Universal Dependencies Parsing for Colloquial Singaporean English

Singlish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media. We investigate dependency parsing of Singlish by constructing a dependency treebank under the Universal Dependencies scheme, and then training a neural network model by integrating English syntactic knowledge into a state-of-the-art parser trained on the Singlish treebank. Results show that English knowledge can lead to 25% relative error reduction, resulting in a parser of 84.47% accuracies. To the best of our knowledge, we are the first to use neural stacking to improve cross-lingual dependency parsing on low-resource languages. We make both our annotation and parser available for further research.Comment: Accepted by ACL 201

8-Methyl-5-methyl­ene-2-oxotricyclo[5.3.1.13,9]dodecan-endo-8-ol

The title compound, C14H20O2, crystallizes with homochiral chains of mol­ecules hydrogen bonded together along the b axis. Adjacent chains in the ab plane contain mol­ecules of the same chirality, leading to a chiral segregation of the mol­ecules into layers

Study of Glycine Soja Resistance to Aphis glycines. I. Screening of Resistant Varieties

A total of 985 wild and semi-wild soybean accessions were field screened for resistance to the aphid. The investigation involved inoculating A. glycines in cage houses, and was carried out for two years. We identified that three wild soybeans 85-32, 85-39 and 85-1 had resistance characters on A. glycines, whose resistance level was identified to be “High Resistance (HR)”. The aphid resistance characters in these three materials were higher than those found in cultivated soybean materials. The damage index difference significance level test and the observed growth rate of aphis populations also further demonstrated an obvious difference in the resistance characters between the wild soybeans and A. glycines; simultaneously, they validated the aphid resistance characters in the above three materials.Originating text in Chinese.Citation: Yue, Derong, Guo, Shougui, Chan, Yulian. (1989). Study of Glycine Soja Resistance to Aphis glycines. I. Screening of Resistant Varieties. Journal of Jilin Agricultural Sciences, 39(3), 15-39

Calculation of composition distribution of ultrafine ion-H2O-H2SO4 clusters using a modified binary ion nucleation theory

Thomson's ion nucleation theory was modified to include the effects of curvature dependence of the microscopic surface tension of field dependent, nonlinear, dielectric properties of the liquid; and of sulfuric acid hydrate formation in binary mixtures of water and sulfuric acid vapors. The modified theory leads to a broadening of the ion cluster spectrum, and shifts it towards larger numbers of H2O and H2SO4 molecules. Whether there is more shifting towards larger numbers of H2O or H2SO4 molecules depends on the relative humidity and relative acidity of the mixture. Usually, a broadening of the spectrum is accompanied by a lowering of the mean cluster intensity. For fixed values of relative humidity and relative acidity, a similar broadening pattern is observed when the temperature is lowered. These features of the modified theory illustrate that a trace of sulfuric acid can facilitate the formation of ultrafine, stable, prenucleation ion clusters as well as the growth of the prenucleation ion clusters towards the critical saddle point conditions, even with low values of relative humidity and relative acidity

Susceptibility to Social Engineering in Social Networking Sites: The Case of Facebook

Past research has suggested that social engineering poses the most significant security risk. Recent studies have suggested that social networking sites (SNSs) are the most common source of social engineering attacks. The risk of social engineering attacks in SNSs is associated with the difficulty of making accurate judgments regarding source credibility in the virtual environment of SNSs. In this paper, we quantitatively investigate source credibility dimensions in terms of social engineering on Facebook, as well as the source characteristics that influence Facebook users to judge an attacker as credible, therefore making them susceptible to victimization. Moreover, in order to predict users’ susceptibility to social engineering victimization based on their demographics, we investigate the effectiveness of source characteristics on different demographic groups by measuring the consent intentions and behavior responses of users to social engineering requests using a role-play experiment