#Bieber + #Blast = #BieberBlast: Early Prediction of Popular Hashtag Compounds

Compounding of natural language units is a very common phenomena. In this paper, we show, for the first time, that Twitter hashtags which, could be considered as correlates of such linguistic units, undergo compounding. We identify reasons for this compounding and propose a prediction model that can identify with 77.07% accuracy if a pair of hashtags compounding in the near future (i.e., 2 months after compounding) shall become popular. At longer times T = 6, 10 months the accuracies are 77.52% and 79.13% respectively. This technique has strong implications to trending hashtag recommendation since newly formed hashtag compounds can be recommended early, even before the compounding has taken place. Further, humans can predict compounds with an overall accuracy of only 48.7% (treated as baseline). Notably, while humans can discriminate the relatively easier cases, the automatic framework is successful in classifying the relatively harder cases.Comment: 14 pages, 4 figures, 9 tables, published in CSCW (Computer-Supported Cooperative Work and Social Computing) 2016. in Proceedings of 19th ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2016

Ag/mgo nanoparticles via gas aggregation nanocluster source for perovskite solar cell engineering

Nanocluster aggregation sources based on magnetron-sputtering represent precise and versatile means to deposit a controlled quantity of metal nanoparticles at selected interfaces. In this work, we exploit this methodology to produce Ag/MgO nanoparticles (NPs) and deposit them on a glass/FTO/TiO2 substrate, which constitutes the mesoscopic front electrode of a monolithic perovskite-based solar cell (PSC). Herein, the Ag NP growth through magnetron sputtering and gas aggregation, subsequently covered with MgO ultrathin layers, is fully characterized in terms of structural and morphological properties while thermal stability and endurance against air-induced oxidation are demonstrated in accordance with PSC manufacturing processes. Finally, once the NP coverage is optimized, the Ag/MgO engineered PSCs demonstrate an overall increase of 5% in terms of device power conversion efficiencies (up to 17.8%)

Appropriate model use for predicting elevations and inundation extent for extreme flood events

Flood risk assessment is generally studied using flood simulation models; however, flood risk managers often simplify the computational process; this is called a “simplification strategy”. This study investigates the appropriateness of the “simplification strategy” when used as a flood risk assessment tool for areas prone to flash flooding. The 2004 Boscastle, UK, flash flood was selected as a case study. Three different model structures were considered in this study, including: (1) a shock-capturing model, (2) a regular ADI-type flood model and (3) a diffusion wave model, i.e. a zero-inertia approach. The key findings from this paper strongly suggest that applying the “simplification strategy” is only appropriate for flood simulations with a mild slope and over relatively smooth terrains, whereas in areas susceptible to flash flooding (i.e. steep catchments), following this strategy can lead to significantly erroneous predictions of the main parameters—particularly the peak water levels and the inundation extent. For flood risk assessment of urban areas, where the emergence of flash flooding is possible, it is shown to be necessary to incorporate shock-capturing algorithms in the solution procedure, since these algorithms prevent the formation of spurious oscillations and provide a more realistic simulation of the flood levels

Development and validation of a simple questionnaire for the identification of hereditary breast cancer in primary care

<p>Abstract</p> <p>Background</p> <p>Breast cancer is a significant public health problem worldwide and the development of tools to identify individuals at-risk for hereditary breast cancer syndromes, where specific interventions can be proposed to reduce risk, has become increasingly relevant. A previous study in Southern Brazil has shown that a family history suggestive of these syndromes may be prevalent at the primary care level. Development of a simple and sensitive instrument, easily applicable in primary care units, would be particularly helpful in underserved communities in which identification and referral of high-risk individuals is difficult.</p> <p>Methods</p> <p>A simple 7-question instrument about family history of breast, ovarian and colorectal cancer, FHS-7, was developed to screen for individuals with an increased risk for hereditary breast cancer syndromes. FHS-7 was applied to 9218 women during routine visits to primary care units in Southern Brazil. Two consecutive samples of 885 women and 910 women who answered positively to at least one question and negatively to all questions were included, respectively. The sensitivity, specificity and positive and negative predictive values were determined.</p> <p>Results</p> <p>Of the 885 women reporting a positive family history, 211 (23.8%; CI95%: 21.5–26.2) had a pedigree suggestive of a hereditary breast and/or breast and colorectal cancer syndrome. Using as cut point one positive answer, the sensitivity and specificity of the instrument were 87.6% and 56.4%, respectively. Concordance between answers in two different applications was given by a intra-class correlation (ICC) of 0.84 for at least one positive answer. Temporal stability of the instrument was adequate (ICC = 0.65).</p> <p>Conclusion</p> <p>A simple instrument for the identification of the most common hereditary breast cancer syndrome phenotypes, showing good specificity and temporal stability was developed and could be used as a screening tool in primary care to refer at-risk individuals for genetic evaluations.</p