more responsive to people's preferences.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43513/1/11111_2005_Article_BF01359051.pd

Social determinants of content selection in the age of (mis)information

Despite the enthusiastic rhetoric about the so called \emph{collective intelligence}, conspiracy theories -- e.g. global warming induced by chemtrails or the link between vaccines and autism -- find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite narratives may result in heated debates. In this work we provide a genuine example of information consumption from a sample of 1.2 million of Facebook Italian users. We show by means of a thorough quantitative analysis that information supporting different worldviews -- i.e. scientific and conspiracist news -- are consumed in a comparable way by their respective users. Moreover, we measure the effect of the exposure to 4709 evidently false information (satirical version of conspiracy theses) and to 4502 debunking memes (information aiming at contrasting unsubstantiated rumors) of the most polarized users of conspiracy claims. We find that either contrasting or teasing consumers of conspiracy narratives increases their probability to interact again with unsubstantiated rumors.Comment: misinformation, collective narratives, crowd dynamics, information spreadin

Diffraction Symmetry in Crystalline, Close-Packed C60

We have grown crystals of the carbon structure C60 by sublimation. In contrast to solution-grown crystals, the sublimed crystals have long range order with no evidence of solvent inclusions. Sublimed C60 forms three dimensional, faceted crystals with a close-packed, face-centered cubic unit cell. We have refined a crystal structure using the "soccer ball" model of the C60 molecule. The results indicate that the C60 molecule has the expected spherical shape, however the data are not sufficiently accurate to unambiguously determine atomic positions

Measuring proper motions of isolated neutron stars with Chandra

The excellent spatial resolution of the Chandra observatory offers the unprecedented possibility to measure proper motions at X-ray wavelength with relatively high accuracy using as reference the background of extragalactic or remote galactic X-ray sources. We took advantage of this capability to constrain the proper motion of RX J0806.4-4123 and RX J0420.0-5022, two X-ray bright and radio quiet isolated neutron stars (INSs) discovered by ROSAT and lacking an optical counterpart. In this paper, we present results from a preliminary analysis from which we derive 2 sigma upper limits of 76 mas/yr and 138 mas/yr on the proper motions of RX J0806.4-4123 and RX J0420.0-5022 respectively. We use these values together with those of other ROSAT discovered INSs to constrain the origin, distance and evolutionary status of this particular group of objects. We find that the tangential velocities of radio quiet ROSAT neutron stars are probably consistent with those of 'normal' pulsars. Their distribution on the sky and, for those having accurate proper motion vectors, their possible birth places, all point to a local population, probably created in the part of the Gould Belt nearest to the earth.Comment: 8 pages, 3 figures, to appear in Astrophysics and Space Science, in the proceedings of "Isolated Neutron Stars: from the Interior to the Surface", edited by D. Page, R. Turolla and S. Zan

The Effective Field Theory of Inflation

We study the effective field theory of inflation, i.e. the most general theory describing the fluctuations around a quasi de Sitter background, in the case of single field models. The scalar mode can be eaten by the metric by going to unitary gauge. In this gauge, the most general theory is built with the lowest dimension operators invariant under spatial diffeomorphisms, like g^{00} and K_{mu nu}, the extrinsic curvature of constant time surfaces. This approach allows us to characterize all the possible high energy corrections to simple slow-roll inflation, whose sizes are constrained by experiments. Also, it describes in a common language all single field models, including those with a small speed of sound and Ghost Inflation, and it makes explicit the implications of having a quasi de Sitter background. The non-linear realization of time diffeomorphisms forces correlation among different observables, like a reduced speed of sound and an enhanced level of non-Gaussianity.Comment: 26 pages. v2: minor corrections, JHEP published versio