Morpho-syntactic processing of Arabic plurals after aphasia: dissecting lexical meaning from morpho-syntax within word boundaries

Within the domain of inflectional morpho-syntax, differential processing of regular and irregular forms has been found in healthy speakers and in aphasia. One view assumes that irregular forms are retrieved as full entities, while regular forms are compiled on-line. An alternative view holds that a single mechanism oversees regular and irregular forms. Arabic offers an opportunity to study this phenomenon, as Arabic nouns contain a consonantal root, delivering lexical meaning, and a vocalic pattern, delivering syntactic information, such as gender and number. The aim of this study is to investigate morpho-syntactic processing of regular (sound) and irregular (broken) Arabic plurals in patients with morpho-syntactic impairment. Three participants with acquired agrammatic aphasia produced plural forms in a picture-naming task. We measured overall response accuracy, then analysed lexical errors and morpho-syntactic errors, separately. Error analysis revealed different patterns of morpho-syntactic errors depending on the type of pluralization (sound vs broken). Omissions formed the vast majority of errors in sound plurals, while substitution was the only error mechanism that occurred in broken plurals. The dissociation was statistically significant for retrieval of morpho-syntactic information (vocalic pattern) but not for lexical meaning (consonantal root), suggesting that the participants' selective impairment was an effect of the morpho-syntax of plurals. These results suggest that irregular plurals forms are stored, while regular forms are derived. The current findings support the findings from other languages and provide a new analysis technique for data from languages with non-concatenative morpho-syntax

Feature extraction and selection for Arabic tweets authorship authentication

© 2017, Springer-Verlag Berlin Heidelberg. In tweet authentication, we are concerned with correctly attributing a tweet to its true author based on its textual content. The more general problem of authenticating long documents has been studied before and the most common approach relies on the intuitive idea that each author has a unique style that can be captured using stylometric features (SF). Inspired by the success of modern automatic document classification problem, some researchers followed the Bag-Of-Words (BOW) approach for authenticating long documents. In this work, we consider both approaches and their application on authenticating tweets, which represent additional challenges due to the limitation in their sizes. We focus on the Arabic language due to its importance and the scarcity of works related on it. We create different sets of features from both approaches and compare the performance of different classifiers using them. We experiment with various feature selection techniques in order to extract the most discriminating features. To the best of our knowledge, this is the first study of its kind to combine these different sets of features for authorship analysis of Arabic tweets. The results show that combining all the feature sets we compute yields the best results

The Trifluoromethyl Group as a Bioisosteric Replacement of the Aliphatic Nitro Group in CB1 Receptor Positive Allosteric Modulators (PAMs)

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jmedchem.9b00252. Experimental procedures, characterization of all intermediates and target compounds, and copies of NMR spectra of compounds 1, 39-57. Molecular formula strings of target compounds are available. ACKNOWLEDGEMENTS. We gratefully thank Signal Pharma and the Canadian Institutes of Health Research Proof of Principle grants PPP-125784 and PP2-139101 for financial support and fellowship (C.C.T), NIH grants R01DA039942, P30DA033934 and VCU School of Pharmacy start-up funds (A.H.L.). We thank the EPSRC National Crystallography Service (University of Southampton) for the X-ray data collection. We are grateful to Dr Monica Sani (CNR-ICRM, Milan, Italy) and Mr Massimo Frigerio (Politecnico di Milano, Italy) for the synthesis of two tetrazole-substituted indoles (Het-1 and Het-2)Peer reviewedPostprin

Overview of the PAN/CLEF 2015 Evaluation Lab

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-24027-5_49This paper presents an overview of the PAN/CLEF evaluation lab. During the last decade, PAN has been established as the main forum of text mining research focusing on the identification of personal traits of authors left behind in texts unintentionally. PAN 2015 comprises three tasks: plagiarism detection, author identification and author profiling studying important variations of these problems. In plagiarism detection, community-driven corpus construction is introduced as a new way of developing evaluation resources with diversity. In author identification, cross-topic and cross-genre author verification (where the texts of known and unknown authorship do not match in topic and/or genre) is introduced. A new corpus was built for this challenging, yet realistic, task covering four languages. In author profiling, in addition to usual author demographics, such as gender and age, five personality traits are introduced (openness, conscientiousness, extraversion, agreeableness, and neuroticism) and a new corpus of Twitter messages covering four languages was developed. In total, 53 teams participated in all three tasks of PAN 2015 and, following the practice of previous editions, software submissions were required and evaluated within the TIRA experimentation framework.Stamatatos, E.; Potthast, M.; Rangel, F.; Rosso, P.; Stein, B. (2015). Overview of the PAN/CLEF 2015 Evaluation Lab. En Experimental IR Meets Multilinguality, Multimodality, and Interaction: 6th International Conference of the CLEF Association, CLEF'15, Toulouse, France, September 8-11, 2015, Proceedings. Springer International Publishing. 518-538. doi:10.1007/978-3-319-24027-5_49S518538Álvarez-Carmona, M.A., López-Monroy, A.P., Montes-Y-Gómez, M., Villaseñor-Pineda, L., Jair-Escalante, H.: INAOE’s participation at PAN 2015: author profiling task–notebook for PAN at CLEF 2015. In: CLEF 2013 Working Notes. CEUR (2015)Argamon, S., Koppel, M., Fine, J., Shimoni, A.R.: Gender, Genre, and Writing Style in Formal Written Texts. TEXT 23, 321–346 (2003)Bagnall, D.: Author identification using multi-headed recurrent neural networks. In: CLEF 2015 Working Notes. CEUR (2015)Burger, J.D., Henderson, J., Kim, G., Zarrella, G.: Discriminating gender on twitter. In: Proceedings of EMNLP 2011. ACL (2011)Burrows, S., Potthast, M., Stein, B.: Paraphrase Acquisition via Crowdsourcing and Machine Learning. ACM TIST 4(3), 43:1–43:21 (2013)Castillo, E., Cervantes, O., Vilariño, D., Pinto, D., León, S.: Unsupervised method for the authorship identification task. In: CLEF 2014 Labs and Workshops, Notebook Papers. CEUR (2014)Celli, F., Lepri, B., Biel, J.I., Gatica-Perez, D., Riccardi, G., Pianesi, F.: The workshop on computational personality recognition 2014. In: Proceedings of ACM MM 2014 (2014)Celli, F., Pianesi, F., Stillwell, D., Kosinski, M.: Workshop on computational personality recognition: shared task. In: Proceedings of WCPR at ICWSM 2013 (2013)Celli, F., Polonio, L.: Relationships between personality and interactions in facebook. In: Social Networking: Recent Trends, Emerging Issues and Future Outlook. Nova Science Publishers, Inc. (2013)Chaski, C.E.: Who’s at the Keyboard: Authorship Attribution in Digital Evidence Invesigations. International Journal of Digital Evidence 4 (2005)Chittaranjan, G., Blom, J., Gatica-Perez, D.: Mining Large-scale Smartphone Data for Personality Studies. Personal and Ubiquitous Computing 17(3), 433–450 (2013)Fréry, J., Largeron, C., Juganaru-Mathieu, M.: UJM at clef in author identification. In: CLEF 2014 Labs and Workshops, Notebook Papers. CEUR (2014)Gollub, T., Potthast, M., Beyer, A., Busse, M., Rangel, F., Rosso, P., Stamatatos, E., Stein, B.: Recent trends in digital text forensics and its evaluation. In: Forner, P., Müller, H., Paredes, R., Rosso, P., Stein, B. (eds.) CLEF 2013. LNCS, vol. 8138, pp. 282–302. Springer, Heidelberg (2013)Gollub, T., Stein, B., Burrows, S.: Ousting ivory tower research: towards a web framework for providing experiments as a service. In: Proceedings of SIGIR 2012. ACM (2012)Hagen, M., Potthast, M., Stein, B.: Source retrieval for plagiarism detection from large web corpora: recent approaches. In: CLEF 2015 Working Notes. CEUR (2015)van Halteren, H.: Linguistic profiling for author recognition and verification. In: Proceedings of ACL 2004. ACL (2004)Holmes, J., Meyerhoff, M.: The Handbook of Language and Gender. Blackwell Handbooks in Linguistics. Wiley (2003)Jankowska, M., Keselj, V., Milios, E.: CNG text classification for authorship profiling task–notebook for PAN at CLEF 2013. In: CLEF 2013 Working Notes. CEUR (2013)Juola, P.: Authorship Attribution. Foundations and Trends in Information Retrieval 1, 234–334 (2008)Juola, P.: How a Computer Program Helped Reveal J.K. Rowling as Author of A Cuckoo’s Calling. Scientific American (2013)Juola, P., Stamatatos, E.: Overview of the author identification task at PAN-2013. In: CLEF 2013 Working Notes. CEUR (2013)Kalimeri, K., Lepri, B., Pianesi, F.: Going beyond traits: multimodal classification of personality states in the wild. In: Proceedings of ICMI 2013. ACM (2013)Koppel, M., Argamon, S., Shimoni, A.R.: Automatically Categorizing Written Texts by Author Gender. Literary and Linguistic Computing 17(4) (2002)Koppel, M., Schler, J., Bonchek-Dokow, E.: Measuring Differentiability: Unmasking Pseudonymous Authors. J. Mach. Learn. Res. 8, 1261–1276 (2007)Koppel, M., Winter, Y.: Determining if Two Documents are Written by the same Author. Journal of the American Society for Information Science and Technology 65(1), 178–187 (2014)Kosinski, M., Bachrach, Y., Kohli, P., Stillwell, D., Graepel, T.: Manifestations of User Personality in Website Choice and Behaviour on Online Social Networks. Machine Learning (2013)López-Monroy, A.P., y Gómez, M.M., Jair-Escalante, H., Villaseñor-Pineda, L.: Using intra-profile information for author profiling–notebook for PAN at CLEF 2014. In: CLEF 2014 Working Notes. CEUR (2014)Lopez-Monroy, A.P., Montes-Y-Gomez, M., Escalante, H.J., Villasenor-Pineda, L., Villatoro-Tello, E.: INAOE’s participation at PAN 2013: author profiling task-notebook for PAN at CLEF 2013. In: CLEF 2013 Working Notes. CEUR (2013)Luyckx, K., Daelemans, W.: Authorship attribution and verification with many authors and limited data. In: Proceedings of COLING 2008 (2008)Maharjan, S., Shrestha, P., Solorio, T., Hasan, R.: A straightforward author profiling approach in mapreduce. In: Bazzan, A.L.C., Pichara, K. (eds.) IBERAMIA 2014. LNCS, vol. 8864, pp. 95–107. Springer, Heidelberg (2014)Mairesse, F., Walker, M.A., Mehl, M.R., Moore, R.K.: Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text. Journal of Artificial Intelligence Research 30(1), 457–500 (2007)Eissen, S.M., Stein, B.: Intrinsic plagiarism detection. In: Lalmas, M., MacFarlane, A., Rüger, S.M., Tombros, A., Tsikrika, T., Yavlinsky, A. (eds.) ECIR 2006. LNCS, vol. 3936, pp. 565–569. Springer, Heidelberg (2006)Mohammadi, G., Vinciarelli, A.: Automatic personality perception: Prediction of Trait Attribution Based on Prosodic Features. IEEE Transactions on Affective Computing 3(3), 273–284 (2012)Moreau, E., Jayapal, A., Lynch, G., Vogel, C.: Author verification: basic stacked generalization applied to predictions from a set of heterogeneous learners. In: CLEF 2015 Working Notes. CEUR (2015)Nguyen, D., Gravel, R., Trieschnigg, D., Meder, T.: “How old do you think I am?”; a study of language and age in twitter. In: Proceedings of ICWSM 2013. AAAI (2013)Oberlander, J., Nowson, S.: Whose thumb is it anyway?: classifying author personality from weblog text. In: Proceedings of COLING 2006. ACL (2006)Peñas, A., Rodrigo, A.: A simple measure to assess non-response. In: Proceedings of HLT 2011. ACL (2011)Pennebaker, J.W., Mehl, M.R., Niederhoffer, K.G.: Psychological Aspects of Natural Language Use: Our Words. Our Selves. Annual Review of Psychology 54(1), 547–577 (2003)Potthast, M., Barrón-Cedeño, A., Eiselt, A., Stein, B., Rosso, P.: Overview of the 2nd international competition on plagiarism detection. In: CLEF 2010 Working Notes. CEUR (2010)Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-Language Plagiarism Detection. Language Resources and Evaluation (LRE) 45, 45–62 (2011)Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd international competition on plagiarism detection. In: CLEF 2011 Working Notes (2011)Potthast, M., Gollub, T., Hagen, M., Graßegger, J., Kiesel, J., Michel, M., Oberländer, A., Tippmann, M., Barrón-Cedeño, A., Gupta, P., Rosso, P., Stein, B.: Overview of the 4th international competition on plagiarism detection. In: CLEF 2012 Working Notes. CEUR (2012)Potthast, M., Gollub, T., Hagen, M., Tippmann, M., Kiesel, J., Rosso, P., Stamatatos, E., Stein, B.: Overview of the 5th international competition on plagiarism detection. In: CLEF 2013 Working Notes. CEUR (2013)Potthast, M., Gollub, T., Rangel, F., Rosso, P., Stamatatos, E., Stein, B.: Improving the reproducibility of PAN’s shared tasks: plagiarism detection, author identification, and author profiling. In: Kanoulas, E., Lupu, M., Clough, P., Sanderson, M., Hall, M., Hanbury, A., Toms, E. (eds.) CLEF 2014. LNCS, vol. 8685, pp. 268–299. Springer, Heidelberg (2014)Potthast, M., Hagen, M., Beyer, A., Busse, M., Tippmann, M., Rosso, P., Stein, B.: Overview of the 6th international competition on plagiarism detection. In: CLEF 2014 Working Notes. CEUR (2014)Potthast, M., Göring, S., Rosso, P., Stein, B.: Towards data submissions for shared tasks: first experiences for the task of text alignment. In: CLEF 2015 Working Notes. CEUR (2015)Potthast, M., Hagen, M., Stein, B., Graßegger, J., Michel, M., Tippmann, M., Welsch, C.: ChatNoir: a search engine for the clueweb09 corpus. In: Proceedings of SIGIR 2012. ACM (2012)Potthast, M., Hagen, M., Völske, M., Stein, B.: Crowdsourcing interaction logs to understand text reuse from the web. In: Proceedings of ACL 2013. ACL (2013)Potthast, M., Stein, B., Barrón-Cedeño, A., Rosso, P.: An evaluation framework for plagiarism detection. In: Proceedings of COLING 2010. ACL (2010)Potthast, M., Stein, B., Eiselt, A., Barrón-Cedeño, A., Rosso, P.: Overview of the 1st international competition on plagiarism detection. In: Proceedings of PAN at SEPLN 2009. CEUR (2009)Quercia, D., Lambiotte, R., Stillwell, D., Kosinski, M., Crowcroft, J.: The personality of popular facebook users. In: Proceedings of CSCW 2012. ACM (2012)Rammstedt, B., John, O.: Measuring Personality in One Minute or Less: A 10 Item Short Version of the Big Five Inventory in English and German. Journal of Research in Personality (2007)Rangel, F., Rosso, P.: On the impact of emotions on author profiling. In: Information Processing & Management, Special Issue on Emotion and Sentiment in Social and Expressive Media (2014) (in press)Rangel, F., Rosso, P., Celli, F., Potthast, M., Stein, B., Daelemans, W.: Overview of the 3rd author profiling task at PAN 2015. In: CLEF 2015 Working Notes. CEUR (2015)Rangel, F., Rosso, P., Chugur, I., Potthast, M., Trenkmann, M., Stein, B., Verhoeven, B., Daelemans, W.: Overview of the 2nd author profiling task at PAN 2014. In: CLEF 2014 Working Notes. CEUR (2014)Rangel, F., Rosso, P., Koppel, M., Stamatatos, E., Inches, G.: Overview of the author profiling task at PAN 2013–notebook for PAN at CLEF 2013. In: CLEF 2013 Working Notes. CEUR (2013)Sapkota, U., Bethard, S., Montes-y-Gómez, M., Solorio, T.: Not all character N-grams are created equal: a study in authorship attribution. In: Proceedings of NAACL 2015. ACL (2015)Sapkota, U., Solorio, T., Montes-y-Gómez, M., Bethard, S., Rosso, P.: Cross-topic authorship attribution: will out-of-topic data help? In: Proceedings of COLING 2014 (2014)Schler, J., Koppel, M., Argamon, S., Pennebaker, J.W.: Effects of age and gender on blogging. In: AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs. AAAI (2006)Schwartz, H.A., Eichstaedt, J.C., Kern, M.L., Dziurzynski, L., Ramones, S.M., Agrawal, M., Shah, A., Kosinski, M., Stillwell, D., Seligman, M.E., et al.: Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach. PloS one 8(9), 773–791 (2013)Stamatatos, E.: A Survey of Modern Authorship Attribution Methods. Journal of the American Society for Information Science and Technology 60, 538–556 (2009)Stamatatos, E.: On the Robustness of Authorship Attribution Based on Character N-gram Features. Journal of Law and Policy 21, 421–439 (2013)Stamatatos, E., Daelemans, W., Verhoeven, B., Juola, P., López-López, A., Potthast, M., Stein, B.: Overview of the author identification task at PAN 2015. 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Artificial Sequences and Complexity Measures

In this paper we exploit concepts of information theory to address the fundamental problem of identifying and defining the most suitable tools to extract, in a automatic and agnostic way, information from a generic string of characters. We introduce in particular a class of methods which use in a crucial way data compression techniques in order to define a measure of remoteness and distance between pairs of sequences of characters (e.g. texts) based on their relative information content. We also discuss in detail how specific features of data compression techniques could be used to introduce the notion of dictionary of a given sequence and of Artificial Text and we show how these new tools can be used for information extraction purposes. We point out the versatility and generality of our method that applies to any kind of corpora of character strings independently of the type of coding behind them. We consider as a case study linguistic motivated problems and we present results for automatic language recognition, authorship attribution and self consistent-classification.Comment: Revised version, with major changes, of previous "Data Compression approach to Information Extraction and Classification" by A. Baronchelli and V. Loreto. 15 pages; 5 figure

Erroneous selection of a non-target item improves subsequent target identification in rapid serial visual presentations

The second of two targets (T2) embedded in a rapid serial visual presentation (RSVSVP) is often missed even though the first (T1) is correctly reported (attentional blink). The rate of correct T2 identification is quite high, however, when T2 comes immediately after T1 (lag-1 sparing). This study investigated whether and how non-target items induce lag-1 sparing. One T1 and two T2s comprising letters were inserted in distractors comprising symbols in each of two synchronised RSVSVPs. A digit (dummy) was presented with T1 in another stream. Lag-1 sparing occurred even at the location where the dummy was present (Experiment 1). This distractor-induced sparing effect was also obtained even when a Japanese katakana character (Experiment 2) was used as the dummy. The sparing effect was, however, severely weakened when symbols (Experiment 3) and Hebrew letters (Experiment 4) served as the dummy. Our findings suggest a tentative hypothesis that attentional set for item nameability is meta-categorically created and adopted to the dummy only when the dummy is nameable

The rate of telomere loss is related to maximum lifespan in birds

Telomeres are highly conserved regions of DNA that protect the ends of linear chromosomes. The loss of telomeres can signal an irreversible change to a cell's state, including cellular senescence. Senescent cells no longer divide and can damage nearby healthy cells, thus potentially placing them at the crossroads of cancer and ageing. While the epidemiology, cellular and molecular biology of telomeres are well studied, a newer field exploring telomere biology in the context of ecology and evolution is just emerging. With work to date focusing on how telomere shortening relates to individual mortality, less is known about how telomeres relate to ageing rates across species. Here, we investigated telomere length in cross-sectional samples from 19 bird species to determine how rates of telomere loss relate to interspecific variation in maximum lifespan. We found that bird species with longer lifespans lose fewer telomeric repeats each year compared with species with shorter lifespans. In addition, phylogenetic analysis revealed that the rate of telomere loss is evolutionarily conserved within bird families. This suggests that the physiological causes of telomere shortening, or the ability to maintain telomeres, are features that may be responsible for, or co-evolved with, different lifespans observed across species.This article is part of the theme issue 'Understanding diversity in telomere dynamics'

How Digital Are the Digital Humanities? An Analysis of Two Scholarly Blogging Platforms

In this paper we compare two academic networking platforms, HASTAC and Hypotheses, to show the distinct ways in which they serve specific communities in the Digital Humanities (DH) in different national and disciplinary contexts. After providing background information on both platforms, we apply co-word analysis and topic modeling to show thematic similarities and differences between the two sites, focusing particularly on how they frame DH as a new paradigm in humanities research. We encounter a much higher ratio of posts using humanities-related terms compared to their digital counterparts, suggesting a one-way dependency of digital humanities-related terms on the corresponding unprefixed labels. The results also show that the terms digital archive, digital literacy, and digital pedagogy are relatively independent from the respective unprefixed terms, and that digital publishing, digital libraries, and digital media show considerable cross-pollination between the specialization and the general noun. The topic modeling reproduces these findings and reveals further differences between the two platforms. Our findings also indicate local differences in how the emerging field of DH is conceptualized and show dynamic topical shifts inside these respective contexts