Generation of degenerate, factorizable, pulsed squeezed light at telecom wavelengths

We characterize a periodically poled KTP crystal that produces an entangled, two-mode, squeezed state with orthogonal polarizations, nearly identical, factorizable frequency modes, and few photons in unwanted frequency modes. We focus the pump beam to create a nearly circular joint spectral probability distribution between the two modes. After disentangling the two modes, we observe Hong-Ou-Mandel interference with a raw (background corrected) visibility of 86 % (95 %) when an 8.6 nm bandwidth spectral filter is applied. We measure second order photon correlations of the entangled and disentangled squeezed states with both superconducting nanowire single-photon detectors and photon-number-resolving transition-edge sensors. Both methods agree and verify that the detected modes contain the desired photon number distributions

Irony Detection in Twitter: The Role of Affective Content

© ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Internet Technology, Vol. 16. http://dx.doi.org/10.1145/2930663.[EN] Irony has been proven to be pervasive in social media, posing a challenge to sentiment analysis systems. It is a creative linguistic phenomenon where affect-related aspects play a key role. In this work, we address the problem of detecting irony in tweets, casting it as a classification problem. We propose a novel model that explores the use of affective features based on a wide range of lexical resources available for English, reflecting different facets of affect. Classification experiments over different corpora show that affective information helps in distinguishing among ironic and nonironic tweets. Our model outperforms the state of the art in almost all cases.The National Council for Science and Technology (CONACyT Mexico) has funded the research work of Delia Irazu Hernandez Farias (Grant No. 218109/313683 CVU-369616). The work of Viviana Patti was partially carried out at the Universitat Politecnica de Valencia within the framework of a fellowship of the University of Turin cofunded by Fondazione CRT (World Wide Style Program 2). The work of Paolo Rosso has been partially funded by the SomEMBED TIN2015-71147-C2-1-P MINECO research project and by the Generalitat Valenciana under the grant ALMAMATER (PrometeoII/2014/030).Hernandez-Farias, DI.; Patti, V.; Rosso, P. (2016). Irony Detection in Twitter: The Role of Affective Content. ACM Transactions on Internet Technology. 16(3):19:1-19:24. https://doi.org/10.1145/2930663S19:119:24163Rob Abbott, Marilyn Walker, Pranav Anand, Jean E. Fox Tree, Robeson Bowmani, and Joseph King. 2011. 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The development of face orienting mechanisms in infants at-risk for autism

A popular idea related to early brain development in autism is that a lack of attention to, or interest in, social stimuli early in life interferes with the emergence of social brain networks mediating the typical development of socio-communicative skills. Compelling as it is, this developmental account has proved difficult to verify empirically because autism is typically diagnosed in toddlerhood, after this process of brain specialization is well underway. Using a prospective study, we directly tested the integrity of social orienting mechanisms in infants at-risk for autism by virtue of having an older diagnosed sibling. Contrary to previous accounts, infants who later develop autism exhibit a clear orienting response to faces that are embedded within an array of distractors. Nevertheless, infants at-risk for autism as a group, and irrespective of their subsequent outcomes, had a greater tendency to select and sustain attention to faces. This pattern suggests that interactions among multiple social and attentional brain systems over the first two years give rise to variable pathways in infants at-risk

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Bulu Tangkis Petunjuk Praktis untuk Pemula dan Lanjut

26 cm; 156 ha