Clustering Memes in Social Media

The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different kinds of activities, for example engineered misinformation campaigns versus spontaneous communication. Such detection problems require a formal definition of meme, or unit of information that can spread from person to person through the social network. Once a meme is identified, supervised learning methods can be applied to classify different types of communication. The appropriate granularity of a meme, however, is hardly captured from existing entities such as tags and keywords. Here we present a framework for the novel task of detecting memes by clustering messages from large streams of social data. We evaluate various similarity measures that leverage content, metadata, network features, and their combinations. We also explore the idea of pre-clustering on the basis of existing entities. A systematic evaluation is carried out using a manually curated dataset as ground truth. Our analysis shows that pre-clustering and a combination of heterogeneous features yield the best trade-off between number of clusters and their quality, demonstrating that a simple combination based on pairwise maximization of similarity is as effective as a non-trivial optimization of parameters. Our approach is fully automatic, unsupervised, and scalable for real-time detection of memes in streaming data.Comment: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'13), 201

Epitaxy of Fe3O4 on Si(001) by pulsed laser deposition using a TiN/MgO buffer layer

Epitaxy of oxide materials on silicon (Si) substrates is of great interest for future functional devices using the large variety of physical properties of the oxides as ferroelectricity, ferromagnetism, or superconductivity. Recently, materials with high spin polarization of the charge carriers have become interesting for semiconductor-oxide hybrid devices in spin electronics. Here, we report on pulsed laser deposition of magnetite (Fe3O4) on Si(001) substrates cleaned by an in situ laser beam high temperature treatment. After depositing a double buffer layer of titanium nitride (TiN) and magnesium oxide (MgO), a high quality epitaxial magnetite layer can be grown as verified by RHEED intensity oscillations and high resolution x-ray diffraction.Comment: submitte

Sub-unit cell layer-by-layer growth of Fe3O4, MgO, and Sr2RuO4 thin films

The use of oxide materials in oxide electronics requires their controlled epitaxial growth. Recently, it was shown that Reflection High Energy Electron Diffraction (RHEED) allows to monitor the growth of oxide thin films even at high oxygen pressure. Here, we report the sub-unit cell molecular or block layer growth of the oxide materials Sr2RuO4, MgO, and magnetite using Pulsed Laser Deposition (PLD) from stoichiometric targets. Whereas for perovskites such as SrTiO3 or doped LaMnO3 a single RHEED intensity oscillation is found to correspond to the growth of a single unit cell, in materials where the unit cell is composed of several molecular layers or blocks with identical stoichiometry, a sub-unit cell molecular or block layer growth is established resulting in several RHEED intensity oscillations during the growth of a single unit-cell

A Close-up Examination of Racial Disparities in Infant and Maternal Outcomes in Montgomery County, Ohio

Background: Infant and maternal outcomes in Montgomery County, Ohio, are among the worst in the state and rival that of many low-income nations. This study compares maternal and infant outcomes across 3 zip codes in Montgomery County to discern factors that are influencing health outcomes for their residents. The zip codes represent 3 distinct communities with unique racial and socioeconomic makeups. Methods: A cohort of mother-infant dyads (n=5098) who delivered at Miami Valley Hospital and Good Samaritan Hospital from January 1, 2009, to January 1, 2019, was analyzed via retrospective chart review. Maternal health outcome composite score (MCS) and infant health outcome composite score (ICS) from Trotwood, Ohio, (zip code 45426) were compared to those of 2 nearby zip codes (45415 and 45424), which were chosen for their lower infant mortality rates and proximity to Trotwood. Continuous variables were compared by ANOVA followed by post hoc Tukey tests. Categorical variables were compared via chi-square analysis. Results: The MCS and ICS were stratified by zip code and maternal age, race, and BMI. There was a statistically significant difference in MCS for race and BMI across all zip codes, but no statistically significant difference for maternal age. There was no statistically significant difference in ICS across maternal age, race, and BMI. Conclusion: Maternal outcomes for Black women were consistently worse across communities while outcomes for other races varied. Our study shows that maternal outcomes did not correlate with infant outcomes, indicating that interventions focusing on improving maternal outcomes may be inadequate at addressing infant outcomes. Investigations surrounding race-specific interventions in all populations are needed

On the relative intensity of Poisson’s spot

The Fresnel diffraction phenomenon referred to as Poisson’s spot or spot of Arago has, beside its historical significance, become relevant in a number of fields. Among them are for example fundamental tests of the super-position principle in the transition from quantum to classical physics and the search for extra-solar planets using star shades. Poisson’s spot refers to the positive on-axis wave interference in the shadow of any spherical or circular obstacle. While the spot’s intensity is equal to the undisturbed field in the plane wave picture, its intensity in general depends on a number of factors, namely the size and wavelength of the source, the size and surface corrugation of the diffraction obstacle, and the distances between source, obstacle and detector. The intensity can be calculated by solving the Fresnel–Kirchhoff diffraction integral numerically, which however tends to be computationally expensive. We have therefore devised an analytical model for the on-axis intensity of Poisson’s spot relative to the intensity of the undisturbed wave field and successfully validated it both using a simple light diffraction setup and numerical methods. The model will be useful for optimizing future Poisson-spot matter-wave diffraction experiments and determining under what experimental conditions the spot can be observed

Simulation-Based Planning of Optimal Conditions for Industrial Computed Tomography

We present a method to optimise conditions for industrial computed tomography (CT). This optimisation is based on a deterministic simulation. Our algorithm finds task-specific CT equipment settings to achieve optimal exposure parameters by means of an STL-model of the specimen and a raytracing method. These parameters are positioning and orientation of the specimen, X-ray tube voltage and prefilter thickness